diff --git a/.gitignore b/.gitignore index 99f167443..0d679c07f 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ site/ .DS_Store -venv/ +venv*/ +.vscode/ diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 000000000..8dbb36353 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,6 @@ +repos: +- repo: git@github.com:Yelp/detect-secrets + rev: v0.13.1 + hooks: + - id: detect-secrets + args: ['--baseline', '.secrets.baseline'] \ No newline at end of file diff --git a/.secrets.baseline b/.secrets.baseline new file mode 100644 index 000000000..a22082a8b --- /dev/null +++ b/.secrets.baseline @@ -0,0 +1,220 @@ +{ + "exclude": { + "files": null, + "lines": null + }, + "generated_at": "2023-11-30T17:33:04Z", + "plugins_used": [ + { + "name": "AWSKeyDetector" + }, + { + "name": "ArtifactoryDetector" + }, + { + "base64_limit": 4.5, + "name": "Base64HighEntropyString" + }, + { + "name": "BasicAuthDetector" + }, + { + "name": "CloudantDetector" + }, + { + "hex_limit": 3, + "name": "HexHighEntropyString" + }, + { + "name": "IbmCloudIamDetector" + }, + { + "name": "IbmCosHmacDetector" + }, + { + "name": "JwtTokenDetector" + }, + { + "keyword_exclude": null, + "name": "KeywordDetector" + }, + { + "name": "MailchimpDetector" + }, + { + "name": "PrivateKeyDetector" + }, + { + "name": "SlackDetector" + }, + { + "name": "SoftlayerDetector" + }, + { + "name": "StripeDetector" + }, + { + "name": "TwilioKeyDetector" + } + ], + "results": { + "docs/API/Users_Guide/Additional_Examples.md": [ + { + "hashed_secret": "d9bbc424159a2c5ef89902e02caa2be6cff1817c", + "is_secret": false, + "is_verified": false, + "line_number": 89, + "type": "Hex High Entropy String" + }, + { + "hashed_secret": "34d2afab6dc6f76855d5f83cc2dbed2efd99ddfb", + "is_secret": false, + "is_verified": false, + "line_number": 110, + "type": "Hex High Entropy String" + } + ], + "docs/API/Users_Guide/Getting_Started.md": [ + { + "hashed_secret": 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"87d7b59b5af7c86ea71b60ed042d1e62175136fb", + "is_secret": false, + "is_verified": false, + "line_number": 86, + "type": "Hex High Entropy String" + } + ], + "docs/Data_Submission_Portal/Users_Guide/Data_Submission_Walkthrough.md": [ + { + "hashed_secret": "87d7b59b5af7c86ea71b60ed042d1e62175136fb", + "is_secret": false, + "is_verified": false, + "line_number": 651, + "type": "Hex High Entropy String" + } + ], + "docs/Data_Submission_Portal/Users_Guide/Data_Upload_UG.md": [ + { + "hashed_secret": "dbaf99f4789432509c1313aba5256a6ea4ddb986", + "is_secret": false, + "is_verified": false, + "line_number": 482, + "type": "Hex High Entropy String" + }, + { + "hashed_secret": "471568dffba5b4873ca000b88049046d5aa687d4", + "is_secret": false, + "is_verified": false, + "line_number": 553, + "type": "Hex High Entropy String" + }, + { + "hashed_secret": "87d7b59b5af7c86ea71b60ed042d1e62175136fb", + "is_secret": false, + "is_verified": false, + "line_number": 765, + "type": "Hex High Entropy String" + } + ], + "theme/css/font-awesome-4.5.css": [ + { + "hashed_secret": "51de2b835bd35a67eb32dbcd3d77d4b96e5aa39d", + "is_secret": false, + "is_verified": false, + "line_number": 1734, + "type": "Secret Keyword" + } + ], + "theme/css/font-awesome.min-4.5.css": [ + { + "hashed_secret": "3e4128ccd5d7d597667230af6326b3387fd18545", + "is_secret": false, + "is_verified": false, + "line_number": 4, + "type": "Secret Keyword" + } + ] + }, + "version": "0.13.1", + "word_list": { + "file": null, + "hash": null + } +} diff --git a/API_UG.yml b/API_UG.yml index 83d08700a..91b8c60d0 100644 --- a/API_UG.yml +++ b/API_UG.yml @@ -16,6 +16,7 @@ pages: - BAM Slicing: 'API/Users_Guide/BAM_Slicing.md' - Submission: 'API/Users_Guide/Submission.md' - Python Examples: 'API/Users_Guide/Python_Examples.md' + - GraphQL Examples: 'API/Users_Guide/GraphQL_Examples.md' - System Information: 'API/Users_Guide/System_Information.md' - Additional Examples: 'API/Users_Guide/Additional_Examples.md' - "Appendix A: Available Fields": 'API/Users_Guide/Appendix_A_Available_Fields.md' diff --git a/Adding_write_to_file.md b/Adding_write_to_file.md new file mode 100644 index 000000000..39a5cb741 --- /dev/null +++ b/Adding_write_to_file.md @@ -0,0 +1,14 @@ +# Changes made 2-5-2021 + +An extra script added to the following scripts, to redirect a copy of the output to a file: + +``` +- A Basic Query + +- A Filtered Query + +- Complex Filters + +- Basic Troubleshooting +``` +Also the ```.PY``` files in ```scripts``` folder were updated accordingly. diff --git a/Data_Portal_UG.yml b/Data_Portal_UG.yml index b74dd45d9..7cab3b7e4 100644 --- a/Data_Portal_UG.yml +++ b/Data_Portal_UG.yml @@ -9,18 +9,22 @@ copyright: "© 2015-2016" theme_dir: theme pages: - Data Portal: - - Getting Started: 'Data_Portal/Users_Guide/Getting_Started.md' + - Getting Started: 'Data_Portal/Users_Guide/getting_started.md' + - Quick Start: 'Data_Portal/Users_Guide/quick_start.md' + - Cohort Builder: 'Data_Portal/Users_Guide/cohort_builder.md' + - Analysis Center: 'Data_Portal/Users_Guide/analysis_center.md' + - Repository: 'Data_Portal/Users_Guide/Repository.md' - Projects: 'Data_Portal/Users_Guide/Projects.md' - - Exploration: Data_Portal/Users_Guide/Exploration.md - - Repository: Data_Portal/Users_Guide/Repository.md - - Genes and Mutations: Data_Portal/Users_Guide/Genes_and_Mutations.md - - Custom Set Analysis: Data_Portal/Users_Guide/Custom_Set_Analysis.md - - Annotations: 'Data_Portal/Users_Guide/Annotations.md' - - Advanced Search: 'Data_Portal/Users_Guide/Advanced_Search.md' - - Authentication: 'Data_Portal/Users_Guide/Authentication.md' - - File Cart: 'Data_Portal/Users_Guide/Cart.md' - - Image Viewer: 'Data_Portal/Users_Guide/Image_viewer.md' - - Legacy Archive: 'Data_Portal/Users_Guide/Legacy_Archive.md' + - BAM Slicing: 'Data_Portal/Users_Guide/BAMslicing.md' + - Clinical Data Analysis: 'Data_Portal/Users_Guide/clinical_data_analysis.md' + - Cohort Comparison: 'Data_Portal/Users_Guide/cohort_comparison.md' + - Gene Expression Clustering: 'Data_Portal/Users_Guide/gene_expression_clustering.md' + - Mutation Frequency: 'Data_Portal/Users_Guide/mutation_frequency.md' + - OncoMatrix: 'Data_Portal/Users_Guide/oncomatrix.md' + - ProteinPaint: 'Data_Portal/Users_Guide/proteinpaint_lollipop.md' + - Sequence Reads: 'Data_Portal/Users_Guide/proteinpaint_bam.md' + - Set Operations: 'Data_Portal/Users_Guide/set_operations.md' + - For Developers: 'Data_Portal/Users_Guide/Developers_Guide.md' - Release Notes: 'Data_Portal/Release_Notes/Data_Portal_Release_Notes.md' extra: project_root_dir: '/' diff --git a/Data_Portal_V1_UG.yml b/Data_Portal_V1_UG.yml new file mode 100644 index 000000000..46e8e8061 --- /dev/null +++ b/Data_Portal_V1_UG.yml @@ -0,0 +1,27 @@ +# +# GDC Docs - Config +# + +site_name: GDC Docs +site_url: http://docs.gdc.cancer.gov +repo_url: https://github.com/NCI-GDC/gdc-docs +copyright: "© 2015-2016" +theme_dir: theme +pages: +- Data Portal v1.0: + - Getting Started: 'Data_Portal_V1/Users_Guide/Getting_Started.md' + - Projects: 'Data_Portal_V1/Users_Guide/Projects.md' + - Exploration: Data_Portal_V1/Users_Guide/Exploration.md + - Repository: Data_Portal_V1/Users_Guide/Repository.md + - Genes and Mutations: Data_Portal_V1/Users_Guide/Genes_and_Mutations.md + - Annotations: 'Data_Portal_V1/Users_Guide/Annotations.md' + - Advanced Search: 'Data_Portal_V1/Users_Guide/Advanced_Search.md' + - Authentication: 'Data_Portal_V1/Users_Guide/Authentication.md' + - File Cart: 'Data_Portal_V1/Users_Guide/Cart.md' + - Image Viewer: 'Data_Portal_V1/Users_Guide/Image_viewer.md' + - Release Notes: 'Data_Portal_V1/Release_Notes/Data_Portal_V1_Release_Notes.md' +extra: + project_root_dir: '/' + project_org: 'GDC' + project_description: 'GDC Docs' + version: 1.0 diff --git a/Data_Submission_Portal_UG.yml b/Data_Submission_Portal_UG.yml index b00ffc3d2..0f9f5f4c5 100644 --- a/Data_Submission_Portal_UG.yml +++ b/Data_Submission_Portal_UG.yml @@ -9,19 +9,13 @@ copyright: "© 2015-2016" theme_dir: theme pages: - Data Submission Portal: - - Getting Started: 'Data_Submission_Portal/Users_Guide/Getting_Started.md' - - Submission Workflow: 'Data_Submission_Portal/Users_Guide/Submission_Workflow.md' - - Authentication: 'Data_Submission_Portal/Users_Guide/Authentication.md' - - Homepage: 'Data_Submission_Portal/Users_Guide/Homepage.md' - - Dashboard: 'Data_Submission_Portal/Users_Guide/Dashboard.md' - - Upload Data: 'Data_Submission_Portal/Users_Guide/Data_Upload_UG.md' - - Submit Data: 'Data_Submission_Portal/Users_Guide/Submit_Data.md' - - Release Data: 'Data_Submission_Portal/Users_Guide/Release_Data.md' - - Transactions: 'Data_Submission_Portal/Users_Guide/Transactions.md' - - Browse Data: 'Data_Submission_Portal/Users_Guide/Browse_Data.md' - - Pre-Release Data Review: 'Data_Submission_Portal/Users_Guide/Pre_Release_QC.md' - - Best Practices: 'Data_Submission_Portal/Users_Guide/Best_Practices.md' + - Before Submitting Data to the GDC Portal: 'Data_Submission_Portal/Users_Guide/Checklist.md' + - Data Submission Overview: 'Data_Submission_Portal/Users_Guide/Data_Submission_Overview.md' + - Data Submission Portal: 'Data_Submission_Portal/Users_Guide/Data_Submission_Process.md' + - Data Upload Walkthrough: 'Data_Submission_Portal/Users_Guide/Data_Submission_Walkthrough.md' + - Pre-Release Data Portal: 'Data_Submission_Portal/Users_Guide/Pre_Release_QC.md' - Release Notes: 'Data_Submission_Portal/Release_Notes/Data_Submission_Portal_Release_Notes.md' + extra: project_root_dir: '/' project_org: 'GDC' diff --git a/Data_Transfer_Tool_UG.yml b/Data_Transfer_Tool_UG.yml index d8e7a47f4..a474a63af 100644 --- a/Data_Transfer_Tool_UG.yml +++ b/Data_Transfer_Tool_UG.yml @@ -10,12 +10,10 @@ theme_dir: theme pages: - Data Transfer Tool: - Getting Started: 'Data_Transfer_Tool/Users_Guide/Getting_Started.md' - - Accessing Built-in Help: 'Data_Transfer_Tool/Users_Guide/Accessing_Built-in_Help.md' - Preparing for Data Download and Upload: 'Data_Transfer_Tool/Users_Guide/Preparing_for_Data_Download_and_Upload.md' - - Data Download and Upload - Command Line: 'Data_Transfer_Tool/Users_Guide/Data_Download_and_Upload.md' - - Data Download - UI: 'Data_Transfer_Tool/Users_Guide/Data_Download_Upload_UI.md' - - Key Terms: 'Data_Transfer_Tool/Users_Guide/Appendix_A_-_Key_Terms.md' + - Data Transfer Tool Command Line Documentation: 'Data_Transfer_Tool/Users_Guide/Data_Download_and_Upload.md' - Release Notes - Command Line: 'Data_Transfer_Tool/Release_Notes/DTT_Release_Notes.md' + - Data Transfer Tool UI Documentation: 'Data_Transfer_Tool/Users_Guide/Data_Download_DTT_UI.md' - Release Notes - UI: 'Data_Transfer_Tool/Release_Notes/DTT_UI_Release_Notes.md' extra: diff --git a/Data_UG.yml b/Data_UG.yml index 449054797..58e0bfbe8 100644 --- a/Data_UG.yml +++ b/Data_UG.yml @@ -18,7 +18,9 @@ pages: - "Bioinformatics Pipeline: mRNA Analysis": 'Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline.md' - "Bioinformatics Pipeline: miRNA Analysis": 'Data/Bioinformatics_Pipelines/miRNA_Pipeline.md' - "Bioinformatics Pipeline: Copy Number Variation": 'Data/Bioinformatics_Pipelines/CNV_Pipeline.md' - - "Bioinformatics Pipeline: Methylation Liftover": 'Data/Bioinformatics_Pipelines/Methylation_LO_Pipeline.md' + - "Bioinformatics Pipeline: Methylation Analysis": 'Data/Bioinformatics_Pipelines/Methylation_Pipeline.md' + - "Bioinformatics Pipeline: Protein Expression": 'Data/Bioinformatics_Pipelines/RPPA_intro.md' + - Aligned Reads Summary Metrics: 'Data/Bioinformatics_Pipelines/Aligned_reads_summary_metrics.md' - Release Notes: 'Data/Release_Notes/Data_Release_Notes.md' extra: project_root_dir: '/' diff --git a/Notebooks/API_April_2021/Webinar_April_2021.ipynb b/Notebooks/API_April_2021/Webinar_April_2021.ipynb new file mode 100644 index 000000000..c9f46b508 --- /dev/null +++ b/Notebooks/API_April_2021/Webinar_April_2021.ipynb @@ -0,0 +1,953 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# GDC April 2021 Webinar: Using the GDC API\n", + "\n", + "### Monday, April 26, 2021
2:00 PM - 3:00 PM (EST)
Bill Wysocki, Lead for GDC User Services
University of Chicago\n", + "\n", + "## Table of Contents\n", + "\n", + "- [API User's Guide and Other Helpful Links](#links)\n", + "- [Notebook Overview](#overview)\n", + " - [About this notebook](#about_notebook)\n", + " - [Using the Python requests package and interpreting request reponse messages](#requests_package)\n", + "- [GDC API Overview](#api_overview)\n", + " - [GDC API Format](#api_format)\n", + " \n", + "- [Using the GDC API to Query Data in GDC](#query_data)\n", + " - [Search and Retrieval Endpoints Examples](#search_retrieve)\n", + " - [Data Analysis Endpoints Examples](#analysis)\n", + "- [Using the GDC API to Submit Data to GDC](#submit)\n", + "\n", + "## API User's Guide and Other Helpful Links\n", + "\n", + "[GDC API User's Guide](https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/)\n", + "\n", + "[GDC Support Website](https://gdc.cancer.gov/support)\n", + "\n", + "support@nci-gdc.datacommons.io - GDC Helpdesk E-mail\n", + "\n", + "[Requests Python Package User's Guide](https://2.python-requests.org/en/master/)\n", + "\n", + "[Python Documentation Website](https://www.python.org)\n", + "\n", + "[Jupyter Notebook Documentation](https://jupyter.org/documentation)\n", + "\n", + "# Notebook Overview\n", + "\n", + "\n", + "### About this notebook\n", + "\n", + "- This notebook serves to be a resource for GDC users to familiarize themselves with GDC API endpoints and allow users to edit and create custom queries \"in-place\" with provided template functions or submission tasks\n", + "- The provided functional templates can facilitate downstream data analyses and visualizations within the Jupyter Notebook interface and other Python packages\n", + "- Commands and functions in this notebook will rely on the following Python packages:\n", + " - `requests` - if not already installed on your system, can install with command `pip install requests` from command line or using a new code cell in this notebook\n", + " - `json` - part of Python standard library, should already be installed on system\n", + " - `urllib` - part of Python standard library, should already be installed on system\n", + "- To execute code in a code cell, press either 'Cmd + Enter' or 'Control + Enter' depending on operating system and keyboard layout\n", + "- If using notebook to aid in submission requests, will need to download token file from the [GDC Submission Portal](https://docs.gdc.cancer.gov/Data_Submission_Portal/Users_Guide/Data_Submission_Process/#authentication)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#import packages to use in this notebook\n", + "\n", + "import requests\n", + "import json\n", + "import urllib" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using the Python `requests` package and interpreting request reponse messages\n", + "\n", + "- The `requests` package allows users to communicate with the GDC API to make standard `POST`, `PUT`, `GET` and `DELETE` HTTP methods\n", + "- Need to specify request method as part of function (i.e. `request.get()` for `GET` method, `request.post()` for `POST` method etc.)\n", + "- When making a request with `requests` package, can save results of request as variable, i.e.:\n", + " - `response = requests.get(url)`\n", + "- Example `GET` request:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "response = requests.get('https://api.gdc.cancer.gov/cases?filters=%7B%22op%22%3A%20%22%3D%22%2C%20%22content%22%3A%20%7B%22field%22%3A%20%22cases.project.program.name%22%2C%20%22value%22%3A%20%22TCGA%22%7D%7D&fields=submitter_slide_ids&size=1&format=json&pretty=true')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- When returning the contents of the `response` variable, will only return HTTP status code of request, such as `` or ``; need to specify `response.text` method to get return message or data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "response" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "json.loads(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- Typically, successful responses begin with `'2'`, like `200` or `201` and unsuccessful requests begin with `'4'`, like `400` (bad request) or `403` ('forbidden' error, result of bad or insufficient credentials)\n", + "- A list and accompanying explanations of HTTP status codes can be [found here](https://en.wikipedia.org/wiki/List_of_HTTP_status_codes)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# GDC API Overview\n", + "\n", + "\n", + "- The GDC Application Programming Interface (API) is the external facing REpresentational State Transfer (REST) interface for the GDC\n", + "- The GDC API supports user interactions with the GDC Submission and Data Portals, as well as provides developers with a programmatic interface to query and download GDC data, metadata and annotations and submit data to the GDC.\n", + "- The [GDC Data Transfer Tool](https://gdc.cancer.gov/access-data/gdc-data-transfer-tool) client also relies on the GDC API for user authentication, reading manifests, and for download and upload features\n", + "\n", + "\n", + "### GDC API Format\n", + "\n", + "- The HTTP URL that corresponds to the GDC API is: https://api.gdc.cancer.gov/\n", + "- GDC API format for search and retrieval use is: API_URL + ENDPOINT + QUERY_PARAMETERS\n", + "- In order to utilize the GDC API, calls to specific API 'endpoints' for a given query need to be made, i.e. for retrieving data about cases in the GDC, will make calls to `cases` endpoint, https://api.gdc.cancer.gov/cases/\n", + "- For search and retrieval API calls, query parameters can be included, such as filters on endpoint fields, and the fields parameter to specify fields to return from query\n", + " - List of all indexed data fields to use specify as filters or fields for search and retrieval endpoints can be found at https://docs.gdc.cancer.gov/API/Users_Guide/Appendix_A_Available_Fields/\n", + " - Can also view available fields for both Search and Retrieval and Data Analysis endpoints by [using the `_mapping` endpoint for a given endpoint](https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/#_mapping-endpoint) or at the corresponding pages at the [GDC API Documentation site](https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/)\n", + " - Formatting parameters can be specified such as format (TSV or JSON format) and size (number of hits to return)\n", + "- For submitting data using the GDC API, the format for using the GDC API Submission endpoint uses the project ID: https://api.gdc.cancer.gov/program_name/project_code, i.e. https://api.gdc.cancer.gov/submission/TCGA/LUAD or https://api.gdc.cancer.gov/submission/CPTAC/3 \n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using the GDC API to Query Data in GDC\n", + "\n", + "### Overview\n", + "\n", + "- Submitters can make use of several GDC API endpoints to retrieve various data indexed in the GDC API, including biospecimen, clinical and annotation metadata\n", + "- The HTTP `GET` method will be used to retrieve data\n", + "- Additional parameters can be specified to tailor the returned data, such as number of returned entries and filters on data at endpoint\n", + "- Data can be retrieved in `JSON` or `TSV` format by specifying in the request the format desired (see below)\n", + "- Additional features and more information regarding using the GDC API can be found at this link: https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/\n", + "\n", + "\n", + "\n", + "### Endpoints\n", + "\n", + "There are two 'types' of endpoints that can be used to query data in the GDC:\n", + "\n", + "\n", + "[GDC Search and Retrieval Endpoints](https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/#endpoints) - includes endpoints that index project, file and case information, including clinical and biospecimen metadata, as well as file version and history\n", + "\n", + "[GDC Analysis Endpoints](https://docs.gdc.cancer.gov/API/Users_Guide/Data_Analysis/) - endpoints that are used by the GDC data analysis, visualization and exploration (DAVE) tools in the Exploration tab of the GDC Data Portal to access indexed data including gene, mutation, copy number variation and survival data. \n", + "\n", + "\n", + "### Steps\n", + "\n", + "1. Specify and percent-encode `filters`\n", + "2. Specify `fields` to be returned\n", + "3. Specify additional parameters (`size`, `format` of results etc.)\n", + "3. Concatenate parameters to build query url\n", + "4. Submit query and save response text to file\n", + "\n", + "Note: specifying parameters are optional; not specifying `filters` will return all instances at a given endpoint, and not specifying `fields` will return all fields at endpoint, while other parameters will be set to default value (i.e. `size` = 10, `format` = JSON)\n", + "\n", + "### Template queryBuilder() function\n", + "\n", + "- `GET` requests can be built as a URL with the endpoint and other parameters specified using a Python function\n", + "- In notebook, need to first run code for queryBuilder() function to instantiate the function\n", + "- Parameters must be passed into parantheses in the order that they are specified in the function\n", + "- To specify default parameters, users can simply input two quotation marks, i.e. `''`, for a given variable when using the queryBuilder() function\n", + "- Users can edit the template queryBuilder() function to build url request for querying data in GDC API to include other parameters, such as `facets`, `expand`, `from` (pagination) and `sort`: \n", + "https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/#request-parameters" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#format is specified as 'frmat' in function as format is an already declared object in python [the format() function]\n", + "\n", + "def queryBuilder(endpoint, filters, fields, size, frmat):\n", + " api_url = 'https://api.gdc.cancer.gov/'\n", + " \n", + " if frmat.lower() == 'json':\n", + " request_query = api_url + endpoint + '?filters=' + filters + '&fields=' + fields + '&size=' + size + '&format=' + frmat + '&pretty=true'\n", + " else:\n", + " request_query = api_url + endpoint + '?filters=' + filters + '&fields=' + fields + '&size=' + size + '&format=' + frmat\n", + " return request_query" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Templates for query `filters`\n", + "\n", + "- `Filters` are used to specify which hits to return from an endpoint, such as cases of a certain project or files from a certain workflow\n", + "- Filters need to be created in JSON format that then will need to be [percent-encoded]() to be sent in the URL request (can use the `urllib` Python package for percent-endcoded formatting)\n", + "- JSON filters use [operators](https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/#filters-specifying-the-query) to specify relationships between a field and their possible values\n", + "- For a given endpoint, need to use indexed fields at that endpoint\n", + " - For Search and Retrieval endpoints, can reference [Appendix A at GDC API Documentation site](https://docs.gdc.cancer.gov/API/Users_Guide/Appendix_A_Available_Fields/)\n", + " - Can also view available fields for both Search and Retrieval and Data Analysis endpoints by [using the `_mapping` endpoint for a given endpoint](https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/#_mapping-endpoint)\n", + "- Specifying no filters will return all instances for a given endpoint (default)\n", + "- Below are several examples users can edit to build filters for a `GET` request" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#one filter applied to endpoint\n", + "\n", + "#one filter \n", + "one_filter = {\n", + " \"op\":\"=\",\n", + " \"content\":{\n", + " \"field\": \"cases.project.project_id\", \n", + " \"value\": \"TCGA-BRCA\"\n", + " }\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#combination of two filters applied to endpoint, i.e. (x AND/OR y) must be met\n", + "\n", + "combination_two = {\n", + " \"op\" : \"and\",\n", + " \"content\":[{\n", + " \"op\":\"=\",\n", + " \"content\":{\n", + " \"field\": \"cases.project.project_id\", \n", + " \"value\": \"TCGA-BRCA\"\n", + " }\n", + " }, \n", + " {\n", + " \"op\":\"=\", \n", + " \"content\":{\n", + " \"field\":\"cases.disease_type\",\n", + " \"value\": \"ductal and lobular neoplasms\"\n", + " }\n", + " }\n", + " ]\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#combination of three filters applied to endpoint, i.e. (x AND/OR y AND/OR z) must be met\n", + "\n", + "combination_three = {\n", + " \"op\" : \"and\",\n", + " \"content\":[{\n", + " \"op\":\"=\",\n", + " \"content\":{\n", + " \"field\": \"cases.project.project_id\", \n", + " \"value\": \"TCGA-BRCA\"\n", + " }\n", + " }, \n", + " {\n", + " \"op\":\"=\", \n", + " \"content\":{\n", + " \"field\":\"cases.disease_type\",\n", + " \"value\": \"ductal and lobular neoplasms\"\n", + " }\n", + " },\n", + " {\n", + " \"op\":\">\", \n", + " \"content\":{\n", + " \"field\":\"diagnoses.age_at_diagnosis\",\n", + " \"value\": \"15000\"\n", + " }\n", + " }\n", + " \n", + " ]\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#complex combination of three filters applied to endpoint, i.e. (x AND/OR [y AND/OR z]) must be met\n", + "\n", + "combination_three_2 = {\n", + " \"op\": \"and\",\n", + " \"content\": [{\n", + " \"op\": \"=\",\n", + " \"content\": {\n", + " \"field\": \"cases.project.project_id\",\n", + " \"value\": \"TCGA-BRCA\"\n", + " }\n", + " },\n", + " {\n", + " \"op\": \"or\",\n", + " \"content\": [{\n", + " \"op\": \"=\",\n", + " \"content\": {\n", + " \"field\": \"cases.disease_type\",\n", + " \"value\": \"cystic, mucinous and serious neoplasms\"\n", + " }\n", + " },\n", + " {\n", + " \"op\": \"=\",\n", + " \"content\": {\n", + " \"field\": \"cases.disease_type\",\n", + " \"value\": \"ductal and lobular neoplasms\"\n", + " }\n", + " }\n", + " ]\n", + " }\n", + " ]\n", + "}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Template commands for formatting filter parameters" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#percent encoding of filters\n", + "json_string=str(json.dumps(one_filter)) #replace one_filter with input filter variable here\n", + "example_filter = urllib.parse.quote(json_string.encode('utf-8'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Template for formatting `fields` to be returned by query\n", + "\n", + "- The `fields` parameter is passed to the API request URL as a comma-delimited list of fields to be returned\n", + "- For a given endpoint, can only specify indexed fields at that endpoint\n", + " - For Search and Retrieval endpoints, can reference [Appendix A at GDC API Documentation site](https://docs.gdc.cancer.gov/API/Users_Guide/Appendix_A_Available_Fields/)\n", + " - Can also view available fields for both Search and Retrieval and Data Analysis endpoints by [using the `_mapping` endpoint for a given endpoint](https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/#_mapping-endpoint)\n", + "- Specifying no fields will return all available fields for entities that match `filters` for a given endpoint (default)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#specify fields to be returned\n", + "example_fields = \",\".join([\n", + " \"submitter_id\",\n", + " \"disease_type\",\n", + " \"samples.submitter_id\",\n", + " \"samples.sample_type\", \n", + " \"samples.tissue_type\",\n", + " \"diagnoses.age_at_diagnosis\"\n", + "])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Template API `GET` Request " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#build API query: queryBuilder(endpoint, filters, fields, size, frmat)\n", + "\n", + "#to specify no filters and/or no fields to return, replace variable with ''\n", + "\n", + "template_request = queryBuilder('cases', example_filter, example_fields, '11315', \"json\")\n", + "\n", + "template_request" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "##### Note: You can also copy and paste formatted request URL into browser url bar to return results in browser" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#send request\n", + "result = requests.get(template_request)\n", + "\n", + "#write request results to file, edit file name and type \n", + "with open(\"ffpe.json\", \"w+\") as output: \n", + " output.write(result.text)\n", + "output.close()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Search and Retrieval Endpoints Examples\n", + "\n", + "### Example 1: Retrieve case barcode, sample type and primary diagnosis data for DNA-seq files in TCGA-BRCA project\n", + "\n", + "- For this example, we would like to retrieve whether BAM files in the TCGA-BRCA project are for normal or tumor samples, as well as what disease cases were diagnosed as\n", + "- Use 'files' endpoint, as this endpoint contains metadata related to files in the GDC (such as experimental strategy and data category)\n", + "- Need to filter down to files that are of the data category \"sequencing reads\" and experimental strategy type \"WXS\" (whole exome) to filter out other categories (like copy number variation, gene expression) and other experimental stragies (like RNA-Seq). " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#step 1: specify and encode filters\n", + "\n", + "filters = {\n", + " \"op\" : \"and\",\n", + " \"content\":[{\n", + " \"op\":\"=\",\n", + " \"content\":{\n", + " \"field\": \"cases.project.project_id\", \n", + " \"value\": \"TCGA-BRCA\"\n", + " }\n", + " }, \n", + " {\n", + " \"op\":\"=\", \n", + " \"content\":{\n", + " \"field\":\"files.data_category\",\n", + " \"value\": \"sequencing reads\"\n", + " }\n", + " },\n", + " {\n", + " \"op\":\"=\", \n", + " \"content\":{\n", + " \"field\":\"files.experimental_strategy\",\n", + " \"value\": \"WXS\"\n", + " }\n", + " },\n", + " {\n", + " \"op\":\"=\", \n", + " \"content\":{\n", + " \"field\":\"files.data_format\",\n", + " \"value\": \"BAM\"\n", + " }\n", + " }\n", + " \n", + " ]\n", + "}\n", + "\n", + "json_string=str(json.dumps(filters))\n", + "filters_format = urllib.parse.quote(json_string.encode('utf-8'))\n", + "\n", + "#step 2: specify fields to be returned\n", + "fields = \",\".join([\n", + " \"cases.submitter_id\",\n", + " \"file_name\",\n", + " \"cases.samples.sample_type\",\n", + " \"cases.diagnoses.primary_diagnosis\"\n", + "])\n", + "\n", + "#step 3+4: specify size=1 and format=tsv, build query url with 'files' endpoint\n", + "brca_request = queryBuilder('files', filters_format, fields, '1', \"tsv\")\n", + "\n", + "#step 5: send request\n", + "brca_result = requests.get(brca_request)\n", + "\n", + "print(brca_result.text)\n", + "brca_request" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Example 2: Retrieve FFPE data for samples and portions for TCGA projects\n", + "\n", + "- In this example, we will retrieve whether case samples and portions taken from cases in TCGA projects were Formalin-Fixed Paraffin-Embedded (FFPE) specimens or not\n", + "- Use the 'cases' endpoint, as this endpoint contains biospecimen and clinical information related to cases and samples in the GDC" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#step 1: specify and encode filters\n", + "filters = {\n", + " \"op\":\"=\",\n", + " \"content\":{\n", + " \"field\": \"cases.project.program.name\", \n", + " \"value\": \"TCGA\"\n", + " }\n", + "}\n", + "\n", + "json_string=str(json.dumps(filters))\n", + "filters_format = urllib.parse.quote(json_string.encode('utf-8'))\n", + "\n", + "#step 2: specify fields to be returned\n", + "fields = \",\".join([\n", + " \"submitter_id\",\n", + " \"samples.submitter_id\",\n", + " \"samples.is_ffpe\",\n", + " \"samples.portions.submitter_id\",\n", + " \"samples.portions.is_ffpe\"\n", + "])\n", + "\n", + "#step 3+4: specify size=1 and format=json, build query url with 'cases' endpoint\n", + "ffpe_request = queryBuilder('cases', filters_format, fields, '1', \"json\")\n", + "\n", + "#step 5: send request\n", + "ffpe_result = requests.get(ffpe_request)\n", + "\n", + "print(ffpe_result.text)\n", + "ffpe_request" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Example 3: Age at Diagnosis, Days to Death after Diagnosis, Vital Status and other clinical data for cases in TCGA-KIRC project\n", + "\n", + "- In this example, we will retrieve age, survival and other clinical data for cases in the TCGA-KIRC project\n", + "- Use the 'cases' endpoint, as this endpoint contains biospecimen and clinical information related to cases and samples in the GDC\n", + "- Results will only show data for `demographic.days_to_death` if case is deceased" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#step 1: specify and encode filters\n", + "filters = {\n", + " \"op\":\"=\",\n", + " \"content\":{\n", + " \"field\": \"cases.project.project_id\", \n", + " \"value\": \"TCGA-KIRC\"\n", + " }\n", + "}\n", + "\n", + "json_string=str(json.dumps(filters))\n", + "filters_format = urllib.parse.quote(json_string.encode('utf-8'))\n", + "\n", + "#step 2: specify fields to be returned\n", + "fields = \",\".join([\n", + " \"submitter_id\",\n", + " \"diagnoses.age_at_diagnosis\",\n", + " \"demographic.days_to_death\",\n", + " \"demographic.vital_status\", \n", + " \"demographic.ethnicity\",\n", + " \"demographic.race\",\n", + " \"demographic.gender\"\n", + "])\n", + "\n", + "#step 3+4: specify size=2 and format=tsv, build query url with 'cases' endpoint\n", + "age_request = queryBuilder('cases', filters_format, fields, '2', \"tsv\")\n", + "\n", + "#step 5: send request\n", + "age_result = requests.get(age_request)\n", + "\n", + "print(age_result.text)\n", + "age_request" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Analysis Endpoints Examples\n", + "\n", + "### Example 4: Gene information\n", + "\n", + "- In this example, we will retrieve gene IDs and positions of genes present on chromosome 8 of the human genome\n", + "- Use the 'genes' endpoint, as this endpoint contains gene information indexed in the GDC API" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#step 1: specify and encode filters\n", + "filters = {\n", + " \"op\":\"=\",\n", + " \"content\":{\n", + " \"field\": \"gene_chromosome\", \n", + " \"value\": \"8\"\n", + " }\n", + "}\n", + "\n", + "json_string=str(json.dumps(filters))\n", + "filters_format = urllib.parse.quote(json_string.encode('utf-8'))\n", + "\n", + "#step 2: specify fields to be returned\n", + "fields = \",\".join([\n", + " \"id\",\n", + " \"symbol\",\n", + " \"gene_start\",\n", + " \"gene_end\"\n", + "])\n", + "\n", + "#step 3+4: specify size=10 and format=tsv, build query url with 'genes' endpoint\n", + "genes_request = queryBuilder('genes', filters_format, fields, '10', \"tsv\")\n", + "\n", + "#step 5: send request\n", + "genes_result = requests.get(genes_request)\n", + "\n", + "print(genes_result.text)\n", + "genes_request" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Can use gene_id to also query individual information about the gene in question from genes endpoint as well\n", + "#by appending the gene_id at the end of the 'genes' endpoint and specifying parameters\n", + "\n", + "individual_gene_request = requests.get('https://api.gdc.cancer.gov/genes/ENSG00000160948?pretty=true')\n", + "\n", + "print(individual_gene_request.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Example 5: Simple Somatic Mutation Information \n", + "\n", + "- In this example, we will retrieve information on a specific mutation using its COSMIC ID\n", + "- Use the 'ssms' endpoint, as this endpoint contains mutation information indexed in the GDC API" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#step 1: specify and encode filters\n", + "filters = {\n", + " \"op\":\"in\",\n", + " \"content\":{\n", + " \"field\":\"cosmic_id\",\n", + " \"value\":[\n", + " \"COSM4860838\"\n", + " ]\n", + " }\n", + "}\n", + "\n", + "json_string=str(json.dumps(filters))\n", + "filters_format = urllib.parse.quote(json_string.encode('utf-8'))\n", + "\n", + "#step 2: specify all fields to be returned (default = \"\")\n", + "fields = \",\".join([\n", + " \"\"\n", + "])\n", + "\n", + "#step 3+4: specify size=1 and format=json, build query url with 'ssms' endpoint\n", + "mutation_request = queryBuilder('ssms', filters_format, fields, '1', \"json\")\n", + "\n", + "#step 5: send request\n", + "mutation_result = requests.get(mutation_request)\n", + "\n", + "print(mutation_result.text)\n", + "mutation_request" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Example 6: Compare survival data for TCGA-SKCM cases with and without the `chr7:g.140753336A>T` mutation \n", + "\n", + "- For this example we wish to use the survival analysis endpoint to compare two survival plots for TCGA-SKCM cases: one plot with cases having the `chr7:g.140753336A>T`, and the other plot for cases with out the mutation. \n", + "- Can retrieve the `ssm_id` for a mutation from the [GDC Data Portal > Exploration](https://portal.gdc.cancer.gov/exploration) tab. \n", + "- The API query will also print the results of a chi-squared analysis between the two subsets of cases\n", + " - Note that results of chi-square test are dependent on number of cases returned for each plot (`size` parameter); to choose all cases, use total number of cases in project for `size` parameter" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#step 1: specify and encode filters\n", + "filters = [ \n", + " { \n", + " \"op\":\"and\",\n", + " \"content\":[ \n", + " { \n", + " \"op\":\"=\",\n", + " \"content\":{ \n", + " \"field\":\"cases.project.project_id\",\n", + " \"value\":\"TCGA-SKCM\"\n", + " }\n", + " },\n", + " { \n", + " \"op\":\"=\",\n", + " \"content\":{ \n", + " \"field\":\"gene.ssm.ssm_id\",\n", + " \"value\":\"84aef48f-31e6-52e4-8e05-7d5b9ab15087\"\n", + " }\n", + " }\n", + " ]\n", + " },\n", + " { \n", + " \"op\":\"and\",\n", + " \"content\":[ \n", + " { \n", + " \"op\":\"=\",\n", + " \"content\":{ \n", + " \"field\":\"cases.project.project_id\",\n", + " \"value\":\"TCGA-SKCM\"\n", + " }\n", + " },\n", + " { \n", + " \"op\":\"excludeifany\",\n", + " \"content\":{ \n", + " \"field\":\"gene.ssm.ssm_id\",\n", + " \"value\":\"84aef48f-31e6-52e4-8e05-7d5b9ab15087\"\n", + " }\n", + " }\n", + " ]\n", + " }\n", + "]\n", + "\n", + "json_string=str(json.dumps(filters))\n", + "filters_format = urllib.parse.quote(json_string.encode('utf-8'))\n", + "\n", + "#step 2: specify that all fields to be returned (default = \"\") \n", + "fields = \",\".join([\n", + " \"\"\n", + "])\n", + "\n", + "#step 3+4: specify size=10 and format=JSON, build query url with 'analysis/survival' endpoint,\n", + "survival_request = queryBuilder('analysis/survival', filters_format, \"\", '10', \"JSON\")\n", + "\n", + "#step 5: send request\n", + "survival_result = requests.get(survival_request)\n", + "\n", + "#print(survival_result.text)\n", + "survival_request" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#can parse out the chi-squared test from results\n", + "#by loading results as a JSON object and selecting\n", + "#overallStats from results\n", + "\n", + "json.loads(survival_result.text)['overallStats']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Using the GDC API to Submit Data to GDC\n", + "\n", + "### Overview\n", + "\n", + "- For projects that have been approved to be included in the GDC, submitters can make use of the `submission` GDC API endpoint to submit node entities to submission projects\n", + "- Submission will require a token downloaded from the [GDC Submission Portal](https://docs.gdc.cancer.gov/Data_Submission_Portal/Users_Guide/Data_Submission_Process/#authentication)\n", + "- Data can be submitted in `JSON` or `TSV` format; depending on the data format, users will need to edit the `\"Content-Type\"` in the request command (see below)\n", + "- Additionally, `JSON` and `TSV` templates for nodes to be submitted can be downloaded from the GDC Data Dictionary Viewer webpage: https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?_top=1\n", + "- Submittable files (such as FASTQ or BAM files) should be uploaded with the [GDC Data Transfer Tool](https://gdc.cancer.gov/access-data/gdc-data-transfer-tool)\n", + "- Additional features and more information regarding submission using the GDC API can be found here: https://docs.gdc.cancer.gov/API/Users_Guide/Submission/ \n", + "- [Strategies for Submitting in Bulk](https://docs.gdc.cancer.gov/Data_Submission_Portal/Users_Guide/Data_Submission_Walkthrough/#strategies-for-submitting-in-bulk)\n", + "\n", + "### Endpoint\n", + "\n", + "- The format for using the GDC API Submission endpoint uses the project information, i.e. `https://api.gdc.cancer.gov/submission//`\n", + "- For example: https://api.gdc.cancer.gov/submission/TCGA/LUAD or https://api.gdc.cancer.gov/submission/CPTAC/3 \n", + "\n", + "### Steps\n", + "\n", + "1. Read in token file\n", + "2. Read in submission file\n", + "3. Edit endpoint with project ID information and submit data using `POST` (JSON file submission) or `PUT` (TSV file submission) request\n", + "\n", + "### Example 7: Submitting a JSON Data File" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#1. Read in token file\n", + "\n", + "token = open(\"../gdc-user-token.txt\").read().strip()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#2. Read in submission file\n", + "\n", + "example_file_json = json.load(open(\"example_file.json\"))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#3. Edit endpoint and submit data using POST request\n", + "\n", + "ENDPT = \"https://api.gdc.cancer.gov/submission/GDC/INTERNAL\"\n", + "\n", + "#submission request if data is in JSON format\n", + "response = requests.post(url = ENDPT, json = example_file_json, headers={'X-Auth-Token': token, \"Content-Type\": \"application/json\"})\n", + "print(response.text)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Example 8: Submitting a TSV Data File" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#1. Read in token file\n", + "\n", + "token = open(\"../gdc-user-token.txt\").read().strip()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#2. Read in submission file\n", + "\n", + "example_file_tsv = open(\"example_file.txt\", \"rb\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#3. Edit endpoint and submit data using PUT request\n", + "\n", + "ENDPT = \"https://api.gdc.cancer.gov/submission/GDC/INTERNAL/_dry_run\"\n", + "\n", + "#submission request if data is in TSV format\n", + "res = requests.put(url = ENDPT, data = example_file_tsv, headers={'X-Auth-Token': token, \"Content-Type\": \"text/tsv\"})\n", + "\n", + "res.text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Notebooks/API_April_2021/example_file.json b/Notebooks/API_April_2021/example_file.json new file mode 100644 index 000000000..bad702575 --- /dev/null +++ b/Notebooks/API_April_2021/example_file.json @@ -0,0 +1,5 @@ +{ +"type":"case", +"projects":{"code":"INTERNAL"}, +"submitter_id":"GDC-INTERNAL-000099" +} diff --git a/Notebooks/API_April_2021/example_file.txt b/Notebooks/API_April_2021/example_file.txt new file mode 100644 index 000000000..4bcb3d614 --- /dev/null +++ b/Notebooks/API_April_2021/example_file.txt @@ -0,0 +1,2 @@ +type submitter_id projects.code +case GDC-INTERNAL-000098 INTERNAL diff --git a/Notebooks/Submission_June_2021/SAR.json b/Notebooks/Submission_June_2021/SAR.json new file mode 100644 index 000000000..24c7a1e79 --- /dev/null +++ b/Notebooks/Submission_June_2021/SAR.json @@ -0,0 +1,12 @@ +{ +"type": "submitted_aligned_reads", +"submitter_id": "BAM_file_internal_", +"read_groups" : [{"submitter_id":"RG_INTERNAL_2"}], +"file_name":"WXS-file.bam", +"md5sum":"c2d1f25918af7609975370320632f24a", +"file_size": 20, +"data_category":"Sequencing Reads", +"data_type": "Aligned Reads", +"data_format":"BAM", +"experimental_strategy":"WXS" +} diff --git a/Notebooks/Submission_June_2021/WXS-file.bam b/Notebooks/Submission_June_2021/WXS-file.bam new file mode 100644 index 000000000..b3108f263 --- /dev/null +++ b/Notebooks/Submission_June_2021/WXS-file.bam @@ -0,0 +1 @@ +not a real BAM file diff --git a/Notebooks/Submission_June_2021/Webinar_June_2021.ipynb b/Notebooks/Submission_June_2021/Webinar_June_2021.ipynb new file mode 100644 index 000000000..1fa0b5637 --- /dev/null +++ b/Notebooks/Submission_June_2021/Webinar_June_2021.ipynb @@ -0,0 +1,244 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# GDC June 2021 Webinar: GDC Data Submission Overview\n", + "\n", + "### Monday, June 28, 2021
2:00 PM - 3:00 PM (EST)
Bill Wysocki, Lead for GDC User Services
University of Chicago\n", + "\n", + "\n", + "# Notebook Overview\n", + "\n", + "\n", + "### About this notebook\n", + "\n", + "- This notebook functions as a step-by-step set of instructions to submit a BAM file to the GDC using Python. Submitters who have a completely empty project or who have just started submitting with python might find this useful.\n", + "\n", + "- Commands and functions in this notebook will rely on the following Python packages:\n", + " - `requests` - if not already installed on your system, can install with command `pip install requests` from command line or using a new code cell in this notebook\n", + " - `json` - part of Python standard library, should already be installed on system\n", + "- To execute code in a code cell, press either 'Cmd + Enter' or 'Control + Enter' depending on operating system and keyboard layout\n", + "- A token file will need to be downloaded from the [GDC Submission Portal](https://docs.gdc.cancer.gov/Data_Submission_Portal/Users_Guide/Data_Submission_Process/#authentication)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Overview\n", + "\n", + "- For projects that have been approved to be included in the GDC, submitters can make use of the `submission` GDC API endpoint to submit node entities to submission projects\n", + "- Submission will require a token downloaded from the [GDC Submission Portal](https://docs.gdc.cancer.gov/Data_Submission_Portal/Users_Guide/Data_Submission_Process/#authentication)\n", + "- Data can be submitted in `JSON` or `TSV` format; depending on the data format, users will need to edit the `\"Content-Type\"` in the request command (see below)\n", + "- Additionally, `JSON` and `TSV` templates for nodes to be submitted can be downloaded from the GDC Data Dictionary Viewer webpage: https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?_top=1\n", + "- Submittable files (such as FASTQ or BAM files) should be uploaded with the [GDC Data Transfer Tool](https://gdc.cancer.gov/access-data/gdc-data-transfer-tool)\n", + "- Additional features and more information regarding submission using the GDC API can be found here: https://docs.gdc.cancer.gov/API/Users_Guide/Submission/ \n", + "- [Strategies for Submitting in Bulk](https://docs.gdc.cancer.gov/Data_Submission_Portal/Users_Guide/Data_Submission_Walkthrough/#strategies-for-submitting-in-bulk)\n", + "\n", + "### Endpoint\n", + "\n", + "- The format for using the GDC API Submission endpoint uses the project information, i.e. `https://api.gdc.cancer.gov/submission//`\n", + "- For example: https://api.gdc.cancer.gov/submission/TCGA/LUAD or https://api.gdc.cancer.gov/submission/CPTAC/3 \n", + "\n", + "### Steps\n", + "\n", + "1. Read in token file\n", + "2. Read in submission file\n", + "3. Edit endpoint with project ID information and submit data using `POST` (JSON file submission) or `PUT` (TSV file submission) request\n", + "\n", + "### 1. Submitting a Case (JSON)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#1. Import Python packages and read in token file\n", + "\n", + "import json\n", + "import requests\n", + "\n", + "token = open(\"../gdc-user-token.txt\").read().strip()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#2. Read in submission file\n", + "\n", + "case_json = json.load(open(\"case.json\"))\n", + "\n", + "print(json.dumps(case_json, indent=4))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#3. Edit endpoint and submit data using PUT request\n", + "\n", + "ENDPT = \"https://api.gdc.cancer.gov/submission/GDC/INTERNAL/_dry_run\"\n", + "\n", + "#submission request if data is in JSON format\n", + "response = requests.put(url = ENDPT, json = case_json, headers={'X-Auth-Token': token, \"Content-Type\": \"application/json\"})\n", + "print(json.dumps(json.loads(response.text), indent = 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2: Submitting a Sample" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#1. Read in submission file\n", + "\n", + "sample_tsv = open(\"sample.tsv\", \"rb\")\n", + "sample_tsv_display = open(\"sample.tsv\", \"r\")\n", + "\n", + "for x in sample_tsv_display.readlines():\n", + " print(x.strip().split(\"\\t\"))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#2. Edit endpoint and submit data using PUT request\n", + "\n", + "ENDPT = \"https://api.gdc.cancer.gov/submission/GDC/INTERNAL/\"\n", + "\n", + "#submission request if data is in TSV format\n", + "response = requests.put(url = ENDPT, data = sample_tsv, headers={'X-Auth-Token': token, \"Content-Type\": \"text/tsv\"})\n", + "\n", + "print(json.dumps(json.loads(response.text), indent = 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3: Submitting the Aliquot and Read_Group" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#1. Read in submission file\n", + "\n", + "aliquot_rg_json = json.load(open(\"aliquot_readgroup.json\"))\n", + "\n", + "print(json.dumps(aliquot_rg_json, indent=4))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#2. Submit data using PUT request\n", + "\n", + "ENDPT = \"https://api.gdc.cancer.gov/submission/GDC/INTERNAL\"\n", + "\n", + "#submission request if data is in JSON format\n", + "response = requests.put(url = ENDPT, json = aliquot_rg_json, headers={'X-Auth-Token': token, \"Content-Type\": \"application/json\"})\n", + "print(json.dumps(json.loads(response.text), indent = 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 4: Register the Submitted Aligned Reads File" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#1. Read in submission file\n", + "\n", + "sar_json = json.load(open(\"SAR.json\"))\n", + "\n", + "print(json.dumps(sar_json, indent=4))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#2. Submit data using PUT request\n", + "\n", + "ENDPT = \"https://api.gdc.cancer.gov/submission/GDC/INTERNAL\"\n", + "\n", + "#submission request if data is in JSON format\n", + "response = requests.put(url = ENDPT, json = sar_json, headers={'X-Auth-Token': token, \"Content-Type\": \"application/json\"})\n", + "print(json.dumps(json.loads(response.text), indent = 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 5: Upload the Submitted Aligned Reads Data File Using Data Transfer Tool\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "## ./gdc-client upload -t token_file.txt" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Notebooks/Submission_June_2021/aliquot_readgroup.json b/Notebooks/Submission_June_2021/aliquot_readgroup.json new file mode 100644 index 000000000..16948c3cd --- /dev/null +++ b/Notebooks/Submission_June_2021/aliquot_readgroup.json @@ -0,0 +1,22 @@ +[ +{ +"type":"aliquot", +"submitter_id":"ALIQUOT_INTERNAL_2", +"samples":{"submitter_id":"SAMPLE_INTERNAL_2"} +}, +{ +"type":"read_group", +"submitter_id":"RG_INTERNAL_2", +"aliquots":{"submitter_id": "ALIQUOT_INTERNAL_2"}, +"experiment_name": "INTERNAL", +"library_name" : "INTERNAL", +"is_paired_end": true, +"library_selection": "PCR", +"library_strategy":"WXS", +"platform": "Illumina", +"read_group_name": "Read_group_1", +"read_length": 100, +"sequencing_center": "UChicago", +"target_capture_kit": "SeqCap EZ Human Exome v2.0" +} +] diff --git a/Notebooks/Submission_June_2021/case.json b/Notebooks/Submission_June_2021/case.json new file mode 100644 index 000000000..4e1eb9344 --- /dev/null +++ b/Notebooks/Submission_June_2021/case.json @@ -0,0 +1,5 @@ +{ +"type":"case", +"projects":{"code":"INTERNAL1"}, +"submitter_id":"GDC-INTERNAL-000097" +} diff --git a/Notebooks/Submission_June_2021/sample.tsv b/Notebooks/Submission_June_2021/sample.tsv new file mode 100644 index 000000000..97d0da777 --- /dev/null +++ b/Notebooks/Submission_June_2021/sample.tsv @@ -0,0 +1,2 @@ +type submitter_id cases.submitter_id sample_type tissue_type +sample SAMPLE_INTERNAL_2 GDC-INTERNAL-000097 Primary Tumor Genomic Tumor diff --git a/README.md b/README.md index 132ed9c3f..e82cab829 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,97 @@ ![](https://gdc.cancer.gov/sites/all/themes/gdc_bootstrap/logo.png) -# THIS PROJECT HAS MOVED +# GDC Open Source code -Please join us at https://github.com/NCI-GDC/gdc-docs +======= +GDC is Open Source, Github Repositories containing source code of GDC Applications can be found on [GDC GitHub Organization page](https://github.com/NCI-GDC/). +- GDC Data Portal: https://github.com/NCI-GDC/portal-ui +- GDC Legacy Archive: https://github.com/NCI-GDC/portal-ui-legacy +- GDC Data Transfer Tool: https://github.com/NCI-GDC/gdc-client +- GDC Data Dictionary: https://github.com/NCI-GDC/gdcdictionary +- GDC Data Model: https://github.com/NCI-GDC/gdcdatamodel +- GDC Psqlgraph: https://github.com/NCI-GDC/psqlgraph + +# Support + +Please direct technical questions to [GDC Support](https://gdc.cancer.gov/support). + +# GDC Documentation Site + +### Technology + + - Python 2.6, 2.7, 3.3, 3.4 and 3.5. + - [mkdocs](http://www.mkdocs.org/) + - [BSCodeTabs for mkdocs](https://github.com/mikecules/MarkdownBSCodeTabs#for-use-in-mkdocs) + +### Install & Run + +(Optional) Set up virtualenv: + +- [Install virtualenv](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/) +- `python -m virtualenv venv` +- `source venv/bin/activate` +- Run the installation commands below +- To leave the virtual environment: `deactivate` + +Install GDC-docs: + + - `pip install -r requirements.txt` + - `mkdocs serve` (optionally set port `--dev-addr=0.0.0.0:`) + +### Build + + - `mkdocs build --clean` + +### Repository Conventions + +- All Shared content in the "Commons" directory +- One Directory per GDC product (API, Data_Portal, Data_Submission_Portal, Data_Transfer_Tool) +- Each GDC product have a Users_Guide and Release_Notes directory + +### Linking + +To another documentation page +``` +[Authentication and Authorization](../../Commons/Authentication.md) +``` + +Inside another documentation page + +``` +[Authentication and Authorization](../../Commons/Authentication.md#internal-section) +``` + +### Adding icons and PDFs +The convention for this, when updating mkdocs.yml is the following: +- : 'index.md' +example: +- fa-file-pdf-o Download PDF /API/PDF/API_UG.pdf: 'index.md' + +### Documentation Conventions + +A detailed list of all conventions is available on [GDC Website](https://gdc.cancer.gov/conventions-page) + + +### Build PDF + +Install mkdocs2pandoc, following instructions available here: +``` +https://github.com/jgrassler/mkdocs-pandoc +``` + +Prepare a yml file dedicated to your Userguide, using Data_Portal_UG.yml as an example. + +Run the following commands to: +* Convert the User Guide to Pandoc: +* Tweak the pandoc file +* Build a PDF + +``` +mkdocs2pandoc -f Data_Portal_UG.yml -o docs/Data_Portal/PDF/Data_portal_UG.pd +sed -i -e 's/# / /g' docs/Data_Portal/PDF/Data_portal_UG.pd +sed -i -e 's/### /## /g' docs/Data_Portal/PDF/Data_portal_UG.pd +sed -i -e 's/\/site\//\/docs\//g' docs/Data_Portal/PDF/Data_portal_UG.pd +pandoc --toc -V documentclass=report -V geometry:"top=2cm, bottom=1.5cm, left=1cm, right=1cm" -f markdown+grid_tables+table_captions -o docs/Data_Portal/PDF/Data_portal_UG.pdf docs/Data_Portal/PDF/Data_portal_UG.pd +``` diff --git a/docs/API/Release_Notes/API_Release_Notes.md b/docs/API/Release_Notes/API_Release_Notes.md index 232ccf13c..ec0d2d490 100644 --- a/docs/API/Release_Notes/API_Release_Notes.md +++ b/docs/API/Release_Notes/API_Release_Notes.md @@ -3,6 +3,21 @@ | Version | Date | |---|---| +| [v4.0.0](API_Release_Notes.md#v400) | July 31, 2023 | +| [v3.28.0](API_Release_Notes.md#v3280) | May 11, 2023 | +| [v3.5.0](API_Release_Notes.md#v350) | July 8, 2022 | +| [v3.3.0](API_Release_Notes.md#v330) | May 17, 2021 | +| [v3.0.0](API_Release_Notes.md#v300) | August 14, 2020 | +| [v2.1.2](API_Release_Notes.md#v212) | May 7, 2020 | +| [v2.1.0](API_Release_Notes.md#v210) | March 10, 2020 | +| [v2.0.0](API_Release_Notes.md#v200) | January 30, 2020 | +| [v1.23.0](API_Release_Notes.md#v1230) | November 6, 2019 | +| [v1.22.0](API_Release_Notes.md#v1220) | July 31, 2019 | +| [v1.21.0](API_Release_Notes.md#v1210) | June 5, 2019 | +| [v1.20.0](API_Release_Notes.md#v1200) | April 17, 2019 | +| [v1.19.0](API_Release_Notes.md#v1190) | February 20, 2019 | +| [v1.18.0](API_Release_Notes.md#v1180) | December 18, 2018 | +| [v1.17.0](API_Release_Notes.md#v1170) | November 7, 2018 | | [v1.16.0](API_Release_Notes.md#v1160) | September 27, 2018 | | [v1.15.0](API_Release_Notes.md#v1150) | August 23, 2018 | | [v1.14.1](API_Release_Notes.md#v1141) | May 21, 2018 | @@ -21,6 +36,349 @@ | [v1.1.0](API_Release_Notes.md#v110) | May 25, 2016 | | [v1.0.1](API_Release_Notes.md#v101) | May 16, 2016 | +## v4.0.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: July 31, 2023 + +### New Features and Changes + +* The GDC API no longer supports download of Legacy Archive files. + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + +## v3.28.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: May 11, 2023 + +### New Features and Changes + +* The `/legacy/files` endpoint has been deprecated and is no longer available. +* Features to support Data Portal bugfixes were added. + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + +## v3.5.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: July 8, 2022 + +### New Features and Changes + +* Features to support Data Portal performance were added. + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + +## v3.3.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: May 17, 2021 + +### New Features and Changes + +* Features to better support batch tracking for submitted data were added. + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + +## v3.0.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: August 14, 2020 + +### New Features and Changes + +* Enhancements were made to increase performance. + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + +## v2.1.2 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: May 7, 2020 + +### New Features and Changes + +* An update to improve usability in the homepage quicksearch + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + +## v2.1.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: March 10, 2020 + +### New Features and Changes + +* New data dictionary changes. + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + +## v2.0.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: January 30, 2020 + +### New Features and Changes + +* API code now uses Python 3. + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + +## v1.23.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: November 6, 2019 + +### New Features and Changes + +* QC Tests added for Submission +* BAM slicing is now supported for unmapped reads +* API now includes data from molecular_test and follow_up nodes. This impacts what is displayed on the GDC Data Portal +* Better handling of concurrent transactions +* CIViC annotations now included on the ssms endpoint. You can read more about CIViC annotations [here](https://civicdb.org/home) + +### Bugs Fixed Since Last Release + +* Fixed API memory leak +* Fixed data offset issue returned by clinical.tar endpoint + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + + +## v1.22.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: July 31, 2019 + +### New Features and Changes + +* Updated BCR Clinical XML parser code to support future indexing of additional clinical data. Parser code can be found [here](https://github.com/NCI-GDC/gdcdatamodel/tree/develop/gdcdatamodel/xml_mappings) + + - Added a mapping for: + - `ann_arbor_b_symptoms` + - `ann_arbor_extranodal_involvement` + - `ajcc_pathologic_t` + - `ajcc_pathologic_n` + - `ajcc_pathologic_m` + - `ajcc_clinical_t` + - `ajcc_clinical_n` + - `ajcc_clinical_m` + - `ajcc_staging_system_edition` + - `figo_stage` + - `ajcc_clinical_stage` + - `primary_gleason_grade` + - `secondary_gleason_graade` + - `igcccg_stage` + - `masaoka_stage` + + - Updated the mapping for: + - `primary_diagnosis`, `morphology`, `tissue_or_organ_of_origin`, and `site_of_resection_or_biopsy` + +### Bugs Fixed Since Last Release + +* Fixed a bug preventing multipart uploads + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + +## v1.21.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: June 5, 2019 + +### New Features and Changes + +* Mutation indexer update to accommodate data model changes +* Updates to when in the release cycle downloaders and submitters have access to files + + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + +## v1.20.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: April 17, 2019 + +### New Features and Changes + +* Disallowed creation of multiple file versions in the same data release +* Improved API concurrency performance and addressed random failures/4XX/5XX responses +* Improved API/Portal performances for querying large sets of data from the Elasticsearch indices +* Updated BCR Clinical XML parser code to support future indexing of additional clinical data. Parser code can be found [here](https://github.com/NCI-GDC/gdcdatamodel/tree/develop/gdcdatamodel/xml_mappings) + - Updated the mapping for: + - `days_to_death` + - `days_to_birth` + - `vital_status` + - `prior_malignancy` and `synchronous_malignancy` + - Added a mapping for: + - `pack_years_smoked` + - `prior_treatment` + - `age_at_index` + - `days_to_diagnosis` + - `icd_10_code` + - `year_of_diagnosis` + - Remove calculation for: + - `cigarettes_per_day` + - `year_of_birth` + - `year_of_death` + - `bmi` + - Updated XML Parser to pull the most Up-to-Date Survival Information + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + + +## v1.19.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: February 20, 2019 + +### New Features and Changes + +* Added API features to support controlled access DAVE +* Updated API query endpoints to handle filtering of queries based on tokens +* Created login notification Endpoint +* Added hashing and logging for similar ES queries + +### Bugs Fixed Since Last Release + +* Fixed bug where quick search ES query grows with each request +* Fixed bug where new file versions could be created when exactly the same existing metadata is uploaded +* Fixed bug where submitting to specific projects produced error that data already existed + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + +## v1.18.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: December 18, 2018 + +### New Features and Changes + +* Update to auth for GDC Pre-Release Data Portal + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + + +## v1.17.0 + +* __GDC Product__: Application Programming Interface (API) +* __Release Date__: November 7, 2018 + +### New Features and Changes + +* Created new index cnv_centric +* Created new index cnv_occurrence_centric +* Created new REST API endpoints for CNV +* Created mapping from aliquot to case for occurrence on cnv_centric +* Created new graphql endpoints for CNV +* Updated index case_centric to add cnv +* Updated index gene_centric to add cnv + +### Bugs Fixed Since Last Release + +* Fixed bug to prevent users from deleting files in state submitted or released + +### Known Issues and Workarounds + +* Fields are not counted as missing if parent field is also missing. This may occur with queries of nested fields in the Data Portal Advanced Search or an API query using a filter. This behavior could impact results reported using search parameters of "IS MISSING" or "NOT MISSING". +* Certain very large API requests will time out. It is recommended to break up very large requests into a series of smaller requests. + + + ## v1.16.0 * __GDC Product__: Application Programming Interface (API) diff --git a/docs/API/Users_Guide/Additional_Examples.md b/docs/API/Users_Guide/Additional_Examples.md index 86057cbf0..8b852f61b 100644 --- a/docs/API/Users_Guide/Additional_Examples.md +++ b/docs/API/Users_Guide/Additional_Examples.md @@ -668,7 +668,7 @@ curl 'https://api.gdc.cancer.gov/cases?filters=%7b%0d%0a+++%22op%22+%3a+%22%3d%2 #### Example: Filter using a range -This is an example of filtering for age at diagnosis. The request is for cases where the age at diagnosis is between 40 and 70 years. *Note:* `age_at_diagnosis` is expressed in days. +This is an example of filtering for age at diagnosis. The request is for cases where the age at diagnosis is between 40 and 70 years. >**Note:** `age_at_diagnosis` is expressed in days. ```Filter { diff --git a/docs/API/Users_Guide/Appendix_C_Format_of_Submission_Requests_and_Responses.md b/docs/API/Users_Guide/Appendix_C_Format_of_Submission_Requests_and_Responses.md index e831cc09b..9de5b8060 100644 --- a/docs/API/Users_Guide/Appendix_C_Format_of_Submission_Requests_and_Responses.md +++ b/docs/API/Users_Guide/Appendix_C_Format_of_Submission_Requests_and_Responses.md @@ -123,4 +123,4 @@ API responses will contain a status for each entity specified in the request: **`error`**: The desired transaction was not sucessful, and the transaction was aborted because of this entity. This entity did not pass validation or an internal error occured when attempting to complete the transaction. The error state will be accompanied by a list of errors recorded about the entity (see label-error-messages). -**Note:** GDC API requests are transactional. An error with processing a node specified in the transaction will abort the transaction and will result in no changes being applied for any node involved in the transaction. +>**Note:** GDC API requests are transactional. An error with processing a node specified in the transaction will abort the transaction and will result in no changes being applied for any node involved in the transaction. diff --git a/docs/API/Users_Guide/BAM_Slicing.md b/docs/API/Users_Guide/BAM_Slicing.md index 4462549c3..56b96f5cf 100644 --- a/docs/API/Users_Guide/BAM_Slicing.md +++ b/docs/API/Users_Guide/BAM_Slicing.md @@ -13,7 +13,7 @@ Please note the following: * The functionality of this API differs from the usual functionality of `samtools` in that alignment records that overlap multiple regions will not be returned multiple times. * A request with no region or gene specified will return the BAM header, which makes it easy to inspect the references to which the alignment records were aligned. * A request for regions that are not included in the source BAM is not considered an error, and is treated the same as if no records existed for the region. -* Examples provided for BAM slicing functionality are intended for use with GDC harmonized data (i.e. BAM files available in the GDC Data Portal). Slicing of unharmonized BAM files (i.e. BAM files in the GDC Legacy Portal) is not supported. +* Examples provided for BAM slicing functionality are intended for use with GDC harmonized data (i.e. BAM files available in the GDC Data Portal). * Bam slicing does not create an associated bam index (.bai) file. For applications requiring a .bai file users will need to generate this file from the bam slice using a tool and command such as `samtools index`. ### Query Parameters @@ -21,11 +21,11 @@ Please note the following: The following query parameters and JSON fields are supported: | Description | Query Parameter | JSON Field | Query format | -|---|---|---| +|---|---|---|---| | entire chromosome, or a position or region on the chromosome, specified using chromosomal coordinates | region | regions | region=(:(-)?)? | -| region specified using a [HGNC](http://www.genenames.org/) / [GENCODE v22](http://www.gencodegenes.org/) gene name | gencode | gencode | gencode= | +| region specified using a [HGNC](http://www.genenames.org/) / [GENCODE v36](http://www.gencodegenes.org/) gene name | gencode | gencode | gencode= | -**NOTE:** The successfully sliced BAM will contain all reads that overlap (entirely or partially) with the specified region or gene. It is possible to specify an open-ended region, e.g. `chr2:10000`, which would return all reads that (completely or partially) overlap with the region of chromosome 2 from position 10,000 to the end of the chromosome. +>**NOTE:** The successfully sliced BAM will contain all reads that overlap (entirely or partially) with the specified region or gene. It is possible to specify an open-ended region, e.g. `chr2:10000`, which would return all reads that (completely or partially) overlap with the region of chromosome 2 from position 10,000 to the end of the chromosome. ### JSON Schema @@ -61,7 +61,7 @@ The following two requests are examples of BAM slicing using region(s). token=$( ``` +## Examples: Specifying unmapped reads + +Unmapped reads are found in GDC BAM files. You may request these reads by using the following commands. + +```GET +token=$( +``` + After downloading, the sliced BAM file can be converted to SAM using the following command if `samtools` is installed on the user's system: diff --git a/docs/API/Users_Guide/Data_Analysis.md b/docs/API/Users_Guide/Data_Analysis.md index d987f538c..0b7fa2e4c 100644 --- a/docs/API/Users_Guide/Data_Analysis.md +++ b/docs/API/Users_Guide/Data_Analysis.md @@ -1,27 +1,36 @@ # Data Analysis -The GDC DAVE tools use the same API as the rest of the Data Portal and takes advantage of several new endpoints. Similar to the [GDC Data Portal Exploration](http://docs.gdc.cancer.gov/Data_Portal/Users_Guide/Exploration/) feature, the GDC data analysis endpoints allow API users to programmatically explore data in the GDC using advanced filters at a gene and mutation level. Survival analysis data is also available. +The GDC data analysis endpoints allow API users to programmatically explore data in the GDC using advanced filters at a gene and mutation level. Survival analysis data is also available. ## Endpoints The following data analysis endpoints are available from the GDC API: -| __Endpoint__ | __Description__ | -|---|---| -| __/genes__ | Allows users to access summary information about each gene using its Ensembl ID. | -| __/ssms__ | Allows users to access information about each somatic mutation. For example, a `ssm` would represent the transition of C to T at position 52000 of chromosome 1. | -| __/ssm_occurrences__ | A `ssm` entity as applied to a single instance (case). An example of a `ssm occurrence` would be that the transition of C to T at position 52000 of chromosome 1 occurred in patient TCGA-XX-XXXX. | -|__/analysis/top_cases_counts_by_genes__| Returns the number of cases with a mutation in each gene listed in the gene_ids parameter for each project. Note that this endpoint cannot be used with the `format` or `fields` parameters.| -|__/analysis/top_mutated_genes_by_project__| Returns a list of genes that have the most mutations within a given project. | -|__/analysis/top_mutated_cases_by_gene__| Generates information about the cases that are most affected by mutations in a given number of genes | -|__/analysis/mutated_cases_count_by_project__| Returns counts for the number of cases that have associated `ssm` data in each project. The number of affected cases can be found under "case_with_ssm": {"doc_count": $case_count}.| -|__/analysis/survival__| Survival plots can be generated in the Data Portal for different subsets of data, based upon many query factors such as variants, disease type and projects. This endpoint can be used to programmatically retrieve the raw data to generate these plots and apply different filters to the data. (see Survival Example)| +|__Node__| __Endpoint__ | __Description__ | +|---|---|---| +|__Genes__| __/genes__ | Allows users to access summary information about each gene using its Ensembl ID. | +|__SSMS__| __/ssms__ | Allows users to access information about each somatic mutation. For example, a `ssm` would represent the transition of C to T at position 52000 of chromosome 1. | +||__/ssms/``__|Get information about a specific ssm using a ``, often supplemented with the `expand` option to show fields of interest. | +|| __/ssm_occurrences__ | A `ssm` entity as applied to a single instance (case). An example of a `ssm occurrence` would be that the transition of C to T at position 52000 of chromosome 1 occurred in patient TCGA-XX-XXXX. | +||__/ssm_occurrences/``__|Get information about a specific ssm occurrence using a ``, often supplemented with the `expand` option to show fields of interest. | +|__CNVS__|__/cnvs__|Allows users to access data about copy number variations (cnvs). This data will be specifc to cnvs and not a specific case. | +||__/cnvs/``__|Get information about a specific copy number variation using a ``, often supplemented with the `expand` option to show fields of interest. | +||__/cnvs/ids__|This endpoint will retrieve nodes that contain the queried cnv_id. This is accomplished by adding the query parameter: /cnvs/ids?query=``.| +||__/cnv_occurrences__|A `cnv` entity as applied to a single case.| +||__/cnv_occurrences/``__|Get information about a specific copy number variation occurrence using a ``, often supplemented with the `expand` option to show fields of interest. | +||__/cnv_occurrences/ids__|This endpoint will retrieve nodes that contain the queried cnv_occurrence_id. This is accomplished by adding the query parameter: /cnv_occurrences/ids?query=``| +|__Analysis__|__/analysis/top_cases_counts_by_genes__| Returns the number of cases with a mutation in each gene listed in the gene_ids parameter for each project. Note that this endpoint cannot be used with the `format` or `fields` parameters.| +||__/analysis/top_mutated_genes_by_project__| Returns a list of genes that have the most mutations within a given project. | +||__/analysis/top_mutated_cases_by_gene__| Generates information about the cases that are most affected by mutations in a given number of genes | +||__/analysis/mutated_cases_count_by_project__| Returns counts for the number of cases that have associated `ssm` data in each project. The number of affected cases can be found under "case_with_ssm": {"doc_count": $case_count}.| +||__/analysis/survival__| Survival plots can be generated in the Data Portal for different subsets of data, based upon many query factors such as variants, disease type and projects. This endpoint can be used to programmatically retrieve the raw data to generate these plots and apply different filters to the data. (see Survival Example)| + The methods for retrieving information from these endpoints are very similar to those used for the `cases` and `files` endpoints. These methods are explored in depth in the [API Search and Retrieval](https://docs.gdc.cancer.gov/API/Users_Guide/Search_and_Retrieval/) documentation. The `_mapping` parameter can also be used with each of these endpoints to generate a list of potential fields. For example: `https://api.gdc.cancer.gov/ssms/_mapping` -Note: While it is not an endpoint, the `observation` entity is featured in the visualization section of the API. The `observation` entity provides information from the MAF file, such as read depth and normal genotype, that supports the validity of the associated `ssm`. An example is demonstrated below: +While it is not an endpoint, the `observation` entity is featured in the visualization section of the API. The `observation` entity provides information from the MAF file, such as read depth and normal genotype, that supports the validity of the associated `ssm`. An example is demonstrated below: ```Shell curl "https://api.gdc.cancer.gov/ssms/57bb3f2e-ec05-52c2-ab02-7065b7d24849?expand=occurrence.case.observation.read_depth&pretty=true" @@ -143,22 +152,22 @@ gene_start gene_end symbol id ## Simple Somatic Mutation Endpoint Examples -__Example 1__: Similar to the `/genes` endpoint, a user would like to retrieve information about the mutation based on its COSMIC ID. This would be accomplished by creating a JSON filter such as: +__Example 1__: Similar to the `/genes` endpoint, a user would like to retrieve information about the mutation based on its COSMIC ID. This would be accomplished by creating a JSON filter, which will then be encoded to URL for the `curl` command. -```Query +```Filter { "op":"in", "content":{ "field":"cosmic_id", "value":[ - "COSM4860838" + "COSM1135366" ] } } ``` ```Shell -curl 'https://api.gdc.cancer.gov/ssms?pretty=true&filters=%7B%0A%22op%22%3A%22in%22%2C%0A%22content%22%3A%7B%0A%22field%22%3A%22cosmic_id%22%2C%0A%22value%22%3A%5B%0A%22COSM4860838%22%0A%5D%0A%7D%0A%7D%0A' +curl 'https://api.gdc.cancer.gov/ssms?pretty=true&filters=%7B%0A%22op%22%3A%22in%22%2C%0A%22content%22%3A%7B%0A%22field%22%3A%22cosmic_id%22%2C%0A%2value%22%3A%5B%0A%22COSM1135366%22%0A%5D%0A%7D%0A%7D%0A' ``` ```Response @@ -166,52 +175,117 @@ curl 'https://api.gdc.cancer.gov/ssms?pretty=true&filters=%7B%0A%22op%22%3A%22in "data": { "hits": [ { - "ncbi_build": "GRCh38", - "mutation_type": "Simple Somatic Mutation", - "mutation_subtype": "Single base substitution", - "end_position": 62438203, + "id": "edd1ae2c-3ca9-52bd-a124-b09ed304fcc2", + "start_position": 25245350, + "gene_aa_change": [ + "KRAS G12D" + ], "reference_allele": "C", - "ssm_id": "8b3c1a7a-e4e0-5200-9d46-5767c2982145", - "start_position": 62438203, + "ncbi_build": "GRCh38", "cosmic_id": [ - "COSM4860838", - "COSM731764", - "COSM731765" + "COSM1135366", + "COSM521" ], - "id": "8b3c1a7a-e4e0-5200-9d46-5767c2982145", + "mutation_subtype": "Single base substitution", + "mutation_type": "Simple Somatic Mutation", + "chromosome": "chr12", + "ssm_id": "edd1ae2c-3ca9-52bd-a124-b09ed304fcc2", + "genomic_dna_change": "chr12:g.25245350C>T", "tumor_allele": "T", - "gene_aa_change": [ - "CADPS G1147G", - "CADPS G1187G", - "CADPS G1217G", - "CADPS G1226G", - "CADPS G127G", - "CADPS G218G", - "CADPS G95G" - ], - "chromosome": "chr3", - "genomic_dna_change": "chr3:g.62438203C>T" + "end_position": 25245350 } ], "pagination": { "count": 1, - "sort": "", + "total": 1, + "size": 10, "from": 0, + "sort": "", "page": 1, - "total": 1, - "pages": 1, - "size": 10 + "pages": 1 } }, "warnings": {} } ``` +__Example 2:__ Based on the previous example's `ssm_id` (`8b3c1a7a-e4e0-5200-9d46-5767c2982145`), a user would like to look at the consequences and the VEP impact due to this ssm. + +```Shell +curl 'https://api.gdc.cancer.gov/ssms/edd1ae2c-3ca9-52bd-a124-b09ed304fcc2?pretty=true&expand=consequence.transcript&fields=consequence.transcript.annotation.vep_impact' +``` + +```JSON +{ + "data": { + "consequence": [ + { + "transcript": { + "annotation": { + "vep_impact": "MODERATE" + }, + "transcript_id": "ENST00000557334", + "aa_end": 12, + "consequence_type": "missense_variant", + "aa_start": 12, + "is_canonical": false, + "aa_change": "G12D", + "ref_seq_accession": "" + } + }, + { + "transcript": { + "annotation": { + "vep_impact": "MODERATE" + }, + "transcript_id": "ENST00000256078", + "aa_end": 12, + "consequence_type": "missense_variant", + "aa_start": 12, + "is_canonical": true, + "aa_change": "G12D", + "ref_seq_accession": "NM_001369786.1&NM_033360.4" + } + }, + { + "transcript": { + "annotation": { + "vep_impact": "MODERATE" + }, + "transcript_id": "ENST00000311936", + "aa_end": 12, + "consequence_type": "missense_variant", + "aa_start": 12, + "is_canonical": false, + "aa_change": "G12D", + "ref_seq_accession": "NM_001369787.1&NM_004985.5" + } + }, + { + "transcript": { + "annotation": { + "vep_impact": "MODERATE" + }, + "transcript_id": "ENST00000556131", + "aa_end": 12, + "consequence_type": "missense_variant", + "aa_start": 12, + "is_canonical": false, + "aa_change": "G12D", + "ref_seq_accession": "" + } + } + ] + }, + "warnings": {} +} +``` + ## Simple Somatic Mutation Occurrence Endpoint Examples __Example 1:__ A user wants to determine the chromosome in case `TCGA-DU-6407` that contains the greatest number of `ssms`. As this relates to mutations that are observed in a case, the `ssm_occurrences` endpoint is used. -``` +```Filter { "op":"in", "content":{ @@ -223,721 +297,2405 @@ __Example 1:__ A user wants to determine the chromosome in case `TCGA-DU-6407` t ```Shell curl "https://api.gdc.cancer.gov/ssm_occurrences?format=tsv&fields=ssm.chromosome&size=5000&filters=%7B%0D%0A%22op%22%3A%22in%22%2C%0D%0A%22content%22%3A%7B%0D%0A%22field%22%3A%22case.submitter_id%22%2C%0D%0A%22value%22%3A%5B%0D%0A%22TCGA-DU-6407%22%0D%0A%5D%0D%0A%7D%0D%0A%7D" ``` -```Response -ssm.chromosome id -chr3 552c09d1-69b1-5c04-b543-524a6feae3eb -chr10 391011ff-c1fd-5e2a-a128-652bc660f64c -chr10 1378cbc4-af88-55bb-b2e5-185bb4246d7a -chr10 3a2b3870-a395-5bc3-8c8f-0d40b0f2202c -chr1 4a93d7a5-988d-5055-80da-999dc3b45d80 -chrX 22a07c7c-16ba-51df-a9a9-1e41e2a45225 -chr12 dbc5eafa-ea26-5f1c-946c-b6974a345b69 -chr11 02ae553d-1f27-565d-96c5-2c3cfca7264a -chr2 faee73a9-4804-58ea-a91f-18c3d901774f -chr6 97c5b38b-fc96-57f5-8517-cc702b3aa70a -chr17 0010a89d-9434-5d97-8672-36ee394767d0 -chr19 f08dcc53-eadc-5ceb-bf31-f6b38629e4cb -chrX 19ca262d-b354-54a0-b582-c4719e37e91d -chr19 c44a93a1-5c73-5cff-b40e-98ce7e5fe57b -chr3 b67f31b5-0341-518e-8fcc-811cd2e36af1 -chr1 94abd5fd-d539-5a4a-8719-9615cf7cec5d -chr17 1476a543-2951-5ec4-b165-67551b47d810 -chr2 b4822fc9-f0cc-56fd-9d97-f916234e309d -chr2 3548ecfe-5186-51e7-8f40-37f4654cd260 -chr16 105e7811-4601-5ccb-ae93-e7107923599e -chr2 99b3aad4-d368-506d-99d6-047cbe5dff0f -chr13 9dc3f7cd-9efa-530a-8524-30d067e49d54 -chr21 1267330b-ae6d-5e25-b19e-34e98523679e -chr16 c77f7ce5-fbe6-5da4-9a7b-b528f8e530cb -chr10 2cb06277-993e-5502-b2c5-263037c45d18 -chr17 d25129ad-3ad7-584f-bdeb-fba5c3881d32 -chr17 a76469cb-973c-5d4d-bf82-7cf4e8f6c129 -chr10 727c9d57-7b74-556f-aa5b-e1ca1f76d119 -chr15 b4a86ffd-e60c-5c9c-aaa1-9e9f02d86116 -chr5 3a023e72-da92-54f7-aa18-502c1076b2b0 +```tsv +id ssm.chromosome +105e7811-4601-5ccb-ae93-e7107923599e chr16 +faee73a9-4804-58ea-a91f-18c3d901774f chr2 +99b3aad4-d368-506d-99d6-047cbe5dff0f chr2 +2cb06277-993e-5502-b2c5-263037c45d18 chr10 +f08dcc53-eadc-5ceb-bf31-f6b38629e4cb chr19 +97c5b38b-fc96-57f5-8517-cc702b3aa70a chr6 +19ca262d-b354-54a0-b582-c4719e37e91d chrX +b4822fc9-f0cc-56fd-9d97-f916234e309d chr2 +22a07c7c-16ba-51df-a9a9-1e41e2a45225 chrX +0010a89d-9434-5d97-8672-36ee394767d0 chr17 +3a023e72-da92-54f7-aa18-502c1076b2b0 chr5 +391011ff-c1fd-5e2a-a128-652bc660f64c chr10 +3548ecfe-5186-51e7-8f40-37f4654cd260 chr2 +b67f31b5-0341-518e-8fcc-811cd2e36af1 chr3 +4a93d7a5-988d-5055-80da-999dc3b45d80 chr1 +9dc3f7cd-9efa-530a-8524-30d067e49d54 chr13 +552c09d1-69b1-5c04-b543-524a6feae3eb chr3 +dbc5eafa-ea26-5f1c-946c-b6974a345b69 chr12 +d25129ad-3ad7-584f-bdeb-fba5c3881d32 chr17 +1378cbc4-af88-55bb-b2e5-185bb4246d7a chr10 +c44a93a1-5c73-5cff-b40e-98ce7e5fe57b chr19 +1267330b-ae6d-5e25-b19e-34e98523679e chr21 +1476a543-2951-5ec4-b165-67551b47d810 chr17 +727c9d57-7b74-556f-aa5b-e1ca1f76d119 chr10 +94abd5fd-d539-5a4a-8719-9615cf7cec5d chr1 +a76469cb-973c-5d4d-bf82-7cf4e8f6c129 chr17 ``` - -## Analysis Endpoints - -In addition to the `ssms`, `ssm_occurrences`, and `genes` endpoints mentioned previously, several `/analysis` endpoints were designed to quickly retrieve specific datasets used for visualization display. - -__Example 1:__ The `/analysis/top_cases_counts_by_genes` endpoint gives the number of cases with a mutation in each gene listed in the `gene_ids` parameter for each project. Note that this endpoint cannot be used with the `format` or `fields` parameters. In this instance, the query will produce the number of cases in each projects with mutations in the gene `ENSG00000155657`. +__Example 2:__ A user has retrieved a `ssm_occurrence`, and would like to determine if that case also has diagnostic information. ```Shell -curl "https://api.gdc.cancer.gov/analysis/top_cases_counts_by_genes?gene_ids=ENSG00000155657&pretty=true" +curl 'https://api.gdc.cancer.gov/ssm_occurrences/6fd8527d-5c40-5604-8fa9-0ce798eec231?pretty=true&expand=case.diagnoses' ``` - -This JSON-formatted output is broken up by project. For an example, see the following text: - -```json - "genes": { - "my_genes": { - "gene_id": { - "buckets": [ - { - "key": "ENSG00000155657", - "doc_count": 45 - } - ], - "sum_other_doc_count": 0, - "doc_count_error_upper_bound": 0 - }, - "doc_count": 45 - }, - "doc_count": 12305 - }, - "key": "TCGA-GBM", - "doc_count": 45 +```Json +{ + "data": { + "ssm_occurrence_id": "6fd8527d-5c40-5604-8fa9-0ce798eec231", + "case": { + "diagnoses": [ + { + "ajcc_pathologic_t": "T3b", + "synchronous_malignancy": "No", + "morphology": "8720/3", + "ajcc_pathologic_stage": "Stage IIB", + "ajcc_pathologic_n": "N0", + "ajcc_pathologic_m": "M0", + "submitter_id": "TCGA-Z2-A8RT_diagnosis", + "days_to_diagnosis": 0, + "last_known_disease_status": "not reported", + "tissue_or_organ_of_origin": "Skin, NOS", + "days_to_last_follow_up": 839.0, + "age_at_diagnosis": 15342, + "primary_diagnosis": "Malignant melanoma, NOS", + "classification_of_tumor": "not reported", + "prior_malignancy": "no", + "year_of_diagnosis": 2012, + "diagnosis_id": "1d06a202-c51a-52e2-805f-eeb5f7fac14e", + "icd_10_code": "C44.6", + "site_of_resection_or_biopsy": "Skin of upper limb and shoulder", + "prior_treatment": "No", + "state": "released", + "tumor_grade": "Not Reported", + "progression_or_recurrence": "not reported", + "ajcc_staging_system_edition": "7th" } + ] + } + }, + "warnings": {} +} ``` -This portion of the output shows TCGA-GBM including 45 cases that have `ssms` in the gene `ENSG00000155657`. +## Copy Number Variation Endpoint Examples -__Example 2:__ The following demonstrates a use of the `/analysis/top_mutated_genes_by_project` endpoint. This will output the genes that are mutated in the most cases in "TCGA-DLBC" and will count the mutations that have a `HIGH` or `MODERATE` impact on gene function. Note that the `score` field does not represent the number of mutations in a given gene, but a calculation that is used to determine which genes have the greatest number of unique mutations. +__Example 1:__ A user is interested in finding the first 30 cnvs found on chromosome 4 that have a cnv loss. -```json -{ - "op":"AND", - "content":[ - { - "op":"in", - "content":{ - "field":"case.project.project_id", - "value":[ - "TCGA-DLBC" - ] - } - }, - { - "op":"in", - "content":{ - "field":"case.ssm.consequence.transcript.annotation.impact", - "value":[ - "HIGH", - "MODERATE" - ] - } - } - ] +```Filter +{ + "op": "and", + "content": [ + { + "op": "in", + "content": { + "field": "chromosome", + "value": [ + "4" + ] + } + }, + { + "op": "in", + "content": { + "field": "cnv_change", + "value": [ + "Loss" + ] + } + } + ] } ``` + ```Shell -curl "https://api.gdc.cancer.gov/analysis/top_mutated_genes_by_project?fields=gene_id,symbol&filters=%7B%22op%22%3A%22AND%22%2C%22content%22%3A%5B%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22case.project.project_id%22%2C%22value%22%3A%5B%22TCGA-DLBC%22%5D%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22case.ssm.consequence.transcript.annotation.impact%22%2C%22value%22%3A%5B%22HIGH%22%2C%22MODERATE%22%5D%7D%7D%5D%7D&pretty=true" +curl 'https://api.gdc.cancer.gov/cnvs?filters=%7B%0D%0A+++%22op%22%3A+%22and%22%2C%0D%0A++++%22content%22%3A+%5B%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22chromosome%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%224%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22cnv_change%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22Loss%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%0D%0A++++%5D%0D%0A%7D&size=30&sort=start_position&format=tsv' ``` -```Response + +```tsv +chromosome cnv_change cnv_id end_position gene_level_cn id ncbi_build start_position +4 Loss 11381600-f064-5c42-90d2-a5c79c8b23e1 88208 True 11381600-f064-5c42-90d2-a5c79c8b23e1 GRCh38 53286 +4 Loss edef0f2f-c1a7-507c-842f-e1f8a568df9d 202303 True edef0f2f-c1a7-507c-842f-e1f8a568df9d GRCh38 124501 +4 Loss eba92f9a-b045-54a8-948a-451e439ed418 305474 True eba92f9a-b045-54a8-948a-451e439ed418 GRCh38 270675 +4 Loss 89319453-2a3f-5ebe-be30-8af0426e0343 384868 True 89319453-2a3f-5ebe-be30-8af0426e0343 GRCh38 337814 +4 Loss 6567929c-4b6f-582b-aedf-acde2c0ec736 499156 True 6567929c-4b6f-582b-aedf-acde2c0ec736 GRCh38 425815 +4 Loss 2daff58b-5065-50cd-8239-253180eaee81 540200 True 2daff58b-5065-50cd-8239-253180eaee81 GRCh38 499210 +4 Loss 2b42c8d4-6d85-5352-96e1-9e52e722c248 576295 True 2b42c8d4-6d85-5352-96e1-9e52e722c248 GRCh38 573880 +4 Loss 2646cdc7-7602-59a4-ae4f-d171352bae88 670782 True 2646cdc7-7602-59a4-ae4f-d171352bae88 GRCh38 625573 +4 Loss c11ad392-949f-593f-a3ab-d834b2f82809 674330 True c11ad392-949f-593f-a3ab-d834b2f82809 GRCh38 672436 +4 Loss f31be658-4de0-549e-81be-e79759879acf 682033 True f31be658-4de0-549e-81be-e79759879acf GRCh38 673580 +4 Loss d72c62f2-fc29-5b83-9839-7f6b03970aff 689271 True d72c62f2-fc29-5b83-9839-7f6b03970aff GRCh38 681829 +4 Loss 45448d47-6e13-5d30-824d-96150a7f55c6 770640 True 45448d47-6e13-5d30-824d-96150a7f55c6 GRCh38 705748 +4 Loss 517e65ea-9084-54c2-abe0-b1b47e9f872c 826129 True 517e65ea-9084-54c2-abe0-b1b47e9f872c GRCh38 784957 +4 Loss b5a09c9b-d842-5b76-a500-56f18252c29d 932373 True b5a09c9b-d842-5b76-a500-56f18252c29d GRCh38 849276 +4 Loss e3a3b61d-2881-5ad4-90bf-58ef29ae9ecb 958656 True e3a3b61d-2881-5ad4-90bf-58ef29ae9ecb GRCh38 932387 +4 Loss 8630a1b6-3215-5b71-903a-ad9845505afc 986895 True 8630a1b6-3215-5b71-903a-ad9845505afc GRCh38 958887 +4 Loss f748b06f-1fb7-53a9-a7d6-2c22a3ae6de5 993440 True f748b06f-1fb7-53a9-a7d6-2c22a3ae6de5 GRCh38 979073 +4 Loss a5e4a63f-c5f6-5f0f-a6b6-f51bfb643533 1004564 True a5e4a63f-c5f6-5f0f-a6b6-f51bfb643533 GRCh38 986997 +4 Loss 73f6fbbe-6fd9-524c-a7c8-a7cf3f08ada4 1026898 True 73f6fbbe-6fd9-524c-a7c8-a7cf3f08ada4 GRCh38 1009936 +4 Loss adad579a-b002-5022-823a-570c59549065 1113564 True adad579a-b002-5022-823a-570c59549065 GRCh38 1056250 +4 Loss d5a5c45e-594b-5cbc-97d5-75fc5155d021 1208962 True d5a5c45e-594b-5cbc-97d5-75fc5155d021 GRCh38 1166932 +4 Loss 6c910993-faa8-5abc-b433-b3afcc5e9e11 1249953 True 6c910993-faa8-5abc-b433-b3afcc5e9e11 GRCh38 1211445 +4 Loss 4453b4cb-7d8a-5e26-a856-eac62eec287a 1340147 True 4453b4cb-7d8a-5e26-a856-eac62eec287a GRCh38 1289887 +4 Loss 6db1001a-a41b-518d-9491-2bf41544d90f 1395989 True 6db1001a-a41b-518d-9491-2bf41544d90f GRCh38 1345691 +4 Loss 6bef981a-ead1-5aa7-8a69-8d38e576e5c0 1406442 True 6bef981a-ead1-5aa7-8a69-8d38e576e5c0 GRCh38 1402932 +4 Loss af6e0b49-922a-587e-b353-4b9414605cf1 1684261 True af6e0b49-922a-587e-b353-4b9414605cf1 GRCh38 1617915 +4 Loss 400352ad-8526-562a-bbf4-29b90a48f46f 1712344 True 400352ad-8526-562a-bbf4-29b90a48f46f GRCh38 1692731 +4 Loss 8811414d-2434-56c6-afe5-a998c9b18d47 1745171 True 8811414d-2434-56c6-afe5-a998c9b18d47 GRCh38 1712891 +4 Loss 169c4409-0256-5841-9314-f1a4dd2bcc38 1721358 True 169c4409-0256-5841-9314-f1a4dd2bcc38 GRCh38 1715952 +4 Loss 1712ccac-6e70-5fb3-b71e-1a029eaf047c 1808872 True 1712ccac-6e70-5fb3-b71e-1a029eaf047c GRCh38 1793293 +``` + +__Example 2:__ A user wants to determine the location and identity of the gene affected by the cnv `544c4896-0152-5787-8d77-894a16f0ded0`, and determine whether the gene is found within the Cancer Gene Census. + +```Shell +curl 'https://api.gdc.cancer.gov/cnvs/544c4896-0152-5787-8d77-894a16f0ded0?pretty=true&expand=consequence.gene' +``` + +```Json { "data": { - "hits": [ - { - "_score": 14.0, - "symbol": "IGHV2-70", - "gene_id": "ENSG00000274576" - }, - { - "_score": 14.0, - "symbol": "IGLV3-1", - "gene_id": "ENSG00000211673" - }, - { - "_score": 14.0, - "symbol": "IGHM", - "gene_id": "ENSG00000211899" - }, - { - "_score": 11.0, - "symbol": "KMT2D", - "gene_id": "ENSG00000167548" - }, - { - "_score": 11.0, - "symbol": "IGLL5", - "gene_id": "ENSG00000254709" - }, - { - "_score": 11.0, - "symbol": "BTG2", - "gene_id": "ENSG00000159388" - }, - { - "_score": 9.0, - "symbol": "CARD11", - "gene_id": "ENSG00000198286" - }, - { - "_score": 9.0, - "symbol": "IGHG1", - "gene_id": "ENSG00000211896" - }, - { - "_score": 9.0, - "symbol": "IGLC2", - "gene_id": "ENSG00000211677" - }, + "start_position": 27100354, + "consequence": [ { - "_score": 9.0, - "symbol": "LRP1B", - "gene_id": "ENSG00000168702" + "gene": { + "biotype": "protein_coding", + "symbol": "HOXA2", + "gene_id": "ENSG00000105996" + } } ], - "pagination": { - "count": 10, - "sort": "None", - "from": 0, - "page": 1, - "total": 3214, - "pages": 322, - "size": 10 - } + "gene_level_cn": true, + "cnv_change": "Gain", + "ncbi_build": "GRCh38", + "chromosome": "7", + "cnv_id": "544c4896-0152-5787-8d77-894a16f0ded0", + "end_position": 27102686 }, "warnings": {} } ``` -__Example 3:__ The `/analysis/top_mutated_cases_by_gene` endpoint will generate information about the cases that are most affected by mutations in a given number of genes. Below, the file count for each category is given for the cases most affected by mutations in these 50 genes. The size of the output is limited to two cases with the `size=2` parameter, but a higher value can be set by the user. +## Copy Number Variation Occurrence Enpoint Examples -```Shell -curl "https://api.gdc.cancer.gov/analysis/top_mutated_cases_by_gene?fields=diagnoses.days_to_death,diagnoses.age_at_diagnosis,diagnoses.vital_status,diagnoses.primary_diagnosis,demographic.gender,demographic.race,demographic.ethnicity,case_id,summary.data_categories.file_count,summary.data_categories.data_category&filters=%7B%22op%22%3A%22and%22%2C%22content%22%3A%5B%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%22TCGA-DLBC%22%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22genes.gene_id%22%2C%22value%22%3A%5B%22ENSG00000166710%22%2C%22ENSG00000005339%22%2C%22ENSG00000083857%22%2C%22ENSG00000168769%22%2C%22ENSG00000100906%22%2C%22ENSG00000184677%22%2C%22ENSG00000101680%22%2C%22ENSG00000101266%22%2C%22ENSG00000028277%22%2C%22ENSG00000140968%22%2C%22ENSG00000181827%22%2C%22ENSG00000116815%22%2C%22ENSG00000275221%22%2C%22ENSG00000139083%22%2C%22ENSG00000112851%22%2C%22ENSG00000112697%22%2C%22ENSG00000164134%22%2C%22ENSG00000009413%22%2C%22ENSG00000071626%22%2C%22ENSG00000135407%22%2C%22ENSG00000101825%22%2C%22ENSG00000104814%22%2C%22ENSG00000166415%22%2C%22ENSG00000142867%22%2C%22ENSG00000254585%22%2C%22ENSG00000139718%22%2C%22ENSG00000077721%22%2C%22ENSG00000130294%22%2C%22ENSG00000117245%22%2C%22ENSG00000117318%22%2C%22ENSG00000270550%22%2C%22ENSG00000163637%22%2C%22ENSG00000166575%22%2C%22ENSG00000065526%22%2C%22ENSG00000156453%22%2C%22ENSG00000128191%22%2C%22ENSG00000055609%22%2C%22ENSG00000204469%22%2C%22ENSG00000187605%22%2C%22ENSG00000185875%22%2C%22ENSG00000110888%22%2C%22ENSG00000007341%22%2C%22ENSG00000173198%22%2C%22ENSG00000115568%22%2C%22ENSG00000163714%22%2C%22ENSG00000125772%22%2C%22ENSG00000080815%22%2C%22ENSG00000189079%22%2C%22ENSG00000120837%22%2C%22ENSG00000143951%22%5D%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22ssms.consequence.transcript.annotation.impact%22%2C%22value%22%3A%5B%22HIGH%22%5D%7D%7D%5D%7D&pretty=true&size=2" -``` -```Response +__Example 1:__ A user is interested in finding cases that have both cnv and ssm data for females diagnosed with Squamous Cell Neoplasms and have a cnv gain change on chromosome 9. It is important to note that for a case like this, where multiple arguments are need for one filtered field, it is easier for the API to have multiple filters for the same field, `case.available_variation_data` in this example, than having one filter with multiple arguments. + +```Filter { - "data": { - "hits": [ - { - "_score": 7.0, - "diagnoses": [ - { - "days_to_death": null, - "vital_status": "alive", - "age_at_diagnosis": 18691, - "primary_diagnosis": "c83.3" - } - ], - "case_id": "eda9496e-be80-4a13-bf06-89f0cc9e937f", - "demographic": { - "gender": "male", - "race": "white", - "ethnicity": "hispanic or latino" + "op": "and", + "content": [ + { + "op": "in", + "content": { + "field": "cnv.cnv_change", + "value": [ + "Gain" + ] + } }, - "summary": { - "data_categories": [ - { - "file_count": 1, - "data_category": "DNA Methylation" - }, - { - "file_count": 5, - "data_category": "Transcriptome Profiling" - }, - { - "file_count": 1, - "data_category": "Biospecimen" - }, - { - "file_count": 16, - "data_category": "Simple Nucleotide Variation" - }, - { - "file_count": 1, - "data_category": "Clinical" - }, - { - "file_count": 4, - "data_category": "Copy Number Variation" - }, - { - "file_count": 4, - "data_category": "Raw Sequencing Data" + { + "op": "in", + "content": { + "field": "case.demographic.gender", + "value": [ + "female" + ] } - ] - } - }, - { - "_score": 4.0, - "diagnoses": [ - { - "days_to_death": null, - "vital_status": "alive", - "age_at_diagnosis": 27468, - "primary_diagnosis": "c83.3" - } - ], - "case_id": "a43e5f0e-a21f-48d8-97e0-084d413680b7", - "demographic": { - "gender": "male", - "race": "white", - "ethnicity": "not hispanic or latino" }, - "summary": { - "data_categories": [ - { - "file_count": 1, - "data_category": "DNA Methylation" - }, - { - "file_count": 5, - "data_category": "Transcriptome Profiling" - }, - { - "file_count": 1, - "data_category": "Biospecimen" - }, - { - "file_count": 16, - "data_category": "Simple Nucleotide Variation" - }, - { - "file_count": 1, - "data_category": "Clinical" - }, - { - "file_count": 4, - "data_category": "Copy Number Variation" - }, - { - "file_count": 4, - "data_category": "Raw Sequencing Data" + { + "op": "in", + "content": { + "field": "case.available_variation_data", + "value": [ + "cnv" + ] + } + }, + { + "op": "in", + "content": { + "field": "case.available_variation_data", + "value": [ + "ssm" + ] + } + }, + { + "op": "in", + "content": { + "field": "cnv.chromosome", + "value": [ + "9" + ] + } + }, + { + "op": "in", + "content": { + "field": "case.disease_type", + "value": [ + "Squamous Cell Neoplasms" + ] } - ] } - } - ], - "pagination": { - "count": 2, - "sort": "None", - "from": 0, - "page": 1, - "total": 27, - "pages": 14, - "size": 2 - } - }, - "warnings": {} + ] } -``` -__Example 4:__ The `/analysis/mutated_cases_count_by_project` endpoint produces counts for the number of cases that have associated `ssm` data in each project. The number of affected cases can be found under `"case_with_ssm": {"doc_count": $case_count}`. +``` ```Shell -curl "https://api.gdc.cancer.gov/analysis/mutated_cases_count_by_project?size=0&pretty=true" +curl 'https://api.gdc.cancer.gov/cnv_occurrences?filters=%7B%0D%0A++++%22op%22%3A+%22and%22%2C%0D%0A++++%22content%22%3A+%5B%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22cnv.cnv_change%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22Gain%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.demographic.gender%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22female%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.available_variation_data%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22cnv%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.available_variation_data%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22ssm%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22cnv.chromosome%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%229%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%2C%0D%0A++++++++%7B%0D%0A++++++++++++%22op%22%3A+%22in%22%2C%0D%0A++++++++++++%22content%22%3A+%7B%0D%0A++++++++++++++++%22field%22%3A+%22case.disease_type%22%2C%0D%0A++++++++++++++++%22value%22%3A+%5B%0D%0A++++++++++++++++++++%22Squamous+Cell+Neoplasms%22%0D%0A++++++++++++++++%5D%0D%0A++++++++++++%7D%0D%0A++++++++%7D%0D%0A++++%5D%0D%0A%7D&fields=case.available_variation_data,case.case_id&format=tsv' +``` + +```tsv +case.available_variation_data.0 case.available_variation_data.1 case.case_id id +cnv ssm da30a845-c4d3-4c78-b8b0-210239224f8f 3caf6e3b-024f-57b6-bdd9-3b67e423cc11 +cnv ssm 0809ba8b-4ab6-4f43-934c-c1ccbc014a7e e6afe58e-c99c-5c8d-920e-8ba4daad4d89 +cnv ssm 8e0e456e-85ee-4de5-8f0b-72393d6acde0 9d983d9c-8320-53f1-9054-e46926c5b834 +cnv ssm 64a195f6-2212-4e81-bccc-e39c77a10908 8caeaecc-ad68-539d-8b3c-8320b3684763 +cnv ssm 2f6a0e87-1e6c-41f3-93e0-3e505fa654b0 4862c166-0f37-5e3c-ae4e-a2964de01cea +cnv ssm f0daf315-8909-4cda-886d-a2770b08db94 099ff6cd-bd28-56f4-a181-6b02f3ba7503 +cnv ssm ff3808e4-eece-4046-819b-fe1019317f8e 0c936aa2-393e-5463-a431-3613b4510021 +cnv ssm 9205dc07-93f5-4b5e-924e-8e097616160f 133d27a7-fdc6-5082-a1f3-022b89f4e851 +cnv ssm 79ae5209-f476-4d65-a6c0-ebc18d7c8942 7a5e6bb1-8af3-5964-a3cc-c53602c8b099 +cnv ssm ff7099e1-8ff9-48e4-842d-46e98076e7e6 fb27fa8f-aa31-5e20-84da-8f45bb675405 +``` + +__Example 2:__ A user is interested in the first cnv occurrence (`3b9f7ecc-2280-5b89-80f9-ec8d6c5e604e`) from the previous example, and would like to know more about the case exposures and demographics. + +```Shell +curl 'https://api.gdc.cancer.gov/cnv_occurrences/3b9f7ecc-2280-5b89-80f9-ec8d6c5e604e?pretty=true&expand=cnv,case,case.exposures,case.demographic' +``` + +```Json +{ + "data": { + "cnv": { + "start_position": 68815994, + "gene_level_cn": true, + "cnv_change": "Gain", + "ncbi_build": "GRCh38", + "chromosome": "4", + "variant_status": "Tumor Only", + "cnv_id": "1a889109-30d5-51e3-848f-9f615c69f407", + "end_position": 68832023 + }, + "cnv_occurrence_id": "3b9f7ecc-2280-5b89-80f9-ec8d6c5e604e", + "case": { + "exposures": [ + { + "cigarettes_per_day": 5.47945205479452, + "alcohol_history": "Not Reported", + "exposure_id": "f7b08a8e-d22b-5cb0-be9f-b922c9ca87d2", + "submitter_id": "TCGA-38-4629_exposure", + "state": "released", + "pack_years_smoked": 100.0 + } + ], + "primary_site": "Bronchus and lung", + "disease_type": "Adenomas and Adenocarcinomas", + "available_variation_data": [ + "cnv", + "ssm" + ], + "case_id": "127bf818-f7e5-46b5-a9de-39f6d96b8b83", + "submitter_id": "TCGA-38-4629", + "state": "released", + "demographic": { + "demographic_id": "9ea1f795-9510-5acc-a9a5-bf1379e6635a", + "ethnicity": "not hispanic or latino", + "gender": "male", + "race": "white", + "vital_status": "Dead", + "age_at_index": 68, + "submitter_id": "TCGA-38-4629_demographic", + "days_to_death": 864, + "days_to_birth": -25104, + "state": "released", + "year_of_death": 2005, + "year_of_birth": 1935 + } + } + }, + "warnings": {} +} +``` + +## Analysis Endpoints + +In addition to the `ssms`, `ssm_occurrences`, and `genes` endpoints mentioned previously, several `/analysis` endpoints were designed to quickly retrieve specific datasets used for visualization display. + +__Example 1:__ The `/analysis/top_cases_counts_by_genes` endpoint gives the number of cases with a mutation in each gene listed in the `gene_ids` parameter for each project. Note that this endpoint cannot be used with the `format` or `fields` parameters. In this instance, the query will produce the number of cases in each projects with mutations in the gene `ENSG00000155657`. + +```Shell +curl "https://api.gdc.cancer.gov/analysis/top_cases_counts_by_genes?gene_ids=ENSG00000155657&pretty=true" +``` + + +This JSON-formatted output is broken up by project. For an example, see the following text: + +```json +$ curl "https://api.gdc.cancer.gov/analysis/top_cases_counts_by_genes?gene_ids=ENSG00000155657&pretty=true" +{ + "took": 6, + "timed_out": false, + "_shards": { + "total": 12, + "successful": 12, + "skipped": 0, + "failed": 0 + }, + "hits": { + "total": { + "value": 5967, + "relation": "eq" + }, + "max_score": null, + "hits": [] + }, + "aggregations": { + "projects": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "TCGA-BRCA", + "doc_count": 425, + "genes": { + "doc_count": 4031450, + "my_genes": { + "doc_count": 425, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 425 + } + ] + } + } + } + }, + { + "key": "TCGA-LUSC", + "doc_count": 423, + "genes": { + "doc_count": 4123089, + "my_genes": { + "doc_count": 423, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 423 + } + ] + } + } + } + }, + { + "key": "CPTAC-3", + "doc_count": 421, + "genes": { + "doc_count": 251552, + "my_genes": { + "doc_count": 421, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 421 + } + ] + } + } + } + }, + { + "key": "TCGA-SKCM", + "doc_count": 391, + "genes": { + "doc_count": 3040929, + "my_genes": { + "doc_count": 391, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 391 + } + ] + } + } + } + }, + { + "key": "TCGA-LUAD", + "doc_count": 345, + "genes": { + "doc_count": 3188761, + "my_genes": { + "doc_count": 345, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 345 + } + ] + } + } + } + }, + { + "key": "TCGA-OV", + "doc_count": 341, + "genes": { + "doc_count": 3728561, + "my_genes": { + "doc_count": 341, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 341 + } + ] + } + } + } + }, + { + "key": "TCGA-STAD", + "doc_count": 300, + "genes": { + "doc_count": 2145783, + "my_genes": { + "doc_count": 300, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 300 + } + ] + } + } + } + }, + { + "key": "TCGA-UCEC", + "doc_count": 297, + "genes": { + "doc_count": 1637055, + "my_genes": { + "doc_count": 297, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 297 + } + ] + } + } + } + }, + { + "key": "TCGA-HNSC", + "doc_count": 293, + "genes": { + "doc_count": 2325617, + "my_genes": { + "doc_count": 293, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 293 + } + ] + } + } + } + }, + { + "key": "TCGA-COAD", + "doc_count": 288, + "genes": { + "doc_count": 1695280, + "my_genes": { + "doc_count": 288, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 288 + } + ] + } + } + } + }, + { + "key": "TCGA-BLCA", + "doc_count": 280, + "genes": { + "doc_count": 2466835, + "my_genes": { + "doc_count": 280, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 280 + } + ] + } + } + } + }, + { + "key": "MMRF-COMMPASS", + "doc_count": 181, + "genes": { + "doc_count": 45977, + "my_genes": { + "doc_count": 181, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 181 + } + ] + } + } + } + }, + { + "key": "TCGA-LIHC", + "doc_count": 167, + "genes": { + "doc_count": 1216775, + "my_genes": { + "doc_count": 167, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 167 + } + ] + } + } + } + }, + { + "key": "TCGA-CESC", + "doc_count": 161, + "genes": { + "doc_count": 1103281, + "my_genes": { + "doc_count": 161, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 161 + } + ] + } + } + } + }, + { + "key": "TCGA-KIRC", + "doc_count": 161, + "genes": { + "doc_count": 842546, + "my_genes": { + "doc_count": 161, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 161 + } + ] + } + } + } + }, + { + "key": "CPTAC-2", + "doc_count": 131, + "genes": { + "doc_count": 72575, + "my_genes": { + "doc_count": 131, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 131 + } + ] + } + } + } + }, + { + "key": "TCGA-GBM", + "doc_count": 131, + "genes": { + "doc_count": 756809, + "my_genes": { + "doc_count": 131, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 131 + } + ] + } + } + } + }, + { + "key": "TCGA-ESCA", + "doc_count": 129, + "genes": { + "doc_count": 1210888, + "my_genes": { + "doc_count": 129, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 129 + } + ] + } + } + } + }, + { + "key": "TCGA-PRAD", + "doc_count": 101, + "genes": { + "doc_count": 379949, + "my_genes": { + "doc_count": 101, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 101 + } + ] + } + } + } + }, + { + "key": "HCMI-CMDC", + "doc_count": 99, + "genes": { + "doc_count": 54829, + "my_genes": { + "doc_count": 99, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 99 + } + ] + } + } + } + }, + { + "key": "TCGA-READ", + "doc_count": 98, + "genes": { + "doc_count": 726313, + "my_genes": { + "doc_count": 98, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 98 + } + ] + } + } + } + }, + { + "key": "TCGA-LGG", + "doc_count": 95, + "genes": { + "doc_count": 424689, + "my_genes": { + "doc_count": 95, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 95 + } + ] + } + } + } + }, + { + "key": "TCGA-KIRP", + "doc_count": 93, + "genes": { + "doc_count": 521936, + "my_genes": { + "doc_count": 93, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 93 + } + ] + } + } + } + }, + { + "key": "TCGA-SARC", + "doc_count": 93, + "genes": { + "doc_count": 903111, + "my_genes": { + "doc_count": 93, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 93 + } + ] + } + } + } + }, + { + "key": "TCGA-TGCT", + "doc_count": 51, + "genes": { + "doc_count": 524456, + "my_genes": { + "doc_count": 51, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 51 + } + ] + } + } + } + }, + { + "key": "TARGET-ALL-P2", + "doc_count": 50, + "genes": { + "doc_count": 1882, + "my_genes": { + "doc_count": 50, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 50 + } + ] + } + } + } + }, + { + "key": "TCGA-KICH", + "doc_count": 43, + "genes": { + "doc_count": 353674, + "my_genes": { + "doc_count": 43, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 43 + } + ] + } + } + } + }, + { + "key": "TCGA-PAAD", + "doc_count": 43, + "genes": { + "doc_count": 300427, + "my_genes": { + "doc_count": 43, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 43 + } + ] + } + } + } + }, + { + "key": "CGCI-HTMCP-CC", + "doc_count": 37, + "genes": { + "doc_count": 3606, + "my_genes": { + "doc_count": 37, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 37 + } + ] + } + } + } + }, + { + "key": "CDDP_EAGLE-1", + "doc_count": 32, + "genes": { + "doc_count": 16980, + "my_genes": { + "doc_count": 32, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 32 + } + ] + } + } + } + }, + { + "key": "TCGA-ACC", + "doc_count": 29, + "genes": { + "doc_count": 283969, + "my_genes": { + "doc_count": 29, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 29 + } + ] + } + } + } + }, + { + "key": "CMI-MBC", + "doc_count": 28, + "genes": { + "doc_count": 3581, + "my_genes": { + "doc_count": 28, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 28 + } + ] + } + } + } + }, + { + "key": "TCGA-THCA", + "doc_count": 28, + "genes": { + "doc_count": 89120, + "my_genes": { + "doc_count": 28, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 28 + } + ] + } + } + } + }, + { + "key": "TCGA-UCS", + "doc_count": 28, + "genes": { + "doc_count": 283673, + "my_genes": { + "doc_count": 28, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 28 + } + ] + } + } + } + }, + { + "key": "TCGA-MESO", + "doc_count": 21, + "genes": { + "doc_count": 137002, + "my_genes": { + "doc_count": 21, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 21 + } + ] + } + } + } + }, + { + "key": "TCGA-PCPG", + "doc_count": 19, + "genes": { + "doc_count": 99444, + "my_genes": { + "doc_count": 19, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 19 + } + ] + } + } + } + }, + { + "key": "TARGET-NBL", + "doc_count": 15, + "genes": { + "doc_count": 829, + "my_genes": { + "doc_count": 15, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 15 + } + ] + } + } + } + }, + { + "key": "TCGA-UVM", + "doc_count": 12, + "genes": { + "doc_count": 68201, + "my_genes": { + "doc_count": 12, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 12 + } + ] + } + } + } + }, + { + "key": "EXCEPTIONAL_RESPONDERS-ER", + "doc_count": 11, + "genes": { + "doc_count": 10617, + "my_genes": { + "doc_count": 11, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 11 + } + ] + } + } + } + }, + { + "key": "TCGA-THYM", + "doc_count": 11, + "genes": { + "doc_count": 59647, + "my_genes": { + "doc_count": 11, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 11 + } + ] + } + } + } + }, + { + "key": "BEATAML1.0-COHORT", + "doc_count": 10, + "genes": { + "doc_count": 279, + "my_genes": { + "doc_count": 10, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 10 + } + ] + } + } + } + }, + { + "key": "TARGET-OS", + "doc_count": 10, + "genes": { + "doc_count": 414, + "my_genes": { + "doc_count": 10, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 10 + } + ] + } + } + } + }, + { + "key": "TCGA-LAML", + "doc_count": 10, + "genes": { + "doc_count": 10175, + "my_genes": { + "doc_count": 10, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 10 + } + ] + } + } + } + }, + { + "key": "TCGA-DLBC", + "doc_count": 9, + "genes": { + "doc_count": 63497, + "my_genes": { + "doc_count": 9, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 9 + } + ] + } + } + } + }, + { + "key": "TCGA-CHOL", + "doc_count": 8, + "genes": { + "doc_count": 52960, + "my_genes": { + "doc_count": 8, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 8 + } + ] + } + } + } + }, + { + "key": "CMI-MPC", + "doc_count": 7, + "genes": { + "doc_count": 365, + "my_genes": { + "doc_count": 7, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 7 + } + ] + } + } + } + }, + { + "key": "CMI-ASC", + "doc_count": 6, + "genes": { + "doc_count": 5745, + "my_genes": { + "doc_count": 6, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 6 + } + ] + } + } + } + }, + { + "key": "TARGET-WT", + "doc_count": 3, + "genes": { + "doc_count": 51, + "my_genes": { + "doc_count": 3, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 3 + } + ] + } + } + } + }, + { + "key": "TARGET-ALL-P3", + "doc_count": 2, + "genes": { + "doc_count": 66, + "my_genes": { + "doc_count": 2, + "gene_id": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, + "buckets": [ + { + "key": "ENSG00000155657", + "doc_count": 2 + } + ] + } + } + } + } + ] + } + } + +``` + +This portion of the output shows TCGA-GBM including 45 cases that have `ssms` in the gene `ENSG00000155657`. + +__Example 2:__ The following demonstrates a use of the `/analysis/top_mutated_genes_by_project` endpoint. This will output the genes that are mutated in the most cases in "TCGA-DLBC" and will count the mutations that have a `HIGH` or `MODERATE` impact on gene function. Note that the `score` field does not represent the number of mutations in a given gene, but a calculation that is used to determine which genes have the greatest number of unique mutations. + +```json +{ + "op":"AND", + "content":[ + { + "op":"in", + "content":{ + "field":"case.project.project_id", + "value":[ + "TCGA-DLBC" + ] + } + }, + { + "op":"in", + "content":{ + "field":"case.ssm.consequence.transcript.annotation.vep_impact", + "value":[ + "HIGH", + "MODERATE" + ] + } + } + ] +} +``` +```Shell +curl "https://api.gdc.cancer.gov/analysis/top_mutated_genes_by_project?fields=gene_id,symbol&filters=%7B%20%20%0A%20%20%20%22op%22%3A%22AND%20%20%20%22content%22%3A%5B%20%20%0A%20%20%20%20%20%20%7B%20%20%0A%20%20%20%20%20%20%20%20%20%22op%22%3A%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%22content%22%3A%7B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%22case.project.project_id%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%5B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22TCGA-DLBC%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%7D%2C%0A%20%20%20%20%20%20%7B%20%20%0A%20%20%20%20%20%20%20%20%20%22op%22%3A%22in%22%2C%0A%20%20%20%20%20%20%20%20%20%22content%22%3A%7B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%22field%22%3A%22case.ssm.consequence.transcript.annotation.vep_impact%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%22value%22%3A%5B%20%20%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22HIGH%22%2C%0A%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%22MODERATE%22%0A%20%20%20%20%20%20%20%20%20%20%20%20%5D%0A%20%20%20%20%20%20%20%20%20%7D%0A%20%20%20%20%20%20%7D%0A%20%20%20%5D%0A%7D%0A&pretty=true" +``` +```Response +{ + "data": { + "hits": [ + { + "symbol": "KMT2D", + "gene_id": "ENSG00000167548", + "_score": 13.0 + }, + { + "symbol": "BTG2", + "gene_id": "ENSG00000159388", + "_score": 13.0 + }, + { + "symbol": "B2M", + "gene_id": "ENSG00000166710", + "_score": 11.0 + }, + { + "symbol": "PIM1", + "gene_id": "ENSG00000137193", + "_score": 10.0 + }, + { + "symbol": "IGHG1", + "gene_id": "ENSG00000211896", + "_score": 10.0 + }, + { + "symbol": "CARD11", + "gene_id": "ENSG00000198286", + "_score": 10.0 + }, + { + "symbol": "H1-4", + "gene_id": "ENSG00000168298", + "_score": 9.0 + }, + { + "symbol": "PCLO", + "gene_id": "ENSG00000186472", + "_score": 9.0 + }, + { + "symbol": "IGHG2", + "gene_id": "ENSG00000211893", + "_score": 9.0 + }, + { + "symbol": "FAT4", + "gene_id": "ENSG00000196159", + "_score": 8.0 + } + ], + "pagination": { + "count": 10, + "total": 3500, + "size": 10, + "from": 0, + "sort": "None", + "page": 1, + "pages": 350 + } + }, + "warnings": {} +} +``` + +__Example 3:__ The `/analysis/top_mutated_cases_by_gene` endpoint will generate information about the cases that are most affected by mutations in a given number of genes. Below, the file count for each category is given for the cases most affected by mutations in these 50 genes. The size of the output is limited to two cases with the `size=2` parameter, but a higher value can be set by the user. + +```Shell +curl "https://api.gdc.cancer.gov/analysis/top_mutated_cases_by_gene?fields=diagnoses.age_at_diagnosis,diagnoses.primary_diagnosis,demographic.gender,demographic.race,demographic.ethnicity,case_id,summary.data_categories.file_count,summary.data_categories.data_category&filters=%7B%22op%22%3A%22and%22%2C%22content%22%3A%5B%7B%22op%22%3A%22%3D%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%22TCGA-DLBC%22%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22genes.gene_id%22%2C%22value%22%3A%5B%22ENSG00000166710%22%2C%22ENSG00000005339%22%2C%22ENSG00000083857%22%2C%22ENSG00000168769%22%2C%22ENSG00000100906%22%2C%22ENSG00000184677%22%2C%22ENSG00000101680%22%2C%22ENSG00000101266%22%2C%22ENSG00000028277%22%2C%22ENSG00000140968%22%2C%22ENSG00000181827%22%2C%22ENSG00000116815%22%2C%22ENSG00000275221%22%2C%22ENSG00000139083%22%2C%22ENSG00000112851%22%2C%22ENSG00000112697%22%2C%22ENSG00000164134%22%2C%22ENSG00000009413%22%2C%22ENSG00000071626%22%2C%22ENSG00000135407%22%2C%22ENSG00000101825%22%2C%22ENSG00000104814%22%2C%22ENSG00000166415%22%2C%22ENSG00000142867%22%2C%22ENSG00000254585%22%2C%22ENSG00000139718%22%2C%22ENSG00000077721%22%2C%22ENSG00000130294%22%2C%22ENSG00000117245%22%2C%22ENSG00000117318%22%2C%22ENSG00000270550%22%2C%22ENSG00000163637%22%2C%22ENSG00000166575%22%2C%22ENSG00000065526%22%2C%22ENSG00000156453%22%2C%22ENSG00000128191%22%2C%22ENSG00000055609%22%2C%22ENSG00000204469%22%2C%22ENSG00000187605%22%2C%22ENSG00000185875%22%2C%22ENSG00000110888%22%2C%22ENSG00000007341%22%2C%22ENSG00000173198%22%2C%22ENSG00000115568%22%2C%22ENSG00000163714%22%2C%22ENSG00000125772%22%2C%22ENSG00000080815%22%2C%22ENSG00000189079%22%2C%22ENSG00000120837%22%2C%22ENSG00000143951%22%5D%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22ssms.consequence.transcript.annotation.vep_impact%22%2C%22value%22%3A%5B%22HIGH%22%5D%7D%7D%5D%7D&pretty=true&size=2" ``` ```Response { - "hits": { - "hits": [], - "total": 14551, - "max_score": 0.0 + "data": { + "hits": [ + { + "summary": { + "data_categories": [ + { + "file_count": 6, + "data_category": "Sequencing Reads" + }, + { + "file_count": 14, + "data_category": "Biospecimen" + }, + { + "file_count": 8, + "data_category": "Copy Number Variation" + }, + { + "file_count": 16, + "data_category": "Simple Nucleotide Variation" + }, + { + "file_count": 4, + "data_category": "Transcriptome Profiling" + }, + { + "file_count": 3, + "data_category": "DNA Methylation" + }, + { + "file_count": 8, + "data_category": "Clinical" + }, + { + "file_count": 4, + "data_category": "Structural Variation" + }, + { + "file_count": 1, + "data_category": "Proteome Profiling" + } + ] + }, + "case_id": "eda9496e-be80-4a13-bf06-89f0cc9e937f", + "diagnoses": [ + { + "age_at_diagnosis": 18691, + "primary_diagnosis": "Malignant lymphoma, large B-cell, diffuse, NOS" + } + ], + "demographic": { + "ethnicity": "hispanic or latino", + "gender": "male", + "race": "white" + }, + "_score": 7.0 + }, + { + "summary": { + "data_categories": [ + { + "file_count": 4, + "data_category": "Sequencing Reads" + }, + { + "file_count": 13, + "data_category": "Biospecimen" + }, + { + "file_count": 8, + "data_category": "Copy Number Variation" + }, + { + "file_count": 16, + "data_category": "Simple Nucleotide Variation" + }, + { + "file_count": 2, + "data_category": "Transcriptome Profiling" + }, + { + "file_count": 3, + "data_category": "DNA Methylation" + }, + { + "file_count": 8, + "data_category": "Clinical" + }, + { + "file_count": 4, + "data_category": "Structural Variation" + } + ] + }, + "case_id": "7a589441-11ef-4158-87e7-3951d86bc2aa", + "diagnoses": [ + { + "age_at_diagnosis": 20812, + "primary_diagnosis": "Malignant lymphoma, large B-cell, diffuse, NOS" + } + ], + "demographic": { + "ethnicity": "not hispanic or latino", + "gender": "female", + "race": "white" + }, + "_score": 4.0 + } + ], + "pagination": { + "count": 2, + "total": 32, + "size": 2, + "from": 0, + "sort": "None", + "page": 1, + "pages": 16 + } }, + "warnings": {} +} +``` + +__Example 4:__ The `/analysis/mutated_cases_count_by_project` endpoint produces counts for the number of cases that have associated `ssm` data in each project. The number of affected cases can be found under `"case_with_ssm": {"doc_count": $case_count}`. + +```Shell +curl "https://api.gdc.cancer.gov/analysis/mutated_cases_count_by_project?size=0&pretty=true" +``` +```Response +{ + "took": 9, + "timed_out": false, "_shards": { - "successful": 9, - "failed": 0, - "total": 9 + "total": 12, + "successful": 12, + "skipped": 0, + "failed": 0 + }, + "hits": { + "total": { + "value": 44451, + "relation": "eq" + }, + "max_score": null, + "hits": [] }, - "took": 4, "aggregations": { "projects": { + "doc_count_error_upper_bound": 0, + "sum_other_doc_count": 0, "buckets": [ { + "key": "FM-AD", + "doc_count": 18004, + "case_summary": { + "doc_count": 54012, + "case_with_ssm": { + "doc_count": 18004 + } + } + }, + { + "key": "TARGET-AML", + "doc_count": 2492, + "case_summary": { + "doc_count": 10780, + "case_with_ssm": { + "doc_count": 22 + } + } + }, + { + "key": "TARGET-ALL-P2", + "doc_count": 1587, + "case_summary": { + "doc_count": 5562, + "case_with_ssm": { + "doc_count": 717 + } + } + }, + { + "key": "MP2PRT-ALL", + "doc_count": 1510, + "case_summary": { + "doc_count": 10472, + "case_with_ssm": { + "doc_count": 1508 + } + } + }, + { + "key": "CPTAC-3", + "doc_count": 1235, + "case_summary": { + "doc_count": 8508, + "case_with_ssm": { + "doc_count": 1218 + } + } + }, + { + "key": "TARGET-NBL", + "doc_count": 1132, + "case_summary": { + "doc_count": 3007, + "case_with_ssm": { + "doc_count": 220 + } + } + }, + { + "key": "TCGA-BRCA", + "doc_count": 1098, + "case_summary": { + "doc_count": 9735, + "case_with_ssm": { + "doc_count": 1098 + } + } + }, + { + "key": "MMRF-COMMPASS", + "doc_count": 995, + "case_summary": { + "doc_count": 3528, + "case_with_ssm": { + "doc_count": 959 + } + } + }, + { + "key": "BEATAML1.0-COHORT", + "doc_count": 826, + "case_summary": { + "doc_count": 2891, + "case_with_ssm": { + "doc_count": 759 + } + } + }, + { + "key": "TARGET-WT", + "doc_count": 652, + "case_summary": { + "doc_count": 3045, + "case_with_ssm": { + "doc_count": 631 + } + } + }, + { + "key": "TCGA-GBM", + "doc_count": 617, + "case_summary": { + "doc_count": 3867, + "case_with_ssm": { + "doc_count": 600 + } + } + }, + { + "key": "TCGA-OV", + "doc_count": 608, + "case_summary": { + "doc_count": 5028, + "case_with_ssm": { + "doc_count": 599 + } + } + }, + { + "key": "TCGA-LUAD", + "doc_count": 585, + "case_summary": { + "doc_count": 4825, + "case_with_ssm": { + "doc_count": 571 + } + } + }, + { + "key": "TCGA-UCEC", + "doc_count": 560, + "case_summary": { + "doc_count": 4559, + "case_with_ssm": { + "doc_count": 559 + } + } + }, + { + "key": "TCGA-KIRC", + "doc_count": 537, + "case_summary": { + "doc_count": 4768, + "case_with_ssm": { + "doc_count": 534 + } + } + }, + { + "key": "TCGA-HNSC", + "doc_count": 528, + "case_summary": { + "doc_count": 4577, + "case_with_ssm": { + "doc_count": 528 + } + } + }, + { + "key": "TCGA-LGG", + "doc_count": 516, + "case_summary": { + "doc_count": 4570, + "case_with_ssm": { + "doc_count": 516 + } + } + }, + { + "key": "TCGA-THCA", + "doc_count": 507, + "case_summary": { + "doc_count": 4442, + "case_with_ssm": { + "doc_count": 507 + } + } + }, + { + "key": "TCGA-LUSC", + "doc_count": 504, "case_summary": { + "doc_count": 4425, "case_with_ssm": { - "doc_count": 216 - }, - "doc_count": 637 - }, - "key": "TARGET-NBL", - "doc_count": 1127 + "doc_count": 504 + } + } }, { + "key": "TCGA-PRAD", + "doc_count": 500, "case_summary": { + "doc_count": 4365, "case_with_ssm": { - "doc_count": 1044 - }, - "doc_count": 7625 - }, - "key": "TCGA-BRCA", - "doc_count": 1098 + "doc_count": 500 + } + } }, { + "key": "NCICCR-DLBCL", + "doc_count": 489, "case_summary": { + "doc_count": 1451, "case_with_ssm": { - "doc_count": 8 - }, - "doc_count": 579 - }, - "key": "TARGET-AML", - "doc_count": 988 + "doc_count": 0 + } + } }, { + "key": "TCGA-SKCM", + "doc_count": 470, "case_summary": { + "doc_count": 4125, "case_with_ssm": { - "doc_count": 34 - }, - "doc_count": 290 - }, - "key": "TARGET-WT", - "doc_count": 652 + "doc_count": 470 + } + } }, { + "key": "TCGA-COAD", + "doc_count": 461, "case_summary": { + "doc_count": 3888, "case_with_ssm": { - "doc_count": 396 - }, - "doc_count": 3197 - }, - "key": "TCGA-GBM", - "doc_count": 617 + "doc_count": 461 + } + } }, { + "key": "TCGA-STAD", + "doc_count": 443, "case_summary": { + "doc_count": 3884, "case_with_ssm": { "doc_count": 443 - }, - "doc_count": 3880 - }, - "key": "TCGA-OV", - "doc_count": 608 + } + } }, { + "key": "REBC-THYR", + "doc_count": 440, "case_summary": { + "doc_count": 2456, "case_with_ssm": { - "doc_count": 569 - }, - "doc_count": 3874 - }, - "key": "TCGA-LUAD", - "doc_count": 585 + "doc_count": 380 + } + } }, { + "key": "TCGA-BLCA", + "doc_count": 412, "case_summary": { + "doc_count": 3645, "case_with_ssm": { - "doc_count": 542 - }, - "doc_count": 3874 - }, - "key": "TCGA-UCEC", - "doc_count": 560 + "doc_count": 412 + } + } }, { + "key": "TARGET-OS", + "doc_count": 383, "case_summary": { + "doc_count": 1276, "case_with_ssm": { - "doc_count": 339 - }, - "doc_count": 3547 - }, - "key": "TCGA-KIRC", - "doc_count": 537 + "doc_count": 97 + } + } }, { + "key": "TCGA-LIHC", + "doc_count": 377, "case_summary": { + "doc_count": 3204, "case_with_ssm": { - "doc_count": 510 - }, - "doc_count": 3671 - }, - "key": "TCGA-HNSC", - "doc_count": 528 + "doc_count": 377 + } + } }, { + "key": "CPTAC-2", + "doc_count": 342, "case_summary": { + "doc_count": 1349, "case_with_ssm": { - "doc_count": 513 - }, - "doc_count": 3606 - }, - "key": "TCGA-LGG", - "doc_count": 516 + "doc_count": 328 + } + } }, { + "key": "TRIO-CRU", + "doc_count": 339, "case_summary": { + "doc_count": 339, "case_with_ssm": { - "doc_count": 496 - }, - "doc_count": 3536 - }, - "key": "TCGA-THCA", - "doc_count": 507 + "doc_count": 0 + } + } }, { + "key": "CGCI-BLGSP", + "doc_count": 324, "case_summary": { + "doc_count": 2076, "case_with_ssm": { - "doc_count": 497 - }, - "doc_count": 3520 - }, - "key": "TCGA-LUSC", - "doc_count": 504 + "doc_count": 262 + } + } }, { + "key": "TCGA-CESC", + "doc_count": 307, "case_summary": { + "doc_count": 2623, "case_with_ssm": { - "doc_count": 498 - }, - "doc_count": 3490 - }, - "key": "TCGA-PRAD", - "doc_count": 500 + "doc_count": 306 + } + } }, { + "key": "TCGA-KIRP", + "doc_count": 291, "case_summary": { + "doc_count": 2568, "case_with_ssm": { - "doc_count": 470 - }, - "doc_count": 3289 - }, - "key": "TCGA-SKCM", - "doc_count": 470 + "doc_count": 291 + } + } }, { + "key": "HCMI-CMDC", + "doc_count": 278, "case_summary": { + "doc_count": 2420, "case_with_ssm": { - "doc_count": 433 - }, - "doc_count": 3188 - }, - "key": "TCGA-COAD", - "doc_count": 461 + "doc_count": 277 + } + } + }, + { + "key": "TCGA-TGCT", + "doc_count": 263, + "case_summary": { + "doc_count": 2124, + "case_with_ssm": { + "doc_count": 262 + } + } + }, + { + "key": "TCGA-SARC", + "doc_count": 261, + "case_summary": { + "doc_count": 2309, + "case_with_ssm": { + "doc_count": 261 + } + } + }, + { + "key": "CGCI-HTMCP-CC", + "doc_count": 212, + "case_summary": { + "doc_count": 1452, + "case_with_ssm": { + "doc_count": 206 + } + } + }, + { + "key": "CMI-MBC", + "doc_count": 200, + "case_summary": { + "doc_count": 653, + "case_with_ssm": { + "doc_count": 174 + } + } + }, + { + "key": "TCGA-LAML", + "doc_count": 200, + "case_summary": { + "doc_count": 1533, + "case_with_ssm": { + "doc_count": 200 + } + } + }, + { + "key": "TARGET-ALL-P3", + "doc_count": 191, + "case_summary": { + "doc_count": 782, + "case_with_ssm": { + "doc_count": 86 + } + } + }, + { + "key": "TCGA-ESCA", + "doc_count": 185, + "case_summary": { + "doc_count": 1623, + "case_with_ssm": { + "doc_count": 185 + } + } + }, + { + "key": "TCGA-PAAD", + "doc_count": 185, + "case_summary": { + "doc_count": 1720, + "case_with_ssm": { + "doc_count": 185 + } + } + }, + { + "key": "TCGA-PCPG", + "doc_count": 179, + "case_summary": { + "doc_count": 1512, + "case_with_ssm": { + "doc_count": 179 + } + } + }, + { + "key": "OHSU-CNL", + "doc_count": 176, + "case_summary": { + "doc_count": 494, + "case_with_ssm": { + "doc_count": 158 + } + } + }, + { + "key": "TCGA-READ", + "doc_count": 172, + "case_summary": { + "doc_count": 1414, + "case_with_ssm": { + "doc_count": 171 + } + } + }, + { + "key": "TCGA-THYM", + "doc_count": 124, + "case_summary": { + "doc_count": 1078, + "case_with_ssm": { + "doc_count": 124 + } + } + }, + { + "key": "TCGA-KICH", + "doc_count": 113, + "case_summary": { + "doc_count": 705, + "case_with_ssm": { + "doc_count": 66 + } + } + }, + { + "key": "WCDT-MCRPC", + "doc_count": 101, + "case_summary": { + "doc_count": 299, + "case_with_ssm": { + "doc_count": 0 + } + } + }, + { + "key": "TCGA-ACC", + "doc_count": 92, + "case_summary": { + "doc_count": 809, + "case_with_ssm": { + "doc_count": 92 + } + } + }, + { + "key": "APOLLO-LUAD", + "doc_count": 87, + "case_summary": { + "doc_count": 510, + "case_with_ssm": { + "doc_count": 83 + } + } + }, + { + "key": "TCGA-MESO", + "doc_count": 87, + "case_summary": { + "doc_count": 813, + "case_with_ssm": { + "doc_count": 87 + } + } + }, + { + "key": "EXCEPTIONAL_RESPONDERS-ER", + "doc_count": 84, + "case_summary": { + "doc_count": 412, + "case_with_ssm": { + "doc_count": 20 + } + } + }, + { + "key": "TCGA-UVM", + "doc_count": 80, + "case_summary": { + "doc_count": 700, + "case_with_ssm": { + "doc_count": 80 + } + } + }, + { + "key": "CGCI-HTMCP-DLBCL", + "doc_count": 70, + "case_summary": { + "doc_count": 465, + "case_with_ssm": { + "doc_count": 50 + } + } + }, + { + "key": "ORGANOID-PANCREATIC", + "doc_count": 70, + "case_summary": { + "doc_count": 225, + "case_with_ssm": { + "doc_count": 57 + } + } + }, + { + "key": "TARGET-RT", + "doc_count": 69, + "case_summary": { + "doc_count": 404, + "case_with_ssm": { + "doc_count": 0 + } + } }, { + "key": "CMI-MPC", + "doc_count": 63, "case_summary": { + "doc_count": 199, "case_with_ssm": { - "doc_count": 441 - }, - "doc_count": 3095 - }, - "key": "TCGA-STAD", - "doc_count": 443 + "doc_count": 60 + } + } }, { + "key": "MATCH-I", + "doc_count": 60, "case_summary": { + "doc_count": 345, "case_with_ssm": { - "doc_count": 412 - }, - "doc_count": 2884 - }, - "key": "TCGA-BLCA", - "doc_count": 412 + "doc_count": 57 + } + } }, { + "key": "TCGA-DLBC", + "doc_count": 58, "case_summary": { + "doc_count": 441, "case_with_ssm": { - "doc_count": 0 - }, - "doc_count": 0 - }, - "key": "TARGET-OS", - "doc_count": 381 + "doc_count": 50 + } + } }, { + "key": "TCGA-UCS", + "doc_count": 57, "case_summary": { + "doc_count": 504, "case_with_ssm": { - "doc_count": 375 - }, - "doc_count": 2635 - }, - "key": "TCGA-LIHC", - "doc_count": 377 + "doc_count": 57 + } + } }, { + "key": "BEATAML1.0-CRENOLANIB", + "doc_count": 56, "case_summary": { + "doc_count": 107, "case_with_ssm": { - "doc_count": 305 - }, - "doc_count": 2142 - }, - "key": "TCGA-CESC", - "doc_count": 307 + "doc_count": 51 + } + } }, { + "key": "MP2PRT-WT", + "doc_count": 52, "case_summary": { + "doc_count": 361, "case_with_ssm": { - "doc_count": 288 - }, - "doc_count": 2033 - }, - "key": "TCGA-KIRP", - "doc_count": 291 + "doc_count": 51 + } + } }, { + "key": "TCGA-CHOL", + "doc_count": 51, "case_summary": { + "doc_count": 378, "case_with_ssm": { - "doc_count": 255 - }, - "doc_count": 1821 - }, - "key": "TCGA-SARC", - "doc_count": 261 + "doc_count": 51 + } + } }, { + "key": "CDDP_EAGLE-1", + "doc_count": 50, "case_summary": { + "doc_count": 384, "case_with_ssm": { - "doc_count": 149 - }, - "doc_count": 1192 - }, - "key": "TCGA-LAML", - "doc_count": 200 + "doc_count": 50 + } + } }, { + "key": "CTSP-DLBCL1", + "doc_count": 45, "case_summary": { + "doc_count": 201, "case_with_ssm": { - "doc_count": 184 - }, - "doc_count": 1293 - }, - "key": "TCGA-ESCA", - "doc_count": 185 + "doc_count": 0 + } + } }, { + "key": "MATCH-W", + "doc_count": 45, "case_summary": { + "doc_count": 265, "case_with_ssm": { - "doc_count": 183 - }, - "doc_count": 1285 - }, - "key": "TCGA-PAAD", - "doc_count": 185 + "doc_count": 44 + } + } }, { + "key": "MATCH-Z1A", + "doc_count": 45, "case_summary": { + "doc_count": 262, "case_with_ssm": { - "doc_count": 179 - }, - "doc_count": 1253 - }, - "key": "TCGA-PCPG", - "doc_count": 179 + "doc_count": 43 + } + } }, { + "key": "CGCI-HTMCP-LC", + "doc_count": 39, "case_summary": { + "doc_count": 292, "case_with_ssm": { - "doc_count": 158 - }, - "doc_count": 1169 - }, - "key": "TCGA-READ", - "doc_count": 172 + "doc_count": 34 + } + } }, { + "key": "CMI-ASC", + "doc_count": 36, "case_summary": { + "doc_count": 124, "case_with_ssm": { - "doc_count": 150 - }, - "doc_count": 1018 - }, - "key": "TCGA-TGCT", - "doc_count": 150 + "doc_count": 36 + } + } }, { + "key": "MATCH-Z1D", + "doc_count": 36, "case_summary": { + "doc_count": 212, "case_with_ssm": { - "doc_count": 123 - }, - "doc_count": 867 - }, - "key": "TCGA-THYM", - "doc_count": 124 + "doc_count": 34 + } + } }, { + "key": "MATCH-Q", + "doc_count": 35, "case_summary": { + "doc_count": 203, "case_with_ssm": { - "doc_count": 66 - }, - "doc_count": 556 - }, - "key": "TCGA-KICH", - "doc_count": 113 + "doc_count": 34 + } + } }, { + "key": "MATCH-B", + "doc_count": 33, "case_summary": { + "doc_count": 187, "case_with_ssm": { - "doc_count": 92 - }, - "doc_count": 620 - }, - "key": "TCGA-ACC", - "doc_count": 92 + "doc_count": 32 + } + } }, { + "key": "MATCH-Y", + "doc_count": 31, "case_summary": { + "doc_count": 181, "case_with_ssm": { - "doc_count": 83 - }, - "doc_count": 605 - }, - "key": "TCGA-MESO", - "doc_count": 87 + "doc_count": 30 + } + } }, { + "key": "TARGET-ALL-P1", + "doc_count": 24, "case_summary": { + "doc_count": 86, "case_with_ssm": { - "doc_count": 80 - }, - "doc_count": 560 - }, - "key": "TCGA-UVM", - "doc_count": 80 + "doc_count": 0 + } + } }, { + "key": "MATCH-U", + "doc_count": 23, "case_summary": { + "doc_count": 137, "case_with_ssm": { - "doc_count": 0 - }, - "doc_count": 163 - }, - "key": "TARGET-RT", - "doc_count": 75 + "doc_count": 22 + } + } }, { + "key": "MATCH-H", + "doc_count": 21, "case_summary": { + "doc_count": 122, "case_with_ssm": { - "doc_count": 48 - }, - "doc_count": 346 - }, - "key": "TCGA-DLBC", - "doc_count": 58 + "doc_count": 21 + } + } }, { + "key": "MATCH-N", + "doc_count": 21, "case_summary": { + "doc_count": 120, "case_with_ssm": { - "doc_count": 57 - }, - "doc_count": 399 - }, - "key": "TCGA-UCS", - "doc_count": 57 + "doc_count": 21 + } + } }, { + "key": "TARGET-CCSK", + "doc_count": 13, "case_summary": { + "doc_count": 100, "case_with_ssm": { - "doc_count": 51 - }, - "doc_count": 306 - }, - "key": "TCGA-CHOL", - "doc_count": 51 + "doc_count": 0 + } + } }, { + "key": "VAREPOP-APOLLO", + "doc_count": 7, "case_summary": { + "doc_count": 14, "case_with_ssm": { - "doc_count": 0 - }, - "doc_count": 13 - }, - "key": "TARGET-CCSK", - "doc_count": 13 + "doc_count": 7 + } + } } - ], - "sum_other_doc_count": 0, - "doc_count_error_upper_bound": 0 + ] } - }, - "timed_out": false + } } ``` + ### Survival Analysis Endpoint -[Survival plots](/Data_Portal/Projects/#Survival-Analysis) are generated for different subsets of data, based on variants or projects, in the GDC Data Portal. The `/analysis/survival` endpoint can be used to programmatically retrieve the raw data used to generate these plots and apply different filters. Note that the `fields` and `format` parameters cannot be modified. +[Survival plots](/Data_Portal/Users_Guide/Exploration/#survival-analysis) are generated for different subsets of data, based on variants or projects, in the GDC Data Portal. The `/analysis/survival` endpoint can be used to programmatically retrieve the raw data used to generate these plots and apply different filters. Note that the `fields` and `format` parameters cannot be modified. __Example 1:__ A user wants to download data to generate a survival plot for cases from the project TCGA-DLBC. @@ -946,298 +2704,392 @@ curl "https://api.gdc.cancer.gov/analysis/survival?filters=%5B%7B%22op%22%3A%22% ``` ```Response { - "overallStats": {}, "results": [ { + "meta": { + "id": 139834474037000 + }, "donors": [ { + "time": 1.0, + "censored": true, "survivalEstimate": 1, "id": "dc87a809-95de-4eb7-a1c2-2650475f2d7e", - "censored": true, - "time": 1 + "submitter_id": "TCGA-RQ-A6JB", + "project_id": "TCGA-DLBC" }, { + "time": 17.0, + "censored": true, "survivalEstimate": 1, "id": "4dd86ebd-ef16-4b2b-9ea0-5d1d7afef257", - "censored": true, - "time": 17 + "submitter_id": "TCGA-RQ-AAAT", + "project_id": "TCGA-DLBC" }, { + "time": 58, + "censored": false, "survivalEstimate": 1, "id": "0bf573ac-cd1e-42d8-90cf-b30d7b08679c", - "censored": false, - "time": 58 + "submitter_id": "TCGA-FA-A6HN", + "project_id": "TCGA-DLBC" }, { + "time": 126.0, + "censored": true, "survivalEstimate": 0.9777777777777777, "id": "f978cb0f-d319-4c01-b4c5-23ae1403a106", - "censored": true, - "time": 126 + "submitter_id": "TCGA-FF-8047", + "project_id": "TCGA-DLBC" }, { - "survivalEstimate": 0.9777777777777777, - "id": "a43e5f0e-a21f-48d8-97e0-084d413680b7", + "time": 132.0, "censored": true, - "time": 132 - }, - { "survivalEstimate": 0.9777777777777777, "id": "1843c82e-7a35-474f-9f79-c0a9af9aa09c", + "submitter_id": "TCGA-FA-A4BB", + "project_id": "TCGA-DLBC" + }, + { + "time": 132.0, "censored": true, - "time": 132 + "survivalEstimate": 0.9777777777777777, + "id": "a43e5f0e-a21f-48d8-97e0-084d413680b7", + "submitter_id": "TCGA-FA-8693", + "project_id": "TCGA-DLBC" }, { + "time": 248, + "censored": false, "survivalEstimate": 0.9777777777777777, "id": "0030a28c-81aa-44b0-8be0-b35e1dcbf98c", - "censored": false, - "time": 248 + "submitter_id": "TCGA-FA-A7Q1", + "project_id": "TCGA-DLBC" }, { + "time": 298.0, + "censored": true, "survivalEstimate": 0.9539295392953929, "id": "f553f1a9-ecf2-4783-a609-6adca7c4c597", - "censored": true, - "time": 298 + "submitter_id": "TCGA-FF-A7CQ", + "project_id": "TCGA-DLBC" }, { + "time": 313, + "censored": false, "survivalEstimate": 0.9539295392953929, "id": "f784bc3a-751b-4025-aab2-0af2f6f24266", - "censored": false, - "time": 313 + "submitter_id": "TCGA-FF-A7CR", + "project_id": "TCGA-DLBC" }, { + "time": 385.0, + "censored": true, "survivalEstimate": 0.929469807518588, "id": "29e3d122-15a1-4235-a356-b1a9f94ceb39", - "censored": true, - "time": 385 + "submitter_id": "TCGA-FF-A7CX", + "project_id": "TCGA-DLBC" }, { + "time": 391, + "censored": false, "survivalEstimate": 0.929469807518588, "id": "0e251c03-bf86-4ed8-b45d-3cbc97160502", - "censored": false, - "time": 391 + "submitter_id": "TCGA-GS-A9U4", + "project_id": "TCGA-DLBC" }, { + "time": 427.0, + "censored": true, "survivalEstimate": 0.9043490019099776, "id": "e6365b38-bc44-400c-b4aa-18ce8ff5bfce", - "censored": true, - "time": 427 + "submitter_id": "TCGA-FA-A82F", + "project_id": "TCGA-DLBC" }, { + "time": 553.0, + "censored": true, "survivalEstimate": 0.9043490019099776, "id": "b56bdbdb-43af-4a03-a072-54dd22d7550c", - "censored": true, - "time": 553 + "submitter_id": "TCGA-FA-A86F", + "project_id": "TCGA-DLBC" }, { + "time": 595, + "censored": false, "survivalEstimate": 0.9043490019099776, "id": "31bbad4e-3789-42ec-9faa-1cb86970f723", - "censored": false, - "time": 595 + "submitter_id": "TCGA-G8-6907", + "project_id": "TCGA-DLBC" }, { + "time": 679.0, + "censored": true, "survivalEstimate": 0.8777505018538018, "id": "0e9fcccc-0630-408d-a121-2c6413824cb7", - "censored": true, - "time": 679 + "submitter_id": "TCGA-FF-8062", + "project_id": "TCGA-DLBC" }, { + "time": 708, + "censored": false, "survivalEstimate": 0.8777505018538018, "id": "a5b188f0-a6d3-4d4a-b04f-36d47ec05338", - "censored": false, - "time": 708 + "submitter_id": "TCGA-FA-A4XK", + "project_id": "TCGA-DLBC" }, { + "time": 719.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "ed746cb9-0f2f-48ce-923a-3a9f9f00b331", - "censored": true, - "time": 719 + "submitter_id": "TCGA-FA-A7DS", + "project_id": "TCGA-DLBC" }, { + "time": 730.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "c85f340e-584b-4f3b-b6a5-540491fc8ad2", - "censored": true, - "time": 730 + "submitter_id": "TCGA-GS-A9TV", + "project_id": "TCGA-DLBC" }, { + "time": 749.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "69f23725-adca-48ac-9b33-80a7aae24cfe", - "censored": true, - "time": 749 + "submitter_id": "TCGA-FA-A6HO", + "project_id": "TCGA-DLBC" }, { + "time": 751.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "67325322-483f-443f-9ffa-2a20d108a2fb", - "censored": true, - "time": 751 + "submitter_id": "TCGA-FF-8046", + "project_id": "TCGA-DLBC" }, { + "time": 765.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "eda9496e-be80-4a13-bf06-89f0cc9e937f", - "censored": true, - "time": 765 + "submitter_id": "TCGA-GS-A9TZ", + "project_id": "TCGA-DLBC" }, { + "time": 788.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "25ff86af-beb4-480c-b706-f3fe0306f7cf", - "censored": true, - "time": 788 + "submitter_id": "TCGA-RQ-A68N", + "project_id": "TCGA-DLBC" }, { + "time": 791.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "1d0db5d7-39ca-466d-96b3-0d278c5ea768", - "censored": true, - "time": 791 + "submitter_id": "TCGA-FF-A7CW", + "project_id": "TCGA-DLBC" }, { + "time": 832.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "c8cde9ea-89e9-4ee8-8a46-417a48f6d3ab", - "censored": true, - "time": 832 + "submitter_id": "TCGA-FF-8061", + "project_id": "TCGA-DLBC" }, { + "time": 946.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "f0a326d2-1f3e-4a5d-bca8-32aaccc52338", - "censored": true, - "time": 946 + "submitter_id": "TCGA-FF-8042", + "project_id": "TCGA-DLBC" }, { + "time": 965.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "a8e2df1e-4042-42af-9231-3a00e83489f0", - "censored": true, - "time": 965 + "submitter_id": "TCGA-FF-8043", + "project_id": "TCGA-DLBC" }, { + "time": 972.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "e56e4d9c-052e-4ec6-a81b-dbd53e9c8ffe", - "censored": true, - "time": 972 + "submitter_id": "TCGA-FM-8000", + "project_id": "TCGA-DLBC" }, { + "time": 982.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "45b0cf9f-a879-417f-8f39-7770552252c0", - "censored": true, - "time": 982 + "submitter_id": "TCGA-GS-A9TQ", + "project_id": "TCGA-DLBC" }, { + "time": 1081.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "1f971af1-6772-4fe6-8d35-bbe527a037fe", - "censored": true, - "time": 1081 + "submitter_id": "TCGA-FF-8041", + "project_id": "TCGA-DLBC" }, { + "time": 1163.0, + "censored": true, "survivalEstimate": 0.8503207986708705, "id": "33365d22-cb83-4d8e-a2d1-06b675f75f6e", - "censored": true, - "time": 1163 + "submitter_id": "TCGA-GS-A9TT", + "project_id": "TCGA-DLBC" }, { + "time": 1252, + "censored": false, "survivalEstimate": 0.8503207986708705, "id": "6a21c948-cd85-4150-8c01-83017d7dc1ed", - "censored": false, - "time": 1252 + "submitter_id": "TCGA-G8-6324", + "project_id": "TCGA-DLBC" }, { + "time": 1299.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "f855dad1-6ffc-493e-ba6c-970874bc9210", - "censored": true, - "time": 1299 + "submitter_id": "TCGA-GR-A4D5", + "project_id": "TCGA-DLBC" }, { + "time": 1334.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "c1c06604-5ae2-4a53-b9c0-eb210d38e3f0", - "censored": true, - "time": 1334 + "submitter_id": "TCGA-GR-A4D6", + "project_id": "TCGA-DLBC" }, { + "time": 1373.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "58e66976-4507-4552-ac53-83a49a142dde", - "censored": true, - "time": 1373 + "submitter_id": "TCGA-GS-A9TX", + "project_id": "TCGA-DLBC" }, { + "time": 1581.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "ea54dbad-1b23-41cc-9378-d4002a8fca51", - "censored": true, - "time": 1581 + "submitter_id": "TCGA-G8-6325", + "project_id": "TCGA-DLBC" }, { + "time": 1581.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "d7df78b5-24f1-4ff4-bd9b-f0e6bec8289a", - "censored": true, - "time": 1581 + "submitter_id": "TCGA-GR-A4D4", + "project_id": "TCGA-DLBC" }, { + "time": 1617.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "29aff186-c321-4ff9-b81b-105e27e620ff", - "censored": true, - "time": 1617 + "submitter_id": "TCGA-GS-A9TW", + "project_id": "TCGA-DLBC" }, { + "time": 1739.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "5eff68ff-f6c3-40c9-9fc8-00e684a7b712", - "censored": true, - "time": 1739 + "submitter_id": "TCGA-GR-A4D9", + "project_id": "TCGA-DLBC" }, { + "time": 2131.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "f8cf647b-1447-4ac3-8c43-bef07765cabf", - "censored": true, - "time": 2131 + "submitter_id": "TCGA-G8-6326", + "project_id": "TCGA-DLBC" }, { - "survivalEstimate": 0.8003019281608192, - "id": "c3d662ee-48d0-454a-bb0c-77d3338d3747", + "time": 2616.0, "censored": true, - "time": 2983 - }, - { "survivalEstimate": 0.8003019281608192, "id": "6e9437f0-a4ed-475c-ab0e-bf1431c70a90", + "submitter_id": "TCGA-GS-A9TY", + "project_id": "TCGA-DLBC" + }, + { + "time": 2983.0, "censored": true, - "time": 3333 + "survivalEstimate": 0.8003019281608192, + "id": "c3d662ee-48d0-454a-bb0c-77d3338d3747", + "submitter_id": "TCGA-GR-7353", + "project_id": "TCGA-DLBC" }, { + "time": 3394.0, + "censored": true, "survivalEstimate": 0.8003019281608192, "id": "fdecb74f-ac4e-46b1-b23a-5f7fde96ef9f", - "censored": true, - "time": 3394 + "submitter_id": "TCGA-GS-A9U3", + "project_id": "TCGA-DLBC" }, { + "time": 3553, + "censored": false, "survivalEstimate": 0.8003019281608192, "id": "a468e725-ad4b-411d-ac5c-2eacc68ec580", - "censored": false, - "time": 3553 + "submitter_id": "TCGA-G8-6909", + "project_id": "TCGA-DLBC" }, { + "time": 3897.0, + "censored": true, "survivalEstimate": 0.6402415425286554, "id": "1ea575f1-f731-408b-a629-f5f4abab569e", - "censored": true, - "time": 3897 + "submitter_id": "TCGA-GS-A9TU", + "project_id": "TCGA-DLBC" }, { + "time": 4578.0, + "censored": true, "survivalEstimate": 0.6402415425286554, "id": "7a589441-11ef-4158-87e7-3951d86bc2aa", - "censored": true, - "time": 4578 + "submitter_id": "TCGA-GR-7351", + "project_id": "TCGA-DLBC" }, { + "time": 5980.0, + "censored": true, "survivalEstimate": 0.6402415425286554, "id": "3622cf29-600f-4410-84d4-a9afeb41c475", - "censored": true, - "time": 5980 + "submitter_id": "TCGA-G8-6914", + "project_id": "TCGA-DLBC" }, { + "time": 6425, + "censored": false, "survivalEstimate": 0.6402415425286554, "id": "3f5a897d-1eaa-4d4c-8324-27ac07c90927", - "censored": false, - "time": 6425 + "submitter_id": "TCGA-G8-6906", + "project_id": "TCGA-DLBC" } - ], - "meta": { - "id": 140429063094496 - } + ] } - ] + ], + "overallStats": {} } ``` diff --git a/docs/API/Users_Guide/Downloading_Files.md b/docs/API/Users_Guide/Downloading_Files.md index 975902ed2..997296ed3 100644 --- a/docs/API/Users_Guide/Downloading_Files.md +++ b/docs/API/Users_Guide/Downloading_Files.md @@ -2,9 +2,7 @@ The GDC API implements file download functionality using `data` and `manifest` endpoints. The `data` endpoint allows users to download files stored in the GDC by specifying file UUID(s). The `manifest` endpoint generates a download manifest file that can be used with the GDC Data Transfer Tool to transfer large volumes of data. -**Note:** Downloading controlled access data requires the use of an authentication token. See [Getting Started: Authentication](Getting_Started.md#authentication) for details. - -**Note:** Requests to download data from the GDC Legacy Archive may be directed to `legacy/data` or `data`. See [Getting Started: Legacy Archive](Getting_Started.md#gdc-legacy-archive) for details. +>**Note:** Downloading controlled access data requires the use of an authentication token. See [Getting Started: Authentication](Getting_Started.md#authentication) for details. ## Data endpoint @@ -24,25 +22,25 @@ curl --remote-name --remote-header-name 'https://api.gdc.cancer.gov/data/5b2974a % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 6111k 100 6111k 0 0 414k 0 0:00:14 0:00:14 --:--:-- 412k -curl: Saved to filename '14-3-3_beta-R-V_GBL1112940.tif' + ``` ### Related Files If the `related_files=true` parameter is specified, the following related files, if available, will be included in the download package by the GDC API: * BAM index files (BAI files) -* Metadata files (such as SRA XML or MAGE-TAB files) +* VCF index files (TBI files) -For example, this request will download a legacy copy number segmentation file and its associated MAGE-TAB metadata file: +For example, this request will download a BAM file and its associated BAI file: ```shell -curl --remote-name --remote-header-name 'https://api.gdc.cancer.gov/data/7efc039a-fde3-4bc1-9433-2fc6b5e3ffa5?related_files=true' +curl --remote-name --remote-header-name -H "x-auth-token: $token" "https://api.gdc.cancer.gov/data/f587ef82-acbe-44f9-ad5a-6207e148f61f?related_files=true" ``` ```Output % Total % Received % Xferd Average Speed Time Time Time Current - Dload Upload Total Spent Left Speed -100 65353 0 65353 0 0 65353 0 --:--:-- --:--:-- --:--:-- 102k -curl: Saved to filename 'gdc_download_20180830_131817.826097.tar.gz' + Dload Upload Total Spent Left Speed +100 63.4M 0 63.4M 0 0 7541k 0 --:--:-- 0:00:08 --:--:-- 9.9M + ``` @@ -57,10 +55,10 @@ curl --remote-name --remote-header-name 'https://api.gdc.cancer.gov/data/e322802 % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 287k 0 287k 0 0 30131 0 --:--:-- 0:00:09 --:--:-- 42759 -curl: Saved to filename 'gdc_download_064d1aa8cc8cbab33e93979bebbf7d6af2d6a802.tar.gz' + ``` -**Note:** This method supports downloading a limited number of files at one time. To download a large number of files, please use [POST](#downloading-multiple-files-using-post). +>**Note:** This method supports downloading a limited number of files at one time. To download a large number of files, please use [POST](#downloading-multiple-files-using-post). #### Downloading an Uncompressed Group of Files @@ -83,19 +81,18 @@ The payload is a string in the following format: where UUID# corresponds to the UUIDs of the files to be downloaded. -In this example we use `curl` to download a set of files from the GDC Legacy Archive. The payload is stored in a plain text file named `Payload`; `curl` includes the `Content-Type: application/x-www-form-urlencoded` header by default. +In this example we use `curl` to download a set of files from the GDC Data Portal. The payload is stored in a plain text file named `Payload`; `curl` includes the `Content-Type: application/x-www-form-urlencoded` header by default. ```Payload -ids=556e5e3f-0ab9-4b6c-aa62-c42f6a6cf20c&ids=e0de63e2-02f3-4309-9b24-69f4c24e85fc&ids=f1a06178-2ec2-4b06-83f3-3aedac332cfe&ids=11a8aca0-c8e6-4ff8-8ab6-fe18a1b8ba82&ids=69a69c84-00de-45ff-b397-fd2b6713ed4f&ids=9ec48233-395d-401e-b205-951c971f8dd4&ids=93129547-378c-4b69-b858-532abfff678e&ids=8d4277e9-a472-4590-886d-24dc2538ea65&ids=6733b412-56da-4f1c-a12b-ff804cb656d7&ids=a72eec98-c5e0-4866-8953-765780acb6c1&ids=e77b2294-1bdd-4fba-928a-d81d2622312f&ids=965e01fc-318e-4c02-a801-d6fad60bfae4&ids=21ad5409-fe0b-4728-97e4-15520b9fc287&ids=1a777521-277c-4aeb-baf1-66871a7c2d2a&ids=c13a3449-9e0d-45a9-bcc0-518f55e45c8a&ids=5f2d329b-d59d-4112-b490-5114b830e34d&ids=bb966617-6c1f-4bb0-a1ed-ceb37ecade67&ids=05d11519-2b33-4742-aa87-3934632f2f2b&ids=39bfafe2-9628-434e-bd72-148051a47477&ids=481bea69-3cd5-45f3-8a52-2d4cc8fc8df7&ids=f95e407b-de69-416c-920c-6be8c9414862&ids=75940293-8fa6-47f9-ad5d-155b61933fdc&ids=e8e84ccf-f8a8-4551-9257-ef731d02116f&ids=e4991159-f088-4a2a-88b7-38d6ac47c6bc +ids=59eb3fc5-9172-4828-8dec-0d9988073103&ids=869b7d7c-ff35-482a-aa8d-1a8675c161d3&ids=b8ffff40-aa0e-4534-b05f-9311f16c2f6b&ids=51e14969-30a7-42d9-8168-4a5ea422ca4a&ids=adcfc856-990b-40fc-8f1e-67dfc2343fb7&ids=7f1e9aee-eb4e-4c79-8626-b603c9be124d&ids=62a8feb5-c660-4261-bcd6-67fbb79bb422 ``` ```Shell curl --remote-name --remote-header-name --request POST 'https://api.gdc.cancer.gov/data' --data @Payload ``` ```Output % Total % Received % Xferd Average Speed Time Time Time Current - Dload Upload Total Spent Left Speed -100 2563k 0 2562k 100 983 854k 327 0:00:03 0:00:03 --:--:-- 776k -curl: Saved to filename 'gdc_download_20180830_132402.379282.tar.gz' + Dload Upload Total Spent Left Speed +100 6804k 0 6804k 100 286 245k 10 0:00:28 0:00:27 0:00:01 357k ``` #### POST request with JSON payload @@ -116,36 +113,16 @@ The payload is a string in the following format: where UUID# corresponds to the UUIDs of the files to be downloaded. -In this example we use `curl` to download a set of files from the GDC Legacy Archive; the payload is stored in a plain text file named `Payload`. +In this example we use `curl` to download a set of files from the GDC Portal; the payload is stored in a plain text file named `Payload`. ```Payload { "ids":[ - "556e5e3f-0ab9-4b6c-aa62-c42f6a6cf20c", - "e0de63e2-02f3-4309-9b24-69f4c24e85fc", - "f1a06178-2ec2-4b06-83f3-3aedac332cfe", - "11a8aca0-c8e6-4ff8-8ab6-fe18a1b8ba82", - "69a69c84-00de-45ff-b397-fd2b6713ed4f", - "9ec48233-395d-401e-b205-951c971f8dd4", - "93129547-378c-4b69-b858-532abfff678e", - "8d4277e9-a472-4590-886d-24dc2538ea65", - "6733b412-56da-4f1c-a12b-ff804cb656d7", - "a72eec98-c5e0-4866-8953-765780acb6c1", - "e77b2294-1bdd-4fba-928a-d81d2622312f", - "965e01fc-318e-4c02-a801-d6fad60bfae4", - "21ad5409-fe0b-4728-97e4-15520b9fc287", - "1a777521-277c-4aeb-baf1-66871a7c2d2a", - "c13a3449-9e0d-45a9-bcc0-518f55e45c8a", - "5f2d329b-d59d-4112-b490-5114b830e34d", - "bb966617-6c1f-4bb0-a1ed-ceb37ecade67", - "05d11519-2b33-4742-aa87-3934632f2f2b", - "39bfafe2-9628-434e-bd72-148051a47477", - "481bea69-3cd5-45f3-8a52-2d4cc8fc8df7", - "f95e407b-de69-416c-920c-6be8c9414862", - "75940293-8fa6-47f9-ad5d-155b61933fdc", - "e8e84ccf-f8a8-4551-9257-ef731d02116f", - "e4991159-f088-4a2a-88b7-38d6ac47c6bc" + "0451fc55-33ef-4151-a68c-cac59be716dc", + "0cc3d450-2c60-4cb0-a073-d92dc979fa5e", + "0de9bc40-3ef8-4fe7-b7d6-80a9339b0bf8", + "0f8d8202-a1ca-4ea1-98b2-c20a6b08479a" ] } ``` @@ -153,10 +130,9 @@ In this example we use `curl` to download a set of files from the GDC Legacy Arc curl --remote-name --remote-header-name --request POST --header 'Content-Type: application/json' --data @request.txt 'https://api.gdc.cancer.gov/data' ``` ```Output - % Total % Received % Xferd Average Speed Time Time Time Current - Dload Upload Total Spent Left Speed -100 2562k 0 2561k 100 1145 788k 352 0:00:03 0:00:03 --:--:-- 788k -curl: Saved to filename 'gdc_download_20160701_011007.tar.gz' +% Total % Received % Xferd Average Speed Time Time Time Current + Dload Upload Total Spent Left Speed +100 5878k 0 5878k 100 205 290k 10 0:00:20 0:00:20 --:--:-- 198k ``` ### Downloading Controlled-access Files @@ -166,31 +142,31 @@ To download controlled-access files, a valid authentication token must be passed ```shell token=$(**NOTE:** When using the command line tool curl be sure to use the bash shell only for compatibility reasons. All examples using curl are using the bash shell. + +The authentication token should be kept in a secure location, as it allows access to all data accessible by the associated user account. ## API Endpoints @@ -52,12 +55,6 @@ The HTTP URL of an endpoint corresponding to a specific major version of the GDC For example, the address of the latest version of the `status` endpoint is `https://api.gdc.cancer.gov/status`, whereas the address of the `status` endpoint corresponding to version 0 of GDC API is `https://api.gdc.cancer.gov/v0/status`. -### GDC Legacy Archive - -To interact with data in the GDC Legacy Archive, add `legacy` to the endpoint URL: - - https://api.gdc.cancer.gov//legacy/ - ## Entity UUIDs All objects (*entities*) in the GDC are assigned a unique identifier in the form of a [version 4 universally unique identifier (UUID)](https://en.wikipedia.org/wiki/Universally_unique_identifier). The UUID uniquely identifies the entity in the GDC, and is stored in the entity's `id` property. @@ -68,51 +65,33 @@ See [GDC Data Model](../../Data/Data_Model/GDC_Data_Model.md) for details. ## Sample Request -The following is an example of a request to the `files` endpoint, which retrieves information about a BAM file stored in the GDC. +The following is an example of a request to the `files` endpoint, which retrieves information about a MAF file stored in the GDC. ``` shell -curl https://api.gdc.cancer.gov/files/d853e541-f16a-4345-9f00-88e03c2dc0bc?pretty=true +curl https://api.gdc.cancer.gov/files/cb92f61d-041c-4424-a3e9-891b7545f351?pretty=true ``` ``` python import requests import json file_endpt = 'https://api.gdc.cancer.gov/files/' -file_uuid = 'd853e541-f16a-4345-9f00-88e03c2dc0bc' +file_uuid = 'cb92f61d-041c-4424-a3e9-891b7545f351' response = requests.get(file_endpt + file_uuid) -print json.dumps(response.json(), indent=2) -``` Response -{ - "data": { - "data_type": "Aligned Reads", - "updated_datetime": "2016-05-26T17:06:40.003624-05:00", - "created_datetime": "2016-05-26T17:06:40.003624-05:00", - "file_name": "0017ba4c33a07ba807b29140b0662cb1_gdc_realn.bam", - "md5sum": "a08304b120c5df76b6532da0e9a35ced", - "data_format": "BAM", - "acl": [ - "phs000178" - ], - "access": "controlled", - "platform": "Illumina", - "state": "submitted", - "file_id": "d853e541-f16a-4345-9f00-88e03c2dc0bc", - "data_category": "Raw Sequencing Data", - "file_size": 23650901931, - "submitter_id": "c30188d7-be1a-4b43-9a17-e19ccd71792e", - "type": "aligned_reads", - "file_state": "processed", - "experimental_strategy": "WXS" - }, - "warnings": {} -} -``` +# OUTPUT METHOD 1: Write to a file. +file = open("sample_request.json", "w") +file.write(response.text) +file.close() + +# OUTPUT METHOD 2: View on screen. +print(json.dumps(response.json(), indent=2)) +``` +[Download Script](scripts/Sample_Request.py) ## Authentication Authentication is required for downloading controlled-access data, and for all data submission functionality. The GDC API uses tokens for authentication. -Users can obtain authentication tokens from the [GDC Data Portal](https://portal.gdc.cancer.gov) and the [GDC Data Submission Portal](https://portal.gdc.cancer.gov/submission). See the [GDC Data Portal User's Guide](../../Data_Portal/Users_Guide/Authentication.md#gdc-authentication-tokens) and the [GDC Data Submission Portal User's Guide](../../Data_Submission_Portal/Users_Guide/Authentication.md#gdc-authentication-tokens) for instructions. +Users can obtain authentication tokens from the [GDC Data Portal](https://portal.gdc.cancer.gov) and the [GDC Data Submission Portal](https://portal.gdc.cancer.gov/submission). See the [GDC Data Submission Portal User's Guide](../../Data_Submission_Portal/Users_Guide/Data_Submission_Process.md#authentication) for instructions. ### Using Authentication Tokens @@ -120,18 +99,52 @@ All API requests that require authentication must include a token as an `X-Auth- In the following example, an authentication token is saved as an environment variable and passed to `curl` to download a controlled-access file: -``` shell -token=$() -curl -O -J -H "X-Auth-Token: $token" 'https://api.gdc.cancer.gov/data/a1c1b23b-cc41-4e85-b1b7-62a42873c5af' +curl -O -J -H "X-Auth-Token: $token" 'https://api.gdc.cancer.gov/data/fd89bfa5-b3a7-4079-bf90-709580c006e5' ``` ```Output - % Total % Received % Xferd Average Speed Time Time Time Current - Dload Upload Total Spent Left Speed -100 31.4M 100 31.4M 0 0 290k 0 0:01:50 0:01:50 --:--:-- 172k -curl: Saved to filename 'ACOLD_p_TCGA_Batch17_SNP_N_GenomeWideSNP_6_A03_466078.tangent.copynumber.data.txt' +% Total % Received % Xferd Average Speed Time Time Time Current + Dload Upload Total Spent Left Speed +100 4161M 100 4161M 0 0 281k 0 4:12:45 4:12:45 --:--:-- 1894k + ``` +```Python +import requests +import json +import re + +''' + This script will not work until $TOKEN_FILE_PATH + is replaced with an actual path. +''' + +with open("$TOKEN_FILE_PATH","r") as token: + token_string = str(token.read().strip()) + +headers = { + 'X-Auth-Token': token_string + } + +data_endpt = 'https://api.gdc.cancer.gov/data/' +data_uuid = 'fd89bfa5-b3a7-4079-bf90-709580c006e5' +headers = { + 'X-Auth-Token': token_string + } +response = requests.get(data_endpt + data_uuid, headers=headers) + +# The file name can be found in the header within the Content-Disposition key. +response_head_cd = response.headers["Content-Disposition"] + +file_name = re.findall("filename=(.+)", response_head_cd)[0] + +with open(file_name, "wb") as output_file: + output_file.write(response.content) +``` +[Download Python Script](scripts/Authentication_Tokens.py) + For more information about authentication tokens, including token expiration and rotation, see [Data Security](../../Data/Data_Security/Data_Security.md#authentication-tokens). -**NOTE:** The authentication token should be kept in a secure location, as it allows access to all data accessible by the associated user account. +>**NOTE:** The authentication token should be kept in a secure location, as it allows access to all data accessible by the associated user account. diff --git a/docs/API/Users_Guide/GraphQL_Examples.md b/docs/API/Users_Guide/GraphQL_Examples.md new file mode 100644 index 000000000..fe9d7888d --- /dev/null +++ b/docs/API/Users_Guide/GraphQL_Examples.md @@ -0,0 +1,174 @@ +# Introduction to GDC GraphQL +[GraphQL](https://graphql.org/) is a query language for APIs. The [GDC REST API](https://docs.gdc.cancer.gov/API/Users_Guide/Getting_Started/) has structured and specifically defined query parameters as well as endpoints that have set requests and responses. The GDC GraphQL provides advanced GDC users greater flexibility to specify the data they would like to be returned. This allows queries to be cleaner and easier to understand, especially when combining multiple queries into one request. + +To produce queries in a visual interface, the GDC recommends using [GraphiQL](https://github.com/graphql/graphiql). See below for the correct endpoint URLs. + +## Using GDC GraphQL vs GDC REST API + +If the query requires only a subset of the data to be returned, GDC GraphQL may speed up requests as GraphQL queries return only the specified data. This may require less work on the GDC server-side to fulfill those requests. Conversely, if an entire data-set is required for each request, the GDC REST API may be a better fit. No matter which method is used, the data returned by the GDC REST API and the GraphQL query will be identical as they query the same source. + +## GDC GraphQL Overview +GraphQL is not a storage model or a database query language. The graph refers to graph structures defined in the schema, where nodes define objects and edges define relationships between objects. The API traverses and returns application data based on the schema definitions, independent of how the data is stored. + +## GDC GraphQL Endpoints + +The GDC GraphQL has only two endpoints: +* __GDC Search and Retrieval Endpoint:__ https://api.gdc.cancer.gov/v0/graphql +* __GDC Submission Endpoint:__ https://api.gdc.cancer.gov/v0/submission/graphql + +This page covers the search and retrieval endpoint, see the [GDC Submission API](Submission.md) for additional details on the submission endpoint. + +## GDC GraphQL Schema +All GDC GraphQL queries are validated and executed against the [GDC GraphQL schema]( https://github.com/NCI-GDC/portal-ui/blob/92f0dfa17838746093c3c011141d08391016da91/data/schema.graphql). Because the GraphQL parameters are discoverable, the GDC GraphQL schema can be queried for details about itself. + +The `__schema` keyword can be queried to list all types defined in the schema and retrieve details about each: + +```GraphQL +{ + __schema { + types { + name + kind + fields { + name + } + } + } +} +``` +The `__type` keyword can also be queried to retrieve details about any type such as "Explore" or "Case": +```GraphQL + +{ + __type(name: "Explore") { + name + kind + description + fields { + name + } + } +} +``` + +```GraphQL +{ + __type(name: "Case") { + name + kind + description + fields { + name + } + } +} +``` + +## Basic GraphQL queries in GDC +The two types of allowed operations in GDC GraphQL API are queries and mutations. Comparing GraphQL to REST, queries operate like `GET` requests, while mutations operate like `POST`/`PATCH`/`DELETE`. + +__Note:__ This guide does not cover GDC GraphQL mutation operations. + +GraphQL queries return only the data that is specified. Queries are built by specifying fields within fields (also called nested *subfields*) until only scalars are returned. Scalars are primitive values such as: `Int`, `Float`, `String`, `Boolean`, or `ID`. + +## Anatomy of a typical GDC GraphQL Query + + [![GraqhQL-Query](images/graphql-query.png)](images/graphql-query.png "Click to see the full image.") + +- __Operation type:__ Describes what type of operation that is being performed, such as query, mutation, or subscription +- __Operation name:__ Similar to a function name, gives queries meaningful names +- __Field:__ Denotes the specific fields on objects that will be included with the response data +- __Arguments:__ A set of key-value pairs associated with a specific field. The parameters can be literal values or variables. __NOTE:__ Arguments can appear on any field, even fields nested deep in an operation. +- __Variable definitions:__ As GraphQL is strong typed, it validates the variable being passed dynamically. __NOTE:__ Variables are passed separately from the query document as JSON such as: + +```json + { "filters_1": {"op":"in","content":{"field":"projects.program.name","value":["TARGET"]}}} +``` + +## GDC GraphQL Examples +### Nodes And Edges Example +A very powerful feature of GDC GraphQL API is that the graph structures defined in the [GDC GraphQL schema]( https://github.com/NCI-GDC/portal-ui/blob/92f0dfa17838746093c3c011141d08391016da91/data/schema.graphql ) can be queried and traversed. In these queries, nodes define objects and edges define relationships between objects. + +```GraphQL + +query PROJECTS_EDGES($filters_1: FiltersArgument) { + projects { + hits(filters: $filters_1) { + total + edges { + node { + primary_site + disease_type + project_id + dbgap_accession_number + } + } + } + } +} + + variable: + { "filters_1": {"op": "in", "content": {"field": "projects.primary_site", "value": ["Kidney"]}}} +``` + +### Query Case File Counts + +```GraphQL +query CaseFileCounts($filters: FiltersArgument) { + viewer { + repository { + cases { + hits(first: 1, filters: $filters) { + edges { + node { + case_id + files { + hits(first: 0) { + total + } + } + summary { + experimental_strategies { + experimental_strategy + file_count + } + data_categories { + data_category + file_count + } + } + } + } + } + } + } + } +} + +variable: +{"filters":{"op":"in","content":{"field":"cases.case_id","value":["dcd5860c-7e3a-44f3-a732-fe92fe3fe300"]}}} +``` + +### Query Simple Static Mutations Based on Gene IDs + +```GraphQL + +query PROJECTS_EDGES($filters_2: FiltersArgument) { + explore { + ssms { + hits(filters: $filters_2) { + total + edges { + node { + ssm_id + gene_aa_change + } + } + } + } + } +} + +variable: +{"filters_2": {"op":"in","content":{"field":"consequence.transcript.gene.gene_id","value":["ENSG00000155657"]}}} +``` diff --git a/docs/API/Users_Guide/Python_Examples.md b/docs/API/Users_Guide/Python_Examples.md index 25ab3b6d3..09db68a8f 100644 --- a/docs/API/Users_Guide/Python_Examples.md +++ b/docs/API/Users_Guide/Python_Examples.md @@ -1,6 +1,6 @@ # Using Python to Query the GDC API -Python can be a versatile tool for retrieving information from the GDC API and performing downstream processing. This page details some examples that demonstrate the basic API queries using Python. The examples in this guide will use the [requests](http://docs.python-requests.org/en/master/) Python library and should be compatible with Python3. +Python can be a versatile tool for retrieving information from the GDC API and performing downstream processing. This page details some examples that demonstrate the basic API queries using Python. The examples in this guide will use the [requests](https://pypi.org/project/requests/) Python library and should be compatible with Python3. ## Querying Metadata @@ -438,5 +438,13 @@ The following script should produce an unformatted JSON string with information import requests status_endpt = "https://api.gdc.cancer.gov/status" response = requests.get(status_endpt) + +# OUTPUT METHOD 1: Write to a file. +file = open("api_status.json", "w") +file.write(response.text) +file.close() + +# OUTPUT METHOD 2: View on screen. print(response.content) ``` +[Download Script](scripts/Basic_Troubleshooting.py) diff --git a/docs/API/Users_Guide/Search_and_Retrieval.md b/docs/API/Users_Guide/Search_and_Retrieval.md index f156ae92e..2c8120489 100644 --- a/docs/API/Users_Guide/Search_and_Retrieval.md +++ b/docs/API/Users_Guide/Search_and_Retrieval.md @@ -4,7 +4,7 @@ The GDC API provides endpoints that search and retrieve information stored in the GDC according to the [GDC Data Model](../../Data/Data_Model/GDC_Data_Model.md). The general format of requests to search & retrieval endpoints is described below. -**Note:** Queries described in this section work for datasets that have been released to the GDC Data Portal. Unreleased data that is in the process of being submitted to GDC cannot be queried using these methods. See [Submission](Submission.md) to learn how to query unreleased data using GraphQL. +>**Note:** Queries described in this section work for datasets that have been released to the GDC Data Portal. Unreleased data that is in the process of being submitted to GDC cannot be queried using these methods. See [Submission](Submission.md) to learn how to query unreleased data using GraphQL. ### Components of a Request @@ -19,8 +19,6 @@ A typical search and retrieval API request specifies the following parameters: Requests can be executed using HTTP GET or HTTP POST. GET requests are limited by maximum URL length, so the POST method is recommended for large queries. -**Note:** Requests for information stored in the GDC Legacy Archive must be directed to `legacy/` endpoints. See [Getting Started](Getting_Started.md#gdc-legacy-archive) for details. - ### POST Example The following is an example of an HTTP POST request to the `files` endpoint of the GDC API. It looks for Gene Expression Quantification files associated with specific TCGA cases (represented by TCGA barcodes) and retrieves the associated biospecimen metadata in TSV format. @@ -87,56 +85,63 @@ The following search and retrieval endpoints are available in the GDC API: The choice of endpoint determines what is listed in the search results. The `files` endpoint will generate a list of files, whereas the `cases` endpoint will generate a list of cases. Each of the above endpoints, other than `_mapping`, can query and return any of the related fields in the [GDC Data Model](../../Data/Data_Model/GDC_Data_Model.md). So the `cases` endpoint can be queried for file fields (e.g. to look for cases that have certain types of experimental data), and the `files` endpoint can be queried for clinical metadata associated with a case (e.g. to look for files from cases diagnosed with a specific cancer type). -### Project Endpoint +### `Project` Endpoint The `projects` endpoint provides access to project records, the highest level of data organization in the GDC. #### Example This example is a query for projects contained in the GDC. It uses the [from](#from), [size](#size), [sort](#sort), and [pretty](#pretty) parameters, and returns the first two projects sorted by project id. ```shell -curl 'https://api.gdc.cancer.gov/projects?from=0&size=2&sort=project.project_id:asc&pretty=true' +curl 'https://api.gdc.cancer.gov/projects?from=0&size=2&sort=project_id:asc&pretty=true' ``` ``` Output { "data": { "hits": [ { - "dbgap_accession_number": null, - "disease_type": [ - "Brain Lower Grade Glioma" - ], - "released": true, - "state": "legacy", + "id": "APOLLO-LUAD", "primary_site": [ - "Brain" + "Bronchus and lung" ], - "project_id": "TCGA-LGG", - "id": "TCGA-LGG", - "name": "Brain Lower Grade Glioma" - }, - { - "dbgap_accession_number": null, + "dbgap_accession_number": "phs003011", + "project_id": "APOLLO-LUAD", "disease_type": [ - "Thyroid Carcinoma" + "Adenomas and Adenocarcinomas" ], - "released": true, - "state": "legacy", + "name": "APOLLO1: Proteogenomic characterization of lung adenocarcinoma", + "releasable": false, + "state": "open", + "released": true + }, + { + "id": "BEATAML1.0-COHORT", "primary_site": [ - "Thyroid" + "Hematopoietic and reticuloendothelial systems" ], - "project_id": "TCGA-THCA", - "id": "TCGA-THCA", - "name": "Thyroid Carcinoma" + "dbgap_accession_number": "phs001657", + "project_id": "BEATAML1.0-COHORT", + "disease_type": [ + "Myelodysplastic Syndromes", + "Leukemias, NOS", + "Unknown", + "Myeloid Leukemias", + "Plasma Cell Tumors", + "Chronic Myeloproliferative Disorders" + ], + "name": "Functional Genomic Landscape of Acute Myeloid Leukemia", + "releasable": true, + "state": "open", + "released": true } ], "pagination": { "count": 2, - "sort": "project.project_id:asc", + "total": 78, + "size": 2, "from": 0, + "sort": "None", "page": 1, - "total": 39, - "pages": 20, - "size": 2 + "pages": 39 } }, "warnings": {} @@ -153,67 +158,109 @@ curl 'https://api.gdc.cancer.gov/projects/TARGET-NBL?expand=summary,summary.expe ```Response { "data": { - "dbgap_accession_number": "phs000467", - "disease_type": [ - "Neuroblastoma" - ], "summary": { + "file_count": 5705, "data_categories": [ { - "case_count": 151, - "file_count": 471, - "data_category": "Transcriptome Profiling" + "file_count": 943, + "case_count": 278, + "data_category": "Sequencing Reads" + }, + { + "file_count": 3080, + "case_count": 220, + "data_category": "Simple Nucleotide Variation" }, { - "case_count": 1127, "file_count": 3, - "data_category": "Biospecimen" + "case_count": 1119, + "data_category": "Clinical" }, { - "case_count": 216, - "file_count": 1732, - "data_category": "Simple Nucleotide Variation" + "file_count": 705, + "case_count": 225, + "data_category": "DNA Methylation" }, { - "case_count": 7, - "file_count": 1, - "data_category": "Clinical" + "file_count": 2, + "case_count": 1132, + "data_category": "Biospecimen" + }, + { + "file_count": 324, + "case_count": 155, + "data_category": "Transcriptome Profiling" }, { - "case_count": 270, - "file_count": 599, - "data_category": "Raw Sequencing Data" + "file_count": 648, + "case_count": 155, + "data_category": "Structural Variation" } ], - "case_count": 1127, - "file_count": 2806, "experimental_strategies": [ { - "case_count": 221, - "file_count": 2174, + "file_count": 1458, + "case_count": 155, + "experimental_strategy": "RNA-Seq" + }, + { + "file_count": 15, + "case_count": 8, + "experimental_strategy": "WGS" + }, + { + "file_count": 3522, + "case_count": 222, "experimental_strategy": "WXS" }, { - "case_count": 151, - "file_count": 628, - "experimental_strategy": "RNA-Seq" + "file_count": 705, + "case_count": 225, + "experimental_strategy": "Methylation Array" } ], - "file_size": 8157614402888 + "case_count": 1132, + "file_size": 16968781125824 }, - "released": true, - "state": "legacy", "primary_site": [ - "Nervous System" + "Stomach", + "Bones, joints and articular cartilage of limbs", + "Heart, mediastinum, and pleura", + "Peripheral nerves and autonomic nervous system", + "Uterus, NOS", + "Bones, joints and articular cartilage of other and unspecified sites", + "Other endocrine glands and related structures", + "Renal pelvis", + "Retroperitoneum and peritoneum", + "Liver and intrahepatic bile ducts", + "Meninges", + "Connective, subcutaneous and other soft tissues", + "Adrenal gland", + "Unknown", + "Spinal cord, cranial nerves, and other parts of central nervous system", + "Skin", + "Other and ill-defined sites", + "Kidney", + "Lymph nodes", + "Hematopoietic and reticuloendothelial systems" ], + "dbgap_accession_number": "phs000467", "project_id": "TARGET-NBL", - "name": "Neuroblastoma" + "disease_type": [ + "Neuroepitheliomatous Neoplasms", + "Not Applicable" + ], + "name": "Neuroblastoma", + "releasable": true, + "state": "open", + "released": true }, "warnings": {} } + ``` -### Files Endpoint +### `Files` Endpoint The GDC Files Endpoint `https://api.gdc.cancer.gov/files` enables search and retrieval of information relating to files stored in the GDC, including file properties such as `file_name`, `md5sum`, `data_format`, and others. @@ -229,99 +276,97 @@ curl 'https://api.gdc.cancer.gov/files?from=0&size=2&sort=file_size:asc&pretty=t "data": { "hits": [ { - "data_release": "13.0", - "data_type": "Raw Simple Somatic Mutation", - "updated_datetime": "2018-07-20T22:27:55.342974+00:00", - "file_name": "333193d5-ca9a-4262-81f5-e9f3b44358fe.vcf.gz", - "submitter_id": "AD19_SimpleSomaticMutation", - "file_id": "333193d5-ca9a-4262-81f5-e9f3b44358fe", - "file_size": 866, - "id": "333193d5-ca9a-4262-81f5-e9f3b44358fe", - "created_datetime": "2017-09-10T19:16:02.549312-05:00", - "md5sum": "e33e95edb778fe67643162ef0ae3297e", - "data_format": "VCF", - "acl": [ - "phs001179" - ], + "id": "0ab5e358-b1ff-4433-8959-c37c5890d9aa", + "data_format": "BEDPE", "access": "controlled", + "file_name": "090e2828-079c-48e6-97cb-735c763da8d3.wgs.BRASS.rerun_structural_variation.bedpe.gz", + "submitter_id": "247c3c9a-58b9-4b70-bda8-cb197acb5609", + "data_category": "Somatic Structural Variation", + "acl": [ + "phs001287" + ], + "type": "structural_variation", + "file_size": 20, + "created_datetime": "2022-04-08T20:27:04.633842-05:00", + "updated_datetime": "2022-07-07T11:02:27.204310-05:00", + "file_id": "0ab5e358-b1ff-4433-8959-c37c5890d9aa", + "data_type": "Structural Rearrangement", "state": "released", + "experimental_strategy": "WGS", "version": "1", - "data_category": "Simple Nucleotide Variation", - "type": "simple_somatic_mutation", - "experimental_strategy": "Targeted Sequencing" + "data_release": "34.0 - 37.0" }, { - "data_release": "13.0", - "data_type": "Raw Simple Somatic Mutation", - "updated_datetime": "2018-07-20T22:27:55.342974+00:00", - "file_name": "d9114e23-0f62-4979-aefc-0dd4d5eb891b.vcf.gz", - "submitter_id": "AD116_SimpleSomaticMutation", - "file_id": "d9114e23-0f62-4979-aefc-0dd4d5eb891b", - "file_size": 866, - "id": "d9114e23-0f62-4979-aefc-0dd4d5eb891b", - "created_datetime": "2017-09-10T21:53:02.376246-05:00", - "md5sum": "95bbfd0586d3c284e9f88edf3bf26065", - "data_format": "VCF", - "acl": [ - "phs001179" - ], + "id": "a8bc2405-b57d-48bb-b241-18b3e28caa56", + "data_format": "BEDPE", "access": "controlled", + "file_name": "eae76f14-8aa7-427f-a90c-4e0ed095e0c2.wgs.BRASS.rerun_structural_variation.bedpe.gz", + "submitter_id": "618cd251-ddcb-4a7e-9a6d-efb132b0bd7a", + "data_category": "Somatic Structural Variation", + "acl": [ + "phs001287" + ], + "type": "structural_variation", + "file_size": 20, + "created_datetime": "2022-04-08T20:43:16.505747-05:00", + "updated_datetime": "2022-07-07T11:00:43.345766-05:00", + "file_id": "a8bc2405-b57d-48bb-b241-18b3e28caa56", + "data_type": "Structural Rearrangement", "state": "released", + "experimental_strategy": "WGS", "version": "1", - "data_category": "Simple Nucleotide Variation", - "type": "simple_somatic_mutation", - "experimental_strategy": "Targeted Sequencing" + "data_release": "34.0 - 37.0" } ], "pagination": { "count": 2, - "sort": "file_size:asc", + "total": 931947, + "size": 2, "from": 0, + "sort": "None", "page": 1, - "total": 356381, - "pages": 178191, - "size": 2 + "pages": 465974 } }, "warnings": {} } + ``` #### Retrieval of file metadata using individual UUIDs: -The `\files` endpoint supports a simple query format that retrieves the metadata of a single file using its UUID. Note that the `\files` endpoint is inactive when querying for earlier file versions. In that case, the `\history` or `/files/versions` endpoints should be used instead. +The `/files` endpoint supports a simple query format that retrieves the metadata of a single file using its UUID. Note that the `/files` endpoint is inactive when querying for earlier file versions. In that case, the `/history` or `/files/versions` endpoints should be used instead. ```Shell -curl 'https://api.gdc.cancer.gov/files/874e71e0-83dd-4d3e-8014-10141b49f12c?pretty=true' +curl 'https://api.gdc.cancer.gov/files/20f45e04-3c10-4f11-b57b-719880eab69e?pretty=true' ``` ``` Output { "data": { - "data_release": "13.0", - "data_type": "Raw Simple Somatic Mutation", - "updated_datetime": "2018-07-20T22:27:55.342974+00:00", - "created_datetime": "2016-06-03T17:03:06.608739-05:00", - "file_name": "874e71e0-83dd-4d3e-8014-10141b49f12c.vcf.gz", - "md5sum": "acf2929b1b825bcd1377023e8b8767ec", "data_format": "VCF", + "access": "controlled", + "file_name": "TCGA_BRCA.8d9cb5ae-e568-41fc-8b53-14467c2623dc.wxs.MuTect2.somatic_annotation.vcf.gz", + "submitter_id": "675f31dd-70e5-4a72-8139-423b14b31564", + "data_category": "Simple Nucleotide Variation", "acl": [ "phs000178" ], - "access": "controlled", - "state": "live", - "version": "1", - "file_id": "874e71e0-83dd-4d3e-8014-10141b49f12c", - "data_category": "Simple Nucleotide Variation", - "file_size": 122293, - "submitter_id": "TCGA-V4-A9EZ-01A-11D-A39W-08_TCGA-V4-A9EZ-10A-01D-A39Z-08_mutect", - "type": "simple_somatic_mutation", - "experimental_strategy": "WXS" + "type": "annotated_somatic_mutation", + "file_size": 6894331, + "created_datetime": "2022-02-07T08:48:39.178606-06:00", + "updated_datetime": "2022-02-09T12:11:12.781445-06:00", + "file_id": "20f45e04-3c10-4f11-b57b-719880eab69e", + "data_type": "Annotated Somatic Mutation", + "state": "released", + "experimental_strategy": "WXS", + "version": "2", + "data_release": "32.0 - 37.0" }, "warnings": {} } ``` -__Note:__ The `file_size` field associated with each file is reported in bytes. +>__Note:__ The `file_size` field associated with each file is reported in bytes. #### Example of retrieving file version information: @@ -335,40 +380,50 @@ curl 'https://api.gdc.cancer.gov/files/versions/1dd28069-5777-4ff9-bd2b-d1ba68e8 ``` Output1 [ { - "latest_size": 332092, - "latest_id": "1dd28069-5777-4ff9-bd2b-d1ba68e88b06", - "latest_version": "1", + "id": "1dd28069-5777-4ff9-bd2b-d1ba68e88b06", "filename": "1dd28069-5777-4ff9-bd2b-d1ba68e88b06.vcf.gz", - "state": "validated", "version": "1", - "latest_filename": "1dd28069-5777-4ff9-bd2b-d1ba68e88b06.vcf.gz", - "latest_release": [ - "13.0" - ], - "latest_state": "validated", - "release": "13.0", - "latest_md5": "c2f9b196e154906a70c7ec46492a859d", + "md5": "c2f9b196e154906a70c7ec46492a859d", "size": 332092, - "id": "1dd28069-5777-4ff9-bd2b-d1ba68e88b06", - "md5": "c2f9b196e154906a70c7ec46492a859d" + "state": "validated", + "release": "12.0", + "latest_id": "76b3f4d8-c6b7-4662-ac42-1d27d4684281", + "latest_filename": "def1cc5b-55f0-4372-a3ff-df3ea93cf3e7.wxs.somaticsniper.raw_somatic_mutation.vcf.gz", + "latest_version": "2", + "latest_size": 357706, + "latest_state": "validated", + "latest_release": [ + "32.0", + "33.0", + "33.1", + "34.0", + "35.0", + "36.0", + "37.0" + ] }, { - "latest_size": 6653119038, - "latest_id": "2a03abac-f1a2-49a9-a57c-7543739dd862", - "latest_version": "1", + "id": "2a03abac-f1a2-49a9-a57c-7543739dd862", "filename": "a5d86cde-32ca-4ed6-b1a5-5a47575f2ac6_gdc_realn_rehead.bam", - "state": "validated", "version": "1", - "latest_filename": "a5d86cde-32ca-4ed6-b1a5-5a47575f2ac6_gdc_realn_rehead.bam", - "latest_release": [ - "13.0" - ], - "latest_state": "validated", - "release": "13.0", - "latest_md5": "48686fcd84ac713d44261ca9e26b89fb", + "md5": "48686fcd84ac713d44261ca9e26b89fb", "size": 6653119038, - "id": "2a03abac-f1a2-49a9-a57c-7543739dd862", - "md5": "48686fcd84ac713d44261ca9e26b89fb" + "state": "validated", + "release": "12.0", + "latest_id": "de0ce84d-c286-405c-a556-39dac14c7c74", + "latest_filename": "d45c33cc-88e2-4de5-a578-f7e31a6c0738.rna_seq.genomic.gdc_realn.bam", + "latest_version": "2", + "latest_size": 6223445806, + "latest_state": "validated", + "latest_release": [ + "32.0", + "33.0", + "33.1", + "34.0", + "35.0", + "36.0", + "37.0" + ] } ] ``` @@ -377,82 +432,126 @@ curl --request POST --header "Content-Type: text/tsv" https://api.gdc.cancer.go ``` ``` Output2 -[{ - "latest_size": 44857, - "state": "validated", - "latest_version": "1", - "filename": "nationwidechildrens.org_clinical.TCGA-13-1500.xml", - "latest_id": "0b20e27c-9a09-4f15-923f-d5b4f185dc22", - "version": "1", - "latest_filename": "nationwidechildrens.org_clinical.TCGA-13-1500.xml", - "latest_release": [ - "12.0" - ], - "latest_state": "validated", - "release": "12.0", - "latest_md5": "597aa4df24c4d544b6c25cbd8b25a33e", - "md5": "597aa4df24c4d544b6c25cbd8b25a33e", - "id": "0b20e27c-9a09-4f15-923f-d5b4f185dc22", - "size": 44857 -},{ - "latest_size": 27620, - "state": "validated", - "latest_version": "1", - "filename": "BUCKS_p_TCGA_272_273_N_GenomeWideSNP_6_G05_1320676.grch38.seg.v2.txt", - "latest_id": "3edc7084-013c-4493-8507-c00b0e9962d8", - "version": "1", - "latest_filename": "BUCKS_p_TCGA_272_273_N_GenomeWideSNP_6_G05_1320676.grch38.seg.v2.txt", - "latest_release": [ - "12.0" - ], - "latest_state": "validated", - "release": "12.0", - "latest_md5": "35a18d990a05eedfaf96e753bee0b96d", - "md5": "35a18d990a05eedfaf96e753bee0b96d", - "id": "3edc7084-013c-4493-8507-c00b0e9962d8", - "size": 27620 -},{ - "latest_size": 2346, - "state": "validated", - "latest_version": "1", - "filename": "a22f5e32-b16e-458f-a412-7e438056ece6.vep.vcf.gz", - "latest_id": "a22f5e32-b16e-458f-a412-7e438056ece6", - "version": "1", - "latest_filename": "a22f5e32-b16e-458f-a412-7e438056ece6.vep.vcf.gz", - "latest_release": [ - "12.0" - ], - "latest_state": "validated", - "release": "12.0", - "latest_md5": "68b2433b31679bbbc6681919a1b81762", - "md5": "68b2433b31679bbbc6681919a1b81762", - "id": "a22f5e32-b16e-458f-a412-7e438056ece6", - "size": 2346 -},{ - "latest_size": 35411, - "state": "validated", - "latest_version": "1", - "filename": "CYANS_p_TCGAb_422_423_424_NSP_GenomeWideSNP_6_G12_1513758.nocnv_grch38.seg.v2.txt", - "latest_id": "ac7d2078-bd6b-446e-b30a-d889da5624b6", - "version": "1", - "latest_filename": "CYANS_p_TCGAb_422_423_424_NSP_GenomeWideSNP_6_G12_1513758.nocnv_grch38.seg.v2.txt", - "latest_release": [ - "12.0" - ], - "latest_state": "validated", - "release": "12.0", - "latest_md5": "6338826b620773062232830fad51ae64", - "md5": "6338826b620773062232830fad51ae64", - "id": "ac7d2078-bd6b-446e-b30a-d889da5624b6", - "size": 35411 -}] -``` - -### Cases Endpoint +[ + { + "id": "0b20e27c-9a09-4f15-923f-d5b4f185dc22", + "filename": "nationwidechildrens.org_clinical.TCGA-13-1500.xml", + "version": "1", + "md5": "597aa4df24c4d544b6c25cbd8b25a33e", + "size": 44857, + "state": "validated", + "release": "12.0", + "latest_id": "0b20e27c-9a09-4f15-923f-d5b4f185dc22", + "latest_filename": "nationwidechildrens.org_clinical.TCGA-13-1500.xml", + "latest_version": "1", + "latest_md5": "597aa4df24c4d544b6c25cbd8b25a33e", + "latest_size": 44857, + "latest_state": "validated", + "latest_release": [ + "12.0", + "13.0", + "14.0", + "15.0", + "16.0", + "17.0", + "18.0", + "19.0", + "20.0", + "21.0", + "22.0", + "23.0", + "24.0", + "25.0", + "26.0", + "27.0", + "28.0", + "29.0", + "30.0", + "31.0", + "32.0", + "33.0", + "33.1", + "34.0", + "35.0", + "36.0", + "37.0" + ] + }, + { + "id": "3edc7084-013c-4493-8507-c00b0e9962d8", + "filename": "BUCKS_p_TCGA_272_273_N_GenomeWideSNP_6_G05_1320676.grch38.seg.v2.txt", + "version": "1", + "md5": "35a18d990a05eedfaf96e753bee0b96d", + "size": 27620, + "state": "validated", + "release": "12.0", + "latest_id": "3edc7084-013c-4493-8507-c00b0e9962d8", + "latest_filename": "BUCKS_p_TCGA_272_273_N_GenomeWideSNP_6_G05_1320676.grch38.seg.v2.txt", + "latest_version": "1", + "latest_md5": "35a18d990a05eedfaf96e753bee0b96d", + "latest_size": 27620, + "latest_state": "validated", + "latest_release": [ + "12.0", + "13.0", + "14.0", + "15.0", + "16.0", + "17.0", + "18.0", + "19.0", + "20.0", + "21.0", + "22.0", + "23.0", + "24.0", + "25.0", + "26.0", + "27.0", + "28.0", + "29.0", + "30.0", + "31.0", + "32.0", + "33.0", + "33.1", + "34.0", + "35.0", + "36.0", + "37.0" + ] + }, + { + "id": "a22f5e32-b16e-458f-a412-7e438056ece6", + "filename": "a22f5e32-b16e-458f-a412-7e438056ece6.vep.vcf.gz", + "version": "1", + "md5": "68b2433b31679bbbc6681919a1b81762", + "size": 2346, + "state": "validated", + "release": "12.0", + "latest_id": "55491171-6170-45cb-af9d-d99345b289e5", + "latest_filename": "4b89bb97-41f6-43c4-a481-287556f7bb4a.targeted_sequencing.annotated_somatic_mutation.vcf.gz", + "latest_version": "2", + "latest_size": 2618, + "latest_state": "validated", + "latest_release": [ + "32.0", + "33.0", + "33.1", + "34.0", + "35.0", + "36.0", + "37.0" + ] + } +] +``` + +### `Cases` Endpoint The GDC Cases Endpoint `https://api.gdc.cancer.gov/cases` enables search and retrieval of information related to a specific case. -__Note:__ The `cases` endpoint is designed to retrieve the metadata associated with one or more cases, including all nested biospecimen entities. Filters can be applied to retrieve information for entire cases, but not for lower-level biospecimen entities. For example, a sample within a case cannot be used to query for aliquots that are associated only with that sample. All aliquots associated with the case would be retrieved. +The `cases` endpoint is designed to retrieve the metadata associated with one or more cases, including all nested biospecimen entities. Filters can be applied to retrieve information for entire cases, but not for lower-level biospecimen entities. For example, a sample within a case cannot be used to query for aliquots that are associated only with that sample. All aliquots associated with the case would be retrieved. #### Example @@ -468,100 +567,109 @@ curl 'https://api.gdc.cancer.gov/cases?filters=%7B%22op%22%3A%22and%22%2C%22cont ``` ``` Output { - { - "data": { - "hits": [ - { - "updated_datetime": "2017-03-04T16:39:19.244769-06:00", - "submitter_analyte_ids": [ - "TCGA-BH-A0EA-01A-11R", - "TCGA-BH-A0EA-10A-01W", - "TCGA-BH-A0EA-01A-11W", - "TCGA-BH-A0EA-01A-11D", - "TCGA-BH-A0EA-10A-01D" - ], - "analyte_ids": [ - "fe678556-acf4-4bde-a95e-860bb0150a95", - "66ed0f86-5ca5-4dec-ba76-7ee4dcf31831", - "f19f408a-815f-43d9-8032-e9482b796371", - "69ddc092-88a0-4839-a2bb-9f1c9e760409", - "30cb470f-66d4-4085-8c30-83a42e8453d4" - ], - "submitter_id": "TCGA-BH-A0EA", - "case_id": "1f601832-eee3-48fb-acf5-80c4a454f26e", - "id": "1f601832-eee3-48fb-acf5-80c4a454f26e", - "disease_type": "Breast Invasive Carcinoma", - "sample_ids": [ - "9a6c71a6-82cd-42b1-a93f-f569370848d6", - "7f791228-dd77-4ab0-8227-d784a4c7fea1" - ], - "portion_ids": [ - "cb6086d1-3416-4310-b109-e8fa6e8b72d4", - "8629bf5a-cdaf-4f6a-90bb-27dd4a7565c5", - "ae4f5816-f97a-4605-9b05-9ab820467dee" - ], - "submitter_portion_ids": [ - "TCGA-BH-A0EA-01A-21-A13C-20", - "TCGA-BH-A0EA-01A-11", - "TCGA-BH-A0EA-10A-01" - ], - "created_datetime": null, - "slide_ids": [ - "90154ea1-6b76-4445-870e-d531d6fa1239", - "a0826f0d-986a-491b-8c6f-b34f8929f3ee" - ], - "state": "live", - "aliquot_ids": [ - "eef9dce1-6ba6-432b-bbe2-53c7dbe64fe7", - "cde982b7-3b0a-49eb-8710-a599cb0e44c1", - "b1a3739d-d554-4202-b96f-f25a444e2042", - "97c64d6a-7dce-4d0f-9cb3-b3e4eb4719c5", - "561b8777-801a-49ed-a306-e7dafeb044b6", - "42d050e4-e8ee-4442-b9c0-0ee14706b138", - "ca71ca96-cbb7-4eab-9487-251dda34e107", - "cfbd5476-e83a-401d-9f9a-639c73a0e35b", - "edad5bd3-efe0-4c5f-b05c-2c0c2951c45a", - "262715e1-835c-4f16-8ee7-6900e26f7cf5", - "2beb34c4-d493-4a73-b21e-de77d43251ff", - "bcb7fc6d-60a0-48b7-aa81-14c0dda72d76" - ], - "primary_site": "Breast", - "submitter_aliquot_ids": [ - "TCGA-BH-A0EA-10A-01D-A113-01", - "TCGA-BH-A0EA-01A-11R-A115-07", - "TCGA-BH-A0EA-01A-11D-A10Y-09", - "TCGA-BH-A0EA-01A-11D-A314-09", - "TCGA-BH-A0EA-01A-11R-A114-13", - "TCGA-BH-A0EA-01A-11D-A111-01", - "TCGA-BH-A0EA-01A-11D-A112-05", - "TCGA-BH-A0EA-01A-11D-A10X-02", - "TCGA-BH-A0EA-10A-01D-A110-09", - "TCGA-BH-A0EA-10A-01W-A12U-09", - "TCGA-BH-A0EA-10A-01D-A10Z-02", - "TCGA-BH-A0EA-01A-11W-A12T-09" - ], - "submitter_sample_ids": [ - "TCGA-BH-A0EA-10A", - "TCGA-BH-A0EA-01A" - ], - "submitter_slide_ids": [ - "TCGA-BH-A0EA-01A-01-MSA", - "TCGA-BH-A0EA-01A-01-TSA" - ] - } - ], - "pagination": { - "count": 1, - "sort": "", - "from": 0, - "page": 1, - "total": 1, - "pages": 1, - "size": 10 - } - }, - "warnings": {} - } + "data": { + "hits": [ + { + "id": "1f601832-eee3-48fb-acf5-80c4a454f26e", + "slide_ids": [ + "a0826f0d-986a-491b-8c6f-b34f8929f3ee", + "90154ea1-6b76-4445-870e-d531d6fa1239", + "1dd1cab5-5a81-428a-8153-91e8c4cf9905" + ], + "submitter_slide_ids": [ + "TCGA-BH-A0EA-01Z-00-DX1", + "TCGA-BH-A0EA-01A-01-MSA", + "TCGA-BH-A0EA-01A-01-TSA" + ], + "disease_type": "Ductal and Lobular Neoplasms", + "analyte_ids": [ + "f19f408a-815f-43d9-8032-e9482b796371", + "fe678556-acf4-4bde-a95e-860bb0150a95", + "69ddc092-88a0-4839-a2bb-9f1c9e760409", + "66ed0f86-5ca5-4dec-ba76-7ee4dcf31831", + "30cb470f-66d4-4085-8c30-83a42e8453d4" + ], + "submitter_id": "TCGA-BH-A0EA", + "submitter_analyte_ids": [ + "TCGA-BH-A0EA-10A-01D", + "TCGA-BH-A0EA-01A-11D", + "TCGA-BH-A0EA-01A-11R", + "TCGA-BH-A0EA-10A-01W", + "TCGA-BH-A0EA-01A-11W" + ], + "aliquot_ids": [ + "cde982b7-3b0a-49eb-8710-a599cb0e44c1", + "b1a3739d-d554-4202-b96f-f25a444e2042", + "eef9dce1-6ba6-432b-bbe2-53c7dbe64fe7", + "97c64d6a-7dce-4d0f-9cb3-b3e4eb4719c5", + "262715e1-835c-4f16-8ee7-6900e26f7cf5", + "cfbd5476-e83a-401d-9f9a-639c73a0e35b", + "bcb7fc6d-60a0-48b7-aa81-14c0dda72d76", + "561b8777-801a-49ed-a306-e7dafeb044b6", + "edad5bd3-efe0-4c5f-b05c-2c0c2951c45a", + "42d050e4-e8ee-4442-b9c0-0ee14706b138", + "2beb34c4-d493-4a73-b21e-de77d43251ff", + "ca71ca96-cbb7-4eab-9487-251dda34e107" + ], + "submitter_aliquot_ids": [ + "TCGA-BH-A0EA-10A-01W-A12U-09", + "TCGA-BH-A0EA-01A-11D-A111-01", + "TCGA-BH-A0EA-01A-11D-A314-09", + "TCGA-BH-A0EA-01A-11D-A10X-02", + "TCGA-BH-A0EA-10A-01D-A10Z-02", + "TCGA-BH-A0EA-10A-01D-A110-09", + "TCGA-BH-A0EA-01A-11D-A10Y-09", + "TCGA-BH-A0EA-10A-01D-A113-01", + "TCGA-BH-A0EA-01A-11D-A112-05", + "TCGA-BH-A0EA-01A-11R-A115-07", + "TCGA-BH-A0EA-01A-11W-A12T-09", + "TCGA-BH-A0EA-01A-11R-A114-13" + ], + "created_datetime": null, + "diagnosis_ids": [ + "84654ad5-2a2c-5c3b-8340-ecac6a5550fe" + ], + "sample_ids": [ + "55864d86-dab8-47bb-a3e3-8cfb198b06c1", + "9a6c71a6-82cd-42b1-a93f-f569370848d6", + "7f791228-dd77-4ab0-8227-d784a4c7fea1" + ], + "submitter_sample_ids": [ + "TCGA-BH-A0EA-01A", + "TCGA-BH-A0EA-01Z", + "TCGA-BH-A0EA-10A" + ], + "primary_site": "Breast", + "submitter_diagnosis_ids": [ + "TCGA-BH-A0EA_diagnosis" + ], + "updated_datetime": "2019-08-06T14:15:54.128069-05:00", + "case_id": "1f601832-eee3-48fb-acf5-80c4a454f26e", + "state": "released", + "portion_ids": [ + "cb6086d1-3416-4310-b109-e8fa6e8b72d4", + "8629bf5a-cdaf-4f6a-90bb-27dd4a7565c5", + "ae4f5816-f97a-4605-9b05-9ab820467dee" + ], + "submitter_portion_ids": [ + "TCGA-BH-A0EA-10A-01", + "TCGA-BH-A0EA-01A-21-A13C-20", + "TCGA-BH-A0EA-01A-11" + ] + } + ], + "pagination": { + "count": 1, + "total": 1, + "size": 10, + "from": 0, + "sort": "", + "page": 1, + "pages": 1 + } + }, + "warnings": {} +} ``` #### Retrieval of case metadata using individual UUIDs: @@ -572,133 +680,133 @@ The `cases` endpoint supports a simple query format that retrieves the metadata curl 'https://api.gdc.cancer.gov/cases/1f601832-eee3-48fb-acf5-80c4a454f26e?pretty=true&expand=diagnoses' ``` ```Response -{ + "data": { - "diagnoses": [ - { - "classification_of_tumor": "not reported", - "last_known_disease_status": "not reported", - "updated_datetime": "2016-05-16T10:59:16.740358-05:00", - "primary_diagnosis": "c50.9", - "submitter_id": "TCGA-BH-A0EA_diagnosis", - "tumor_stage": "stage iia", - "age_at_diagnosis": 26548.0, - "vital_status": "dead", - "morphology": "8500/3", - "days_to_death": 991.0, - "days_to_last_known_disease_status": null, - "days_to_last_follow_up": null, - "state": null, - "days_to_recurrence": null, - "diagnosis_id": "84654ad5-2a2c-5c3b-8340-ecac6a5550fe", - "tumor_grade": "not reported", - "tissue_or_organ_of_origin": "c50.9", - "days_to_birth": -26548.0, - "progression_or_recurrence": "not reported", - "prior_malignancy": "not reported", - "site_of_resection_or_biopsy": "c50.9", - "created_datetime": null - } - ], - "sample_ids": [ - "7f791228-dd77-4ab0-8227-d784a4c7fea1", - "9a6c71a6-82cd-42b1-a93f-f569370848d6" - ], - "portion_ids": [ - "cb6086d1-3416-4310-b109-e8fa6e8b72d4", - "8629bf5a-cdaf-4f6a-90bb-27dd4a7565c5", - "ae4f5816-f97a-4605-9b05-9ab820467dee" + "slide_ids": [ + "90154ea1-6b76-4445-870e-d531d6fa1239", + "1dd1cab5-5a81-428a-8153-91e8c4cf9905", + "a0826f0d-986a-491b-8c6f-b34f8929f3ee" ], - "submitter_portion_ids": [ - "TCGA-BH-A0EA-01A-11", - "TCGA-BH-A0EA-01A-21-A13C-20", - "TCGA-BH-A0EA-10A-01" + "submitter_slide_ids": [ + "TCGA-BH-A0EA-01A-01-MSA", + "TCGA-BH-A0EA-01A-01-TSA", + "TCGA-BH-A0EA-01Z-00-DX1" ], - "created_datetime": null, - "submitter_aliquot_ids": [ - "TCGA-BH-A0EA-01A-11R-A114-13", - "TCGA-BH-A0EA-01A-11D-A111-01", - "TCGA-BH-A0EA-01A-11W-A12T-09", - "TCGA-BH-A0EA-01A-11R-A114-13", - "TCGA-BH-A0EA-01A-11R-A115-07", - "TCGA-BH-A0EA-01A-11D-A111-01", - "TCGA-BH-A0EA-01A-11D-A314-09", - "TCGA-BH-A0EA-01A-11D-A112-05", - "TCGA-BH-A0EA-01A-11D-A10Y-09", - "TCGA-BH-A0EA-01A-11D-A10X-02", - "TCGA-BH-A0EA-01A-11W-A12T-09", - "TCGA-BH-A0EA-01A-11D-A10X-02", - "TCGA-BH-A0EA-01A-11D-A10Y-09", - "TCGA-BH-A0EA-01A-11D-A314-09", - "TCGA-BH-A0EA-01A-11R-A115-07", - "TCGA-BH-A0EA-01A-11D-A112-05", - "TCGA-BH-A0EA-10A-01D-A110-09", - "TCGA-BH-A0EA-10A-01D-A113-01", - "TCGA-BH-A0EA-10A-01W-A12U-09", - "TCGA-BH-A0EA-10A-01D-A10Z-02", - "TCGA-BH-A0EA-10A-01D-A113-01", - "TCGA-BH-A0EA-10A-01D-A110-09", - "TCGA-BH-A0EA-10A-01W-A12U-09", - "TCGA-BH-A0EA-10A-01D-A10Z-02" + "disease_type": "Ductal and Lobular Neoplasms", + "analyte_ids": [ + "fe678556-acf4-4bde-a95e-860bb0150a95", + "66ed0f86-5ca5-4dec-ba76-7ee4dcf31831", + "30cb470f-66d4-4085-8c30-83a42e8453d4", + "69ddc092-88a0-4839-a2bb-9f1c9e760409", + "f19f408a-815f-43d9-8032-e9482b796371" ], - "updated_datetime": "2016-05-02T14:37:43.619198-05:00", + "submitter_id": "TCGA-BH-A0EA", "submitter_analyte_ids": [ - "TCGA-BH-A0EA-01A-11R", "TCGA-BH-A0EA-01A-11D", - "TCGA-BH-A0EA-01A-11W", + "TCGA-BH-A0EA-01A-11R", "TCGA-BH-A0EA-10A-01W", + "TCGA-BH-A0EA-01A-11W", "TCGA-BH-A0EA-10A-01D" ], - "analyte_ids": [ - "30cb470f-66d4-4085-8c30-83a42e8453d4", - "66ed0f86-5ca5-4dec-ba76-7ee4dcf31831", - "f19f408a-815f-43d9-8032-e9482b796371", - "69ddc092-88a0-4839-a2bb-9f1c9e760409", - "fe678556-acf4-4bde-a95e-860bb0150a95" - ], - "submitter_id": "TCGA-BH-A0EA", - "case_id": "1f601832-eee3-48fb-acf5-80c4a454f26e", - "state": null, "aliquot_ids": [ - "bcb7fc6d-60a0-48b7-aa81-14c0dda72d76", - "97c64d6a-7dce-4d0f-9cb3-b3e4eb4719c5", - "edad5bd3-efe0-4c5f-b05c-2c0c2951c45a", - "bcb7fc6d-60a0-48b7-aa81-14c0dda72d76", - "ca71ca96-cbb7-4eab-9487-251dda34e107", - "97c64d6a-7dce-4d0f-9cb3-b3e4eb4719c5", "eef9dce1-6ba6-432b-bbe2-53c7dbe64fe7", - "42d050e4-e8ee-4442-b9c0-0ee14706b138", - "561b8777-801a-49ed-a306-e7dafeb044b6", + "2beb34c4-d493-4a73-b21e-de77d43251ff", + "b1a3739d-d554-4202-b96f-f25a444e2042", "262715e1-835c-4f16-8ee7-6900e26f7cf5", + "cfbd5476-e83a-401d-9f9a-639c73a0e35b", "edad5bd3-efe0-4c5f-b05c-2c0c2951c45a", - "262715e1-835c-4f16-8ee7-6900e26f7cf5", + "bcb7fc6d-60a0-48b7-aa81-14c0dda72d76", + "42d050e4-e8ee-4442-b9c0-0ee14706b138", + "97c64d6a-7dce-4d0f-9cb3-b3e4eb4719c5", "561b8777-801a-49ed-a306-e7dafeb044b6", - "eef9dce1-6ba6-432b-bbe2-53c7dbe64fe7", "ca71ca96-cbb7-4eab-9487-251dda34e107", - "42d050e4-e8ee-4442-b9c0-0ee14706b138", - "cfbd5476-e83a-401d-9f9a-639c73a0e35b", - "2beb34c4-d493-4a73-b21e-de77d43251ff", - "b1a3739d-d554-4202-b96f-f25a444e2042", - "cde982b7-3b0a-49eb-8710-a599cb0e44c1", - "2beb34c4-d493-4a73-b21e-de77d43251ff", - "cfbd5476-e83a-401d-9f9a-639c73a0e35b", - "b1a3739d-d554-4202-b96f-f25a444e2042", "cde982b7-3b0a-49eb-8710-a599cb0e44c1" ], - "slide_ids": [ - "90154ea1-6b76-4445-870e-d531d6fa1239", - "a0826f0d-986a-491b-8c6f-b34f8929f3ee" + "submitter_aliquot_ids": [ + "TCGA-BH-A0EA-01A-11R-A115-07", + "TCGA-BH-A0EA-01A-11D-A112-05", + "TCGA-BH-A0EA-10A-01W-A12U-09", + "TCGA-BH-A0EA-01A-11D-A10X-02", + "TCGA-BH-A0EA-10A-01D-A113-01", + "TCGA-BH-A0EA-10A-01D-A110-09", + "TCGA-BH-A0EA-01A-11D-A314-09", + "TCGA-BH-A0EA-01A-11D-A10Y-09", + "TCGA-BH-A0EA-01A-11D-A111-01", + "TCGA-BH-A0EA-10A-01D-A10Z-02", + "TCGA-BH-A0EA-01A-11R-A114-13", + "TCGA-BH-A0EA-01A-11W-A12T-09" + ], + "diagnoses": [ + { + "synchronous_malignancy": "Not Reported", + "ajcc_pathologic_stage": "Stage IIA", + "days_to_diagnosis": 0, + "created_datetime": null, + "last_known_disease_status": "not reported", + "tissue_or_organ_of_origin": "Breast, NOS", + "days_to_last_follow_up": null, + "age_at_diagnosis": 26548, + "primary_diagnosis": "Infiltrating duct carcinoma, NOS", + "updated_datetime": "2019-08-08T16:25:42.215495-05:00", + "prior_malignancy": "yes", + "year_of_diagnosis": 2008, + "state": "released", + "prior_treatment": "No", + "days_to_last_known_disease_status": null, + "ajcc_staging_system_edition": "6th", + "ajcc_pathologic_t": "T1c", + "days_to_recurrence": null, + "morphology": "8500/3", + "ajcc_pathologic_n": "N1a", + "ajcc_pathologic_m": "M0", + "submitter_id": "TCGA-BH-A0EA_diagnosis", + "classification_of_tumor": "not reported", + "diagnosis_id": "84654ad5-2a2c-5c3b-8340-ecac6a5550fe", + "icd_10_code": "C50.9", + "site_of_resection_or_biopsy": "Breast, NOS", + "tumor_grade": "Not Reported", + "progression_or_recurrence": "not reported" + } + ], + "created_datetime": null, + "diagnosis_ids": [ + "84654ad5-2a2c-5c3b-8340-ecac6a5550fe" + ], + "sample_ids": [ + "55864d86-dab8-47bb-a3e3-8cfb198b06c1", + "7f791228-dd77-4ab0-8227-d784a4c7fea1", + "9a6c71a6-82cd-42b1-a93f-f569370848d6" ], "submitter_sample_ids": [ "TCGA-BH-A0EA-01A", + "TCGA-BH-A0EA-01Z", "TCGA-BH-A0EA-10A" + ], + "primary_site": "Breast", + "submitter_diagnosis_ids": [ + "TCGA-BH-A0EA_diagnosis" + ], + "updated_datetime": "2019-08-06T14:15:54.128069-05:00", + "case_id": "1f601832-eee3-48fb-acf5-80c4a454f26e", + "state": "released", + "portion_ids": [ + "1ef8b20e-43e5-49d7-ac9a-03ce14f58daa", + "cb6086d1-3416-4310-b109-e8fa6e8b72d4", + "8629bf5a-cdaf-4f6a-90bb-27dd4a7565c5", + "ae4f5816-f97a-4605-9b05-9ab820467dee" + ], + "submitter_portion_ids": [ + "TCGA-BH-A0EA-01A-21-A13C-20", + "TCGA-BH-A0EA-10A-01", + "TCGA-BH-A0EA-01A-21", + "TCGA-BH-A0EA-01A-11" ] }, "warnings": {} } ``` -### Annotations Endpoint +### `Annotations` Endpoint The GDC Annotation Endpoint `https://api.gdc.cancer.gov/annotations` enables search and retrieval of annotations stored in the GDC. @@ -801,7 +909,7 @@ curl 'https://api.gdc.cancer.gov/annotations?filters=%7B%22op%22%3A%22in%22%2C%2 "warnings": {} } ``` -### History Endpoint +### `History` Endpoint The GDC History Endpoint `https://api.gdc.cancer.gov/history` enables search and retrieval of version and release information about a file. This endpoint will return the entire provenance of all versions of a file. A file may be versioned if a file is updated by the GDC (e.g. using a new alignment algorithm or fixing a file that contained an error). `Version` refers to the instance of a particular file. `Release` refers to which data release a file was part of. A file may be a part of many different data releases with no change in version number or content. @@ -814,11 +922,12 @@ This example is a query for versioning information associated with the follow wi curl 'https://api.gdc.cancer.gov/history/1dd28069-5777-4ff9-bd2b-d1ba68e88b06' ``` ``` Output -[{"release_date": "2018-07-23", "version": "1", "uuid": "1dd28069-5777-4ff9-bd2b-d1ba68e88b06", "file_change": "released", "data_release": "13.0"}] +[{"uuid": "1dd28069-5777-4ff9-bd2b-d1ba68e88b06", "version": "1", "file_change": "superseded", "release_date": "2018-08-23", "data_release": "12.0"}, {"uuid": "76b3f4d8-c6b7-4662-ac42-1d27d4684281", "version": "2", "file_change": "released", "release_date": "2022-03-29", "data_release": "32.0"}] + ``` -### \_mapping Endpoint +### `_mapping` Endpoint Each search and retrieval endpoint is equipped with a ```_mapping``` endpoint that provides information about available fields. For example, `files/_mapping` endpoint provides information about fields and field groups available at the `files` endpoint: `https://api.gdc.cancer.gov/files/_mapping`. @@ -851,23 +960,24 @@ Each part of the response is described below: curl 'https://api.gdc.cancer.gov/projects/_mapping' ``` ```output +This output was put thought a json format application for easier viewability. { - ... + ... - "_mapping": { - "projects.disease_type": { - "doc_type": "projects", - "field": "disease_type", - "type": "id" - }, - "projects.name": { - "doc_type": "projects", - "field": "name", - "type": "id" - } - } + "_mapping": { + "projects.disease_type": { + "doc_type": "projects", + "field": "disease_type", + "type": "id" + }, + "projects.name": { + "doc_type": "projects", + "field": "name", + "type": "id" + } + } - ... + ... } ``` @@ -967,16 +1077,19 @@ This example requests `male` cases using HTTP GET. The JSON object to be passed to the GDC API looks like: - {"op": "=", - "content": { - "field": "cases.demographic.gender", - "value": ["male"] - } - } + { + "op": "=", + "content": { + "field": "cases.demographic.gender", + "value": [ + "male" + ] + } + } -URL-encoding the above JSON object using [Percent-(URL)-encoding tool](https://www.beautifyconverter.com/json-escape-unescape.php) results in the following string: +URL-encoding the above JSON object using [Percent-(URL)-encoding tool](https://www.freeformatter.com/url-encoder.html) results in the following string: - %7b%22op%22%3a+%22%3d%22%2c%0d%0a++++++%22content%22%3a+%7b%0d%0a++++++++++%22field%22%3a+%22cases.clinical.gender%22%2c%0d%0a++++++++++%22value%22%3a+%5b%22male%22%5d%0d%0a++++++%7d%0d%0a%7d + %7B%0D%0A++++%22op%22%3A+%22%3D%22%2C%0D%0A++++%22content%22%3A+%7B%0D%0A++++++++%22field%22%3A+%22cases.demographic.gender%22%2C%0D%0A++++++++%22value%22%3A+%5B%0D%0A++++++++++++%22male%22%0D%0A++++++++%5D%0D%0A++++%7D%0D%0A%7D The above string can now be passed to the GDC API using the `filters` parameter: @@ -996,697 +1109,785 @@ filt = {"op":"=", params = {'filters':json.dumps(filt), 'sort':'demographic.gender:asc'} # requests URL-encodes automatically response = requests.get(cases_endpt, params = params) -print json.dumps(response.json(), indent=2) +print(json.dumps(response.json(), indent=2)) ``` ``` Output { "data": { "hits": [ { - "sample_ids": [ - "1d014bf1-95ae-42e3-ae39-97ff4841d8ca", - "6b685bfc-651b-48d1-8e68-32c8096ea205" + "id": "03974dc9-0162-4de8-9897-09f88693681a", + "lost_to_followup": null, + "days_to_lost_to_followup": null, + "disease_type": "Nevi and Melanomas", + "analyte_ids": [ + "9747b614-624b-410a-8b94-854a16cd143a", + "c8974764-4836-4a34-aeb8-52b491f78d0e", + "bcea1ed5-b9cb-4a92-ad80-598d8a223fb3" ], - "portion_ids": [ - "c061217a-266a-496d-8a96-3489191afa87", - "0d3a6a58-0e00-4889-bc73-5ddb5a387738", - "e858ee92-0438-48e9-a70d-80ef2c0ad539" + "submitter_id": "HCM-BROD-0334-C43", + "submitter_analyte_ids": [ + "HCM-BROD-0334-C43-10A-01D", + "HCM-BROD-0334-C43-85M-01D", + "HCM-BROD-0334-C43-85M-01R" ], - "submitter_portion_ids": [ - "TCGA-66-2770-01A-21-2193-20", - "TCGA-66-2770-01A-01", - "TCGA-66-2770-11A-01" + "days_to_consent": null, + "aliquot_ids": [ + "dcd74e48-12f3-4a86-a829-c7e055c215b7", + "ea182abf-041d-474a-bc53-f6fdd05cd999", + "33f3ba0a-c902-4288-9fa7-5696d959e51d" ], - "created_datetime": null, "submitter_aliquot_ids": [ - "TCGA-66-2770-01A-01D-1522-08", - "TCGA-66-2770-01A-01D-0848-05", - "TCGA-66-2770-01A-01W-0879-09", - "TCGA-66-2770-11A-01W-0878-08", - "TCGA-66-2770-01A-01R-0849-01", - "TCGA-66-2770-01A-01W-0877-08", - "TCGA-66-2770-01A-01D-0846-06", - "TCGA-66-2770-11A-01W-0880-09", - "TCGA-66-2770-01A-01D-0964-09", - "TCGA-66-2770-11A-01D-0846-06", - "TCGA-66-2770-01A-01D-0845-04", - "TCGA-66-2770-01A-01W-0881-10", - "TCGA-66-2770-11A-01D-0963-08", - "TCGA-66-2770-11A-01D-0844-01", - "TCGA-66-2770-01A-01R-0851-07", - "TCGA-66-2770-11A-01W-0882-10", - "TCGA-66-2770-11A-01D-1522-08", - "TCGA-66-2770-01A-01T-1557-13", - "TCGA-66-2770-01A-01D-0847-02", - "TCGA-66-2770-01A-01D-0844-01", - "TCGA-66-2770-11A-01D-0847-02", - "TCGA-66-2770-11A-01D-0964-09", - "TCGA-66-2770-01A-01D-0963-08", - "TCGA-66-2770-01A-01R-0850-03", - "TCGA-66-2770-11A-01D-0845-04", - "TCGA-66-2770-01A-01T-0852-07" - ], - "updated_datetime": "2016-05-02T15:57:03.730994-05:00", - "submitter_analyte_ids": [ - "TCGA-66-2770-01A-01D", - "TCGA-66-2770-11A-01W", - "TCGA-66-2770-01A-01T", - "TCGA-66-2770-01A-01W", - "TCGA-66-2770-01A-01R", - "TCGA-66-2770-11A-01D" + "HCM-BROD-0334-C43-85M-01R-A79O-41", + "HCM-BROD-0334-C43-10A-01D-A79L-36", + "HCM-BROD-0334-C43-85M-01D-A79L-36" ], - "analyte_ids": [ - "385807d3-78de-4558-8d93-702d93fc835a", - "247acc7a-b4f5-47e9-86da-5ea9b04ad444", - "151b8cb9-6b0a-4db9-9b0e-62aa501b35d9", - "e549aebd-4dda-4ea8-8ccf-56c03bc8b2be", - "631ad4eb-845a-4e70-96ad-4b40157218a8", - "9a75640e-09d4-42b7-8cb4-75d62b39e98a" - ], - "submitter_id": "TCGA-66-2770", - "case_id": "f1b357e4-d67a-42c9-b0b7-12f69fa3da58", - "state": null, - "aliquot_ids": [ - "a2d10f8e-6b27-4df0-bd25-ac24992d0bb4", - "8c1c733a-abed-468f-b4d0-d1ac34ba6d8b", - "cad8d384-3b7a-4f70-89c2-5584ae75c5eb", - "42e774cf-3c4a-4efd-9665-378cb6b4afac", - "3755168b-f5da-422d-847a-566cb112a8d7", - "cae4d249-ba67-4316-8761-7e71e3813182", - "aa6e700c-ce01-4cc9-87de-8bf615a8aa1a", - "ad5c4069-e616-4ab4-9b03-b196f9189b20", - "07c26ea4-0584-4cb0-8e5a-d057b8fe6c14", - 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"slide_ids": [ - "2310e34c-0ea5-4876-9f87-bad0b7a44513" + "submitter_aliquot_ids": [ + "HCM-SANG-0299-C15-85B-01D-A80T-32-aliquot", + "HCM-SANG-0299-C15-10A-01D-A80T-32-aliquot", + "HCM-SANG-0299-C15-85A-01R-A78V-41", + "HCM-SANG-0299-C15-85A-01D-A78U-36", + "HCM-SANG-0299-C15-85A-01R-A80W-32-aliquot", + "HCM-SANG-0299-C15-85X-01D-A78U-36", + "HCM-SANG-0299-C15-85X-01R-A78V-41", + "HCM-SANG-0299-C15-85A-01D-A80T-32-aliquot", + "HCM-SANG-0299-C15-01A-01D-A80T-32-aliquot", + "HCM-SANG-0299-C15-85B-01R-A80W-32-aliquot", + "HCM-SANG-0299-C15-10B-01D-A78U-36" + ], + "created_datetime": "2019-10-14T10:46:36.257369-05:00", + "diagnosis_ids": [ + "7c6aa4ce-6661-4491-a827-c0a8045743a6", + "c1a6f70f-b871-4b4e-a292-aef67c2d4776" ], - "submitter_sample_ids": [ - "TCGA-QR-A70H-01A", - "TCGA-QR-A70H-10A" - ] - }, - { "sample_ids": [ - "19dee039-9c98-4d4a-8baf-eea1b6dda8eb", - "fdf1e501-f34f-450c-9a5c-611157079a86" + "c56f3f94-deda-4d21-8f8e-658108995dfa", + "ce46b9f4-5244-432d-aa87-026e0a27d71a", + "cf134dfb-5126-4bee-bcab-39d584335a21", + "34e0d6ee-97f5-420f-9b34-4784098125f7", + "ac8476c1-53bf-43b5-8695-db441ed1a720", + "9000b366-a14b-44bc-a782-484e09765b2d", + "8541bc01-57e6-4bf7-a42e-da1c8e790633", + "277d7ed9-4e6a-429b-8f4e-438ff0d2ba7a", + "d12d9184-5317-4730-af2e-a8428456a2a7" ], + "submitter_sample_ids": [ + "HCM-SANG-0299-C15-85X", + "HCM-SANG-0299-C15-85B-01D-A80T-32", + "HCM-SANG-0299-C15-85A-01R-A80W-32", + "HCM-SANG-0299-C15-10B", + "HCM-SANG-0299-C15-01A-01D-A80T-32", + "HCM-SANG-0299-C15-85A", + "HCM-SANG-0299-C15-85A-01D-A80T-32", + "HCM-SANG-0299-C15-85B-01R-A80W-32", + "HCM-SANG-0299-C15-10A-01D-A80T-32" + ], + "primary_site": "Esophagus", + "submitter_diagnosis_ids": [ + "HCM-SANG-0299-C15_diagnosis2", + "HCM-SANG-0299-C15_diagnosis" + ], + "updated_datetime": "2023-02-22T07:39:25.979291-06:00", + "case_id": "19b1e69a-355a-4dd7-9c56-d701f6c2c5a0", + "index_date": "Sample Procurement", + "state": "released", "portion_ids": [ - "10b6ccb4-3637-4769-8988-417c0306eaef", - "92f8cd48-451d-4ed6-8e60-b15aa93d2c09", - "d0d55efa-c91d-45de-92bf-cf6f0d263b21" + "b8192c57-9cda-4dca-a590-1e13beadf2a0" ], "submitter_portion_ids": [ - "TCGA-BJ-A18Z-01A-21", - "TCGA-BJ-A18Z-01A-11-A21L-20", - "TCGA-BJ-A18Z-10A-01" + "HCM-SANG-0299-C15-10B-01" + ] + }, + { + "id": "19f1d344-4c14-4733-abbd-c2db6737e210", + "lost_to_followup": null, + "days_to_lost_to_followup": null, + "disease_type": "Ductal and Lobular Neoplasms", + "analyte_ids": [ + "a21d5f05-af57-41bf-ab60-32d2c869611b", + "696f4b03-5f0d-4eaa-975d-a9feb64dae07", + "c8d4fb23-c55d-4bb6-bd3d-fc1f159d7a33", + "5db09eb8-fecc-433f-aa34-a12a7c9333dd", + "51598aba-be8e-42a0-bf6c-aca34776fc1f" ], - "created_datetime": null, - "submitter_aliquot_ids": [ - "TCGA-BJ-A18Z-01A-21D-A13U-02", - "TCGA-BJ-A18Z-10A-01D-A13V-01", - "TCGA-BJ-A18Z-01A-21R-A13Y-07", - "TCGA-BJ-A18Z-01A-21W-A14T-08", - "TCGA-BJ-A18Z-01A-21D-A13Z-05", - "TCGA-BJ-A18Z-01A-21D-A37T-08", - "TCGA-BJ-A18Z-10A-01D-A13W-08", - "TCGA-BJ-A18Z-01A-21R-A13X-13", - "TCGA-BJ-A18Z-01A-21D-A13W-08", - "TCGA-BJ-A18Z-10A-01D-A13U-02", - "TCGA-BJ-A18Z-10A-01W-A14T-08", - "TCGA-BJ-A18Z-01A-21D-A13V-01" - ], - "updated_datetime": "2016-05-02T16:18:19.199189-05:00", + "submitter_id": "HCM-CSHL-0081-C25", "submitter_analyte_ids": [ - "TCGA-BJ-A18Z-01A-21W", - "TCGA-BJ-A18Z-01A-21D", - "TCGA-BJ-A18Z-01A-21R", - "TCGA-BJ-A18Z-10A-01D", - "TCGA-BJ-A18Z-10A-01W" + "HCM-CSHL-0081-C25-11A-11D", + "HCM-CSHL-0081-C25-85A-01R", + "HCM-CSHL-0081-C25-85B-01D", + "HCM-CSHL-0081-C25-01A-11R", + "HCM-CSHL-0081-C25-01A-11D" ], - "analyte_ids": [ - "119ebfa1-75b2-4f24-816a-4e9a5061f6b5", - "f86759fd-ecc5-4f42-b5fe-b9f079d23968", - "39691042-bd28-40ed-b66b-26414ecf1ba0", - "76ea5056-d7fa-49fb-94bf-11171ca7c100", - "71a822c9-b510-4a4c-8c30-18b8083acc2d" - ], - "submitter_id": "TCGA-BJ-A18Z", - "case_id": "0d497faf-2c1c-4173-a5fe-770cca73323c", - "state": null, "aliquot_ids": [ - "fa580596-e70f-4ed0-85a2-6fb594ca679a", - "776cb4b1-8efd-4ea2-b53f-9dff7dd94b10", - "85a7922f-0327-437c-bdf5-1bb67a1e932f", - "6d532180-0175-4610-8bfa-cca3a7c3697a", - "b5977e73-49d8-4e99-9e97-993cc44dad17", - "918793fa-b35e-4745-ac75-4d1c868089f8", - "ba9479a1-929f-4e4e-8bf5-e23cb280dfcf", - "e9776ff5-69b9-4669-ab33-e4bb030461ec", - "8ba98907-ab03-4c9e-a900-e31aa16ff810", - "35e18649-183e-4223-b2f6-d812bdd9becd", - "4aa17671-4420-4989-a6dd-379250f4aeda", - "815c53c3-8add-4612-b93c-3ed4bfa530aa" + "0a65e1bd-6af3-44ba-924c-193eb8e099d6", + "61112c39-c838-4f84-89c7-a33bfe5dea88", + "25cd08c3-09a9-406d-8ec3-ab4946224cf1", + "973d4fa3-4fa7-4ff9-8176-cc51c53b7079", + "9aa21acf-1e24-4b7a-a3c1-73354bdd81b6" ], - "slide_ids": [ - "7c5b5c77-9fbc-4b48-81f5-48b5ede7c436" + "submitter_aliquot_ids": [ + "HCM-CSHL-0081-C25-11A-11D-A78M-36", + "HCM-CSHL-0081-C25-01A-11R-A78N-41", + "HCM-CSHL-0081-C25-85B-01D-A78M-36", + "HCM-CSHL-0081-C25-01A-11D-A78M-36", + "HCM-CSHL-0081-C25-85A-01R-A78N-41" + ], + "created_datetime": "2019-09-19T08:58:31.776805-05:00", + "diagnosis_ids": [ + "c1cca3a7-e0ac-40a1-9db7-6902b48d3c62" + ], + "sample_ids": [ + "d9f23187-9a29-426a-9ead-4bb3a2ce6cf9", + "3709004e-b04d-4473-aa29-8dd84176d17d", + "adcc54e3-074b-4ca6-b179-0a5df8efeb36", + "05478d15-885a-4c44-a46a-81bbe6c9ee11" ], "submitter_sample_ids": [ - "TCGA-BJ-A18Z-01A", - "TCGA-BJ-A18Z-10A" + "HCM-CSHL-0081-C25-85B", + "HCM-CSHL-0081-C25-01A", + "HCM-CSHL-0081-C25-85A", + "HCM-CSHL-0081-C25-11A" + ], + "primary_site": "Pancreas", + "submitter_diagnosis_ids": [ + "HCM-CSHL-0081-C25_diagnosis" + ], + "updated_datetime": "2023-02-22T07:39:25.979291-06:00", + "case_id": "19f1d344-4c14-4733-abbd-c2db6737e210", + "index_date": "Diagnosis", + "state": "released", + "portion_ids": [ + "d9588542-d7ef-413e-900c-3f816b583525", + "b77573f1-e6a3-43c1-a56d-a207c39e18c4" + ], + "submitter_portion_ids": [ + "HCM-CSHL-0081-C25-01A-11", + "HCM-CSHL-0081-C25-11A-11" ] } ], "pagination": { "count": 10, - "sort": "", + "total": 40232, + "size": 10, "from": 0, + "sort": "", "page": 1, - "total": 6340, - "pages": 634, - "size": 10 + "pages": 4024 } }, "warnings": {} @@ -1697,7 +1898,7 @@ print json.dumps(response.json(), indent=2) #### Example: HTTP POST Request -This example demonstrates how to obtain metadata in TSV format for a set of files using their UUIDs (e.g. UUIDs obtained from a [download manifest file generated by the GDC Data Portal](/Data_Portal/Users_Guide/Cart/#gdc-data-transfer-tool)). +This example demonstrates how to obtain metadata in TSV format for a set of files using their UUIDs (e.g. UUIDs obtained from a [download manifest file generated by the GDC Data Portal](/Data_Portal/Users_Guide/Repository.md#generating-a-manifest-file-for-the-data-transfer-tool)). The first step is to construct a JSON query object, including `filters`, `fields`, `format`, and `size` parameters. The object is then submitted as HTTP POST payload to the GDC API using curl, in order to retrieve a TSV file with the requested metadata. @@ -1770,15 +1971,16 @@ cases_endpt = 'https://api.gdc.cancer.gov/cases' params = {'fields':'submitter_id', 'format':'TSV'} response = requests.get(cases_endpt, params = params) -print response.content +print(response.content) ``` ```response1 -submitter_id -TCGA-RC-A6M6 -TCGA-B6-A0RV -TCGA-MB-A5Y8 -TCGA-BQ-5876 -TCGA-Z6-A9VB +id submitter_id +0286c31b-a704-4d7d-99e3-0bc4e8975b8b HCM-CSHL-0084-C25 +02f6d684-b6b5-419a-b0e1-b74d0a384a30 HCM-BROD-0408-C71 +03974dc9-0162-4de8-9897-09f88693681a HCM-BROD-0334-C43 +03bfeb7c-cecf-4691-8263-33cdfe391ea9 HCM-BROD-0124-C25 +04cbceab-f945-482b-956b-840756a17a4a HCM-BROD-0421-C71 + ``` ```shell2 curl 'https://api.gdc.cancer.gov/cases?fields=submitter_id&size=5&format=XML&pretty=true' @@ -1791,7 +1993,7 @@ params = {'fields':'submitter_id', 'format':'XML', 'pretty':'true'} response = requests.get(cases_endpt, params = params) -print response.content +print(response.content) ``` ```Output2 @@ -1799,29 +2001,34 @@ print response.content - TCGA-MQ-A4LV + 0286c31b-a704-4d7d-99e3-0bc4e8975b8b + HCM-CSHL-0084-C25 - TCGA-N9-A4Q1 + 02f6d684-b6b5-419a-b0e1-b74d0a384a30 + HCM-BROD-0408-C71 - TCGA-78-7154 + 03974dc9-0162-4de8-9897-09f88693681a + HCM-BROD-0334-C43 - TCGA-S7-A7WX + 03bfeb7c-cecf-4691-8263-33cdfe391ea9 + HCM-BROD-0124-C25 - TCGA-XF-AAML + 04cbceab-f945-482b-956b-840756a17a4a + HCM-BROD-0421-C71 5 - + 86962 + 5 0 - 2811 - 14052 + 1 - 5 + 17393 @@ -1838,7 +2045,7 @@ Returns when the `pretty` parameter is set to `true`, the API response is format curl 'https://api.gdc.cancer.gov/cases?fields=submitter_id&sort=submitter_id:asc&size=5' ``` ```Response1 -{"data": {"hits": [{"id": "f7af65fc-97e3-52ce-aa2c-b707650e747b", "submitter_id": "TARGET-00-NAAEMA"}, {"id": "513d0a2a-3c94-5a36-97a4-24c3656fc66e", "submitter_id": "TARGET-00-NAAEMB"}, {"id": "b5f20676-727b-50b0-9b5a-582cd8572d6d", "submitter_id": "TARGET-00-NAAEMC"}, {"id": "0c0b183f-0d4a-5a9d-9888-0617cebcc462", "submitter_id": "TARGET-20-PABGKN"}, {"id": "0f5ed7a7-226d-57bc-a4ce-8a6b18560c55", "submitter_id": "TARGET-20-PABHET"}], "pagination": {"count": 5, "sort": "submitter_id:asc", "from": 0, "page": 1, "total": 14551, "pages": 2911, "size": 5}}, "warnings": {}} +{"data": {"hits": [{"id": "be37f1f7-2f98-4f74-bc04-6dd2ae2afcad", "submitter_id": "01BR001"}, {"id": "e6915db0-7c89-484d-8f9f-15cca68b82fc", "submitter_id": "01BR008"}, {"id": "16614d46-172b-479c-992b-e80a8e9a2c59", "submitter_id": "01BR009"}, {"id": "567fc9e3-17a6-42b1-a896-5e9a9507d1d8", "submitter_id": "01BR010"}, {"id": "54e89878-a1bc-4f5a-9d68-4842a469586e", "submitter_id": "01BR015"}], "pagination": {"count": 5, "total": 86962, "size": 5, "from": 0, "sort": "None", "page": 1, "pages": 17393}}, "warnings": {}} ``` ```Request2 curl 'https://api.gdc.cancer.gov/cases?fields=submitter_id&sort=submitter_id:asc&size=5&pretty=true' @@ -1848,34 +2055,34 @@ curl 'https://api.gdc.cancer.gov/cases?fields=submitter_id&sort=submitter_id:as "data": { "hits": [ { - "id": "f7af65fc-97e3-52ce-aa2c-b707650e747b", - "submitter_id": "TARGET-00-NAAEMA" + "id": "be37f1f7-2f98-4f74-bc04-6dd2ae2afcad", + "submitter_id": "01BR001" }, { - "id": "513d0a2a-3c94-5a36-97a4-24c3656fc66e", - "submitter_id": "TARGET-00-NAAEMB" + "id": "e6915db0-7c89-484d-8f9f-15cca68b82fc", + "submitter_id": "01BR008" }, { - "id": "b5f20676-727b-50b0-9b5a-582cd8572d6d", - "submitter_id": "TARGET-00-NAAEMC" + "id": "16614d46-172b-479c-992b-e80a8e9a2c59", + "submitter_id": "01BR009" }, { - "id": "0c0b183f-0d4a-5a9d-9888-0617cebcc462", - "submitter_id": "TARGET-20-PABGKN" + "id": "567fc9e3-17a6-42b1-a896-5e9a9507d1d8", + "submitter_id": "01BR010" }, { - "id": "0f5ed7a7-226d-57bc-a4ce-8a6b18560c55", - "submitter_id": "TARGET-20-PABHET" + "id": "54e89878-a1bc-4f5a-9d68-4842a469586e", + "submitter_id": "01BR015" } ], "pagination": { "count": 5, - "sort": "submitter_id:asc", + "total": 86962, + "size": 5, "from": 0, + "sort": "None", "page": 1, - "total": 14551, - "pages": 2911, - "size": 5 + "pages": 17393 } }, "warnings": {} @@ -1900,121 +2107,131 @@ import json files_endpt = 'https://api.gdc.cancer.gov/files' params = {'fields':'cases.submitter_id,file_id,file_name,file_size'} response = requests.get(files_endpt, params = params) -print json.dumps(response.json(), indent=2) +print(json.dumps(response.json(), indent=2)) ``` ```Response { "data": { "hits": [ { - "file_name": "NARKY_p_TCGAb69_SNP_N_GenomeWideSNP_6_H03_697832.grch38.seg.txt", + "id": "d570eccc-3c1c-4c4f-ae04-96be71fbe016", "cases": [ { - "submitter_id": "TCGA-BP-4989" + "submitter_id": "TCGA-AN-A0FL" } ], - "file_id": "3bd4d5dc-563a-481c-87a6-ec0017d0d58a", - "file_size": 54200 + "file_name": "TCGA-AN-A0FL-01Z-00-DX1.20A041C6-A306-4599-A7D1-65032A252AA9.svs", + "file_id": "d570eccc-3c1c-4c4f-ae04-96be71fbe016", + "file_size": 1055798681 }, { - "file_name": "652ecf99-1af9-41fc-b0a5-d3e5c07a7b5d.FPKM.txt.gz", + "id": "0f8d8202-a1ca-4ea1-98b2-c20a6b08479a", "cases": [ { - "submitter_id": "TCGA-60-2709" + "submitter_id": "TCGA-AN-A0FL" } ], - "file_id": "b3286166-01f9-4149-81b5-a2ea5f27c50e", - "file_size": 530665 + "file_name": "nationwidechildrens.org_ssf.TCGA-AN-A0FL.xml", + "file_id": "0f8d8202-a1ca-4ea1-98b2-c20a6b08479a", + "file_size": 15519 }, { - "file_name": "CUSKS_p_TCGAb47_SNP_1N_GenomeWideSNP_6_D05_628212.nocnv_grch38.seg.txt", + "id": "b76f87b3-99c5-4297-b2df-8cbea8ecaf61", "cases": [ { - "submitter_id": "TCGA-A8-A07Z" + "submitter_id": "TCGA-BH-A18F" } ], - "file_id": "282cc9d1-c5e9-49ff-b27b-e00c1e5529c6", - "file_size": 15806 + "file_name": "7c4e4c2a-a0b1-424f-97d8-359825674429.wxs.aliquot_ensemble_masked.maf.gz", + "file_id": "b76f87b3-99c5-4297-b2df-8cbea8ecaf61", + "file_size": 21571 }, { - "file_name": "REEDY_p_TCGAb65_SNP_N_GenomeWideSNP_6_F01_697686.nocnv_grch38.seg.txt", + "id": "be6d269d-4305-4643-b98e-af703a067761", "cases": [ { - "submitter_id": "TCGA-CJ-4871" + "submitter_id": "TCGA-BH-A18F" } ], - "file_id": "fe44a644-eefc-42c5-aac7-a216bc1e88e1", - "file_size": 6179 + "file_name": "HITCH_p_TCGASNP_b93_N_GenomeWideSNP_6_E11_741424.CEL", + "file_id": "be6d269d-4305-4643-b98e-af703a067761", + "file_size": 69084893 }, { - "file_name": "84df7a8fee9fedb5e8e22849ec66d294_gdc_realn.bam", + "id": "fed73119-1d5e-4f7e-9713-183d1916422b", "cases": [ { - "submitter_id": "TCGA-A2-A0CO" + "submitter_id": "TCGA-BH-A18F" } ], - "file_id": "acd0ec73-c1fe-463e-912c-84e8416510e5", - "file_size": 15545555724 + "file_name": "3b928f83-14a7-4bd6-a9b0-744b414d4495.wxs.varscan2.raw_somatic_mutation.vcf.gz", + "file_id": "fed73119-1d5e-4f7e-9713-183d1916422b", + "file_size": 35903 }, { - "file_name": "ed8c4bb6-891a-4cf2-80ba-42c5594760d0.vcf", + "id": "6877b045-91f1-4030-82ff-b90507e11e17", "cases": [ { - "submitter_id": "TCGA-BQ-7059" + "submitter_id": "TCGA-BH-A18F" } ], - "file_id": "ed8c4bb6-891a-4cf2-80ba-42c5594760d0", - "file_size": 264694 + "file_name": "5057e3cb-25cd-4a67-8d31-6ac8508ba3c7.methylation_array.sesame.level3betas.txt", + "file_id": "6877b045-91f1-4030-82ff-b90507e11e17", + "file_size": 770500 }, { - "file_name": "nationwidechildrens.org_clinical.TCGA-IG-A6QS.xml", + "id": "07e8cdc7-d228-4752-ad19-800abd507277", "cases": [ { - "submitter_id": "TCGA-IG-A6QS" + "submitter_id": "TCGA-BH-A0BM" } ], - "file_id": "fe8cf009-f033-4536-95c7-836adcba5bf3", - "file_size": 36996 + "file_name": "TCGA-BRCA.28dcad29-448e-4bcb-911d-556c6f4a5573.star_fusion.rna_fusion.tsv", + "file_id": "07e8cdc7-d228-4752-ad19-800abd507277", + "file_size": 234 }, { - "file_name": "05f6f9f7-6fb7-4c95-b79c-fdfaba16539d.vep.reheader.vcf.gz", + "id": "fef57b45-ede1-49b0-b60d-957a55a15e0e", "cases": [ { - "submitter_id": "TCGA-DK-A3IV" + "submitter_id": "TCGA-BH-A0BM" } ], - "file_id": "05f6f9f7-6fb7-4c95-b79c-fdfaba16539d", - "file_size": 415044 + "file_name": "nationwidechildrens.org_biospecimen.TCGA-BH-A0BM.xml", + "file_id": "fef57b45-ede1-49b0-b60d-957a55a15e0e", + "file_size": 127218 }, { - "file_name": "C484.TCGA-12-5301-01A-01D-1486-08.7_gdc_realn.bam", + "id": "81a1b323-88b6-4837-bccf-ac84a79828b6", "cases": [ { - "submitter_id": "TCGA-12-5301" + "submitter_id": "TCGA-BH-A0BM" } ], - "file_id": "3b0293c2-4a26-428c-b097-9489f23a2a2d", - "file_size": 23661175335 + "file_name": "TCGA-BRCA.4570b87f-8116-48bf-86d3-b993536c88db.gene_level_copy_number.v36.tsv", + "file_id": "81a1b323-88b6-4837-bccf-ac84a79828b6", + "file_size": 3446816 }, { - "file_name": "75a36e71-400d-46a5-93b0-7813cf0595ea.FPKM.txt.gz", + "id": "c6bf94a6-9940-4155-86b4-bbb10875dbdb", "cases": [ { - "submitter_id": "TCGA-BF-A5EO" + "submitter_id": "TCGA-BH-A18F" } ], - "file_id": "28f763c7-8064-4151-ae0e-31e70cd9bfe8", - "file_size": 488422 + "file_name": "TCGA-BRCA.88cae21a-4890-4fdd-a678-c4864620942c.star_fusion.rna_fusion.bedpe", + "file_id": "c6bf94a6-9940-4155-86b4-bbb10875dbdb", + "file_size": 229 } ], "pagination": { "count": 10, - "sort": "", + "total": 931947, + "size": 10, "from": 0, + "sort": "", "page": 1, - "total": 216435, - "pages": 21644, - "size": 10 + "pages": 93195 } }, "warnings": {} @@ -2028,64 +2245,77 @@ The `expand` parameter provides a shortcut to request multiple related fields (f #### Example ```Shell -curl 'https://api.gdc.cancer.gov/files/ac2ddebd-5e5e-4aea-a430-5a87c6d9c878?expand=cases.samples&pretty=true' -``` +curl 'https://api.gdc.cancer.gov/files/573ee7e9-b8bd-419e-808b-a027c4311731?expand=cases.samples&pretty=true' ``` +```Response { "data": { - "data_type": "Aligned Reads", - "updated_datetime": "2016-09-18T04:25:13.163601-05:00", - "created_datetime": "2016-05-26T18:55:53.506549-05:00", - "file_name": "000aa811c15656604161e8f0e3a0aae4_gdc_realn.bam", - "md5sum": "200475f5f6e42520204e5f6aadfe954f", - "data_format": "BAM", + "proportion_reads_mapped": 0.9648433596149857, + "access": "controlled", + "proportion_base_mismatch": 0.004117986, + "contamination_error": 0, "acl": [ "phs000178" ], - "access": "controlled", + "type": "aligned_reads", "platform": "Illumina", - "state": "submitted", - "file_id": "ac2ddebd-5e5e-4aea-a430-5a87c6d9c878", - "data_category": "Raw Sequencing Data", - "file_size": 12667634731, + "created_datetime": "2022-05-12T14:42:10.014925-05:00", + "updated_datetime": "2022-11-01T11:52:54.136033-05:00", + "pairs_on_diff_chr": 1170013, + "state": "released", + "data_format": "BAM", + "total_reads": 379313036, + "proportion_coverage_30x": 0.000109, "cases": [ { "samples": [ { - "sample_type_id": "11", - "updated_datetime": "2016-09-08T11:00:45.021005-05:00", + "sample_type_id": "10", + "tumor_descriptor": "Not Reported", + "sample_id": "4e128a37-be58-477a-a01f-448179360b7c", + "sample_type": "Blood Derived Normal", + "tumor_code": null, + "created_datetime": null, "time_between_excision_and_freezing": null, - "oct_embedded": "false", - "tumor_code_id": null, - "submitter_id": "TCGA-QQ-A5VA-11A", + "composition": "Not Reported", + "updated_datetime": "2022-04-28T22:05:09.013808-05:00", + "days_to_collection": 6755, + "state": "released", + "initial_weight": null, + "preservation_method": null, "intermediate_dimension": null, - "sample_id": "b4e7558d-898e-4d68-a897-381edde0bbcc", - "is_ffpe": false, - "pathology_report_uuid": null, - "created_datetime": null, - "tumor_descriptor": null, - "sample_type": "Solid Tissue Normal", - "state": null, - "current_weight": null, - "composition": null, "time_between_clamping_and_freezing": null, + "freezing_method": null, + "pathology_report_uuid": null, + "submitter_id": "TCGA-B6-A0RI-10A", + "tumor_code_id": null, "shortest_dimension": null, - "tumor_code": null, - "tissue_type": null, + "oct_embedded": "false", "days_to_sample_procurement": null, - "freezing_method": null, - "preservation_method": null, - "days_to_collection": 5980, - "initial_weight": 810.0, - "longest_dimension": null + "longest_dimension": null, + "current_weight": null, + "is_ffpe": false, + "tissue_type": "Not Reported" } ] } ], - "submitter_id": "32872121-d38a-4128-b96a-698a6f18f29d", - "type": "aligned_reads", - "file_state": "processed", - "experimental_strategy": "WXS" + "file_name": "c9478f7d-bfe3-4e80-8161-39b3d440fa16_wgs_gdc_realn.bam", + "mean_coverage": 5.452655, + "proportion_reads_duplicated": 0.009253781617987946, + "submitter_id": "a4e380e5-420e-49af-986d-e721601065fb", + "data_category": "Sequencing Reads", + "proportion_coverage_10x": 0.07674, + "file_size": 42958286722, + "contamination": 0, + "average_base_quality": 32, + "file_id": "573ee7e9-b8bd-419e-808b-a027c4311731", + "data_type": "Aligned Reads", + "average_insert_size": 207, + "average_read_length": 51, + "experimental_strategy": "WGS", + "version": "1", + "data_release": "36.0 - 37.0" }, "warnings": {} } @@ -2114,7 +2344,7 @@ files_endpt = 'https://api.gdc.cancer.gov/files' params = {'fields':'file_name', 'from':0, 'size':2} response = requests.get(files_endpt, params = params) -print json.dumps(response.json(), indent=2) +print(json.dumps(response.json(), indent=2)) ``` ```Response1 @@ -2122,20 +2352,22 @@ print json.dumps(response.json(), indent=2) "data": { "hits": [ { - "file_name": "unc.edu.276a1e00-cf3a-4463-a97b-d544381219ea.2363081.rsem.isoforms.normalized_results" + "id": "d570eccc-3c1c-4c4f-ae04-96be71fbe016", + "file_name": "TCGA-AN-A0FL-01Z-00-DX1.20A041C6-A306-4599-A7D1-65032A252AA9.svs" }, { - "file_name": "nationwidechildrens.org_clinical.TCGA-EY-A5W2.xml" + "id": "0f8d8202-a1ca-4ea1-98b2-c20a6b08479a", + "file_name": "nationwidechildrens.org_ssf.TCGA-AN-A0FL.xml" } ], "pagination": { "count": 2, - "sort": "", + "total": 931947, + "size": 2, "from": 0, - "pages": 300936, - "total": 601872, + "sort": "", "page": 1, - "size": 2 + "pages": 465974 } }, "warnings": {} @@ -2152,41 +2384,41 @@ files_endpt = 'https://api.gdc.cancer.gov/files' params = {'fields':'file_name', 'from':101, 'size':5} response = requests.get(files_endpt, params = params) -print json.dumps(response.json(), indent=2) +print(json.dumps(response.json(), indent=2)) ``` ``` Output2 { "data": { "hits": [ { - "file_name": "OCULI_p_TCGA_159_160_SNP_N_GenomeWideSNP_6_E09_831242.grch38.seg.txt", - "id": "1d959137-d8e6-4336-b357-8ab9c88eeca8" + "id": "297933f5-1316-4cb6-b53f-9dbfa7f3d7ed", + "file_name": "TCGA-B6-A0RH-01A-02-TSB.ea83f31e-defb-4436-8a58-5b66b18d13b5.svs" }, { - "file_name": "jhu-usc.edu_SKCM.HumanMethylation450.3.lvl-3.TCGA-EE-A3JI-06A-11D-A21B-05.gdc_hg38.txt", - "id": "9c02ec95-4aa3-4112-8823-c0fa87f71773" + "id": "2f31e897-b3e8-49f1-a400-ccf9f00f294a", + "file_name": "URAEI_p_TCGASNP_b85_N_GenomeWideSNP_6_F01_735050.grch38.seg.v2.txt" }, { - "file_name": "jhu-usc.edu_LAML.HumanMethylation450.2.lvl-3.TCGA-AB-3002-03A-01D-0742-05.gdc_hg38.txt", - "id": "731c3560-bcef-4ebf-bfbc-7320399a5bcb" + "id": "ebd6cf90-4f6b-4193-887a-22fdb5645fbc", + "file_name": "TCGA-BRCA.5994c06d-ee9b-4ead-b3d1-2e1f286f7d6d.ascat2.allelic_specific.seg.txt" }, { - "file_name": "CUSKS_p_TCGAb47_SNP_1N_GenomeWideSNP_6_B03_628222.grch38.seg.txt", - "id": "a6f73a3e-faf8-49d9-9b68-77781bd302df" + "id": "aebd6b5a-e676-4357-93df-523b31b55ea0", + "file_name": "TCGA-BRCA.c737131c-636f-4e1b-89b8-bb2d6ddd8164.star_fusion.rna_fusion.bedpe" }, { - "file_name": "5496e9f1-a383-4874-95bb-f4d1b33f4594.vcf", - "id": "5496e9f1-a383-4874-95bb-f4d1b33f4594" + "id": "aa83a7e7-e9cc-4330-a7be-ca750cffb74c", + "file_name": "URAEI_p_TCGASNP_b85_N_GenomeWideSNP_6_F01_735050.birdseed.data.txt" } ], "pagination": { "count": 5, - "sort": "", + "total": 931947, + "size": 5, "from": 101, + "sort": "", "page": 21, - "total": 274724, - "pages": 54945, - "size": 5 + "pages": 186390 } }, "warnings": {} @@ -2212,7 +2444,7 @@ cases_endpt = 'https://api.gdc.cancer.gov/cases' params = {'fields':'submitter_id', 'sort':'submitter_id:asc'} response = requests.get(cases_endpt, params = params) -print json.dumps(response.json(), indent=2) +print(json.dumps(response.json(), indent=2)) ``` ``` Output @@ -2220,54 +2452,54 @@ print json.dumps(response.json(), indent=2) "data": { "hits": [ { - "id": "f7af65fc-97e3-52ce-aa2c-b707650e747b", - "submitter_id": "TARGET-00-NAAEMA" + "id": "be37f1f7-2f98-4f74-bc04-6dd2ae2afcad", + "submitter_id": "01BR001" }, { - "id": "513d0a2a-3c94-5a36-97a4-24c3656fc66e", - "submitter_id": "TARGET-00-NAAEMB" + "id": "e6915db0-7c89-484d-8f9f-15cca68b82fc", + "submitter_id": "01BR008" }, { - "id": "b5f20676-727b-50b0-9b5a-582cd8572d6d", - "submitter_id": "TARGET-00-NAAEMC" + "id": "16614d46-172b-479c-992b-e80a8e9a2c59", + "submitter_id": "01BR009" }, { - "id": "0c0b183f-0d4a-5a9d-9888-0617cebcc462", - "submitter_id": "TARGET-20-PABGKN" + "id": "567fc9e3-17a6-42b1-a896-5e9a9507d1d8", + "submitter_id": "01BR010" }, { - "id": "0f5ed7a7-226d-57bc-a4ce-8a6b18560c55", - "submitter_id": "TARGET-20-PABHET" + "id": "54e89878-a1bc-4f5a-9d68-4842a469586e", + "submitter_id": "01BR015" }, { - "id": "b2a560a4-5e52-5d78-90ef-d680fbaf44d0", - "submitter_id": "TARGET-20-PABHKY" + "id": "a1c7b7b9-b8c8-48c3-9420-55497f9318fd", + "submitter_id": "01BR017" }, { - "id": "1e5c8323-383d-51a0-9199-1b9504b29c7e", - "submitter_id": "TARGET-20-PABLDZ" + "id": "ce3c8b98-e275-4cfd-a379-940d675a564b", + "submitter_id": "01BR018" }, { - "id": "c550a267-30bd-5bf3-9699-61341559e0d5", - "submitter_id": "TARGET-20-PACDZR" + "id": "e4ce89ef-bcaa-418a-8a6b-3602793b9bbf", + "submitter_id": "01BR020" }, { - "id": "0fe29a81-74fc-5158-ae13-0437bc272805", - "submitter_id": "TARGET-20-PACEGD" + "id": "19d3c861-8a5f-49a2-acc0-b55b25465c35", + "submitter_id": "01BR023" }, { - "id": "dd2b23ec-46f4-56b2-9429-6015c6dc730f", - "submitter_id": "TARGET-20-PADDXZ" + "id": "afae8dce-294a-4108-bb28-376f804ae5c4", + "submitter_id": "01BR025" } ], "pagination": { "count": 10, - "sort": "submitter_id:asc", + "total": 86962, + "size": 10, "from": 0, + "sort": "None", "page": 1, - "total": 14551, - "pages": 1456, - "size": 10 + "pages": 8697 } }, "warnings": {} @@ -2298,34 +2530,114 @@ params = {'facets':'program.name', 'from':0, 'size':0, 'sort':'program.name:asc'} response = requests.get(projects_endpt, params = params) -print json.dumps(response.json(), indent=2) +print(json.dumps(response.json(), indent=2)) ``` ```Response { "data": { - "pagination": { - "count": 0, - "sort": "program.name:asc", - "from": 0, - "page": 1, - "total": 39, - "pages": 39, - "size": 0 - }, "hits": [], "aggregations": { "program.name": { "buckets": [ { - "key": "TCGA", - "doc_count": 33 + "doc_count": 33, + "key": "TCGA" + }, + { + "doc_count": 10, + "key": "MATCH" + }, + { + "doc_count": 9, + "key": "TARGET" + }, + { + "doc_count": 4, + "key": "CGCI" + }, + { + "doc_count": 3, + "key": "CMI" + }, + { + "doc_count": 2, + "key": "BEATAML1.0" + }, + { + "doc_count": 2, + "key": "CPTAC" + }, + { + "doc_count": 2, + "key": "MP2PRT" + }, + { + "doc_count": 1, + "key": "APOLLO" + }, + { + "doc_count": 1, + "key": "CDDP_EAGLE" + }, + { + "doc_count": 1, + "key": "CTSP" + }, + { + "doc_count": 1, + "key": "EXCEPTIONAL_RESPONDERS" + }, + { + "doc_count": 1, + "key": "FM" + }, + { + "doc_count": 1, + "key": "HCMI" + }, + { + "doc_count": 1, + "key": "MMRF" + }, + { + "doc_count": 1, + "key": "NCICCR" + }, + { + "doc_count": 1, + "key": "OHSU" + }, + { + "doc_count": 1, + "key": "ORGANOID" + }, + { + "doc_count": 1, + "key": "REBC" + }, + { + "doc_count": 1, + "key": "TRIO" + }, + { + "doc_count": 1, + "key": "VAREPOP" }, { - "key": "TARGET", - "doc_count": 6 + "doc_count": 1, + "key": "WCDT" } ] } + }, + "pagination": { + "count": 0, + "total": 79, + "size": 0, + "from": 0, + "sort": "None", + "page": 1, + "pages": 79 } }, "warnings": {} @@ -2368,125 +2680,233 @@ curl --request POST --header "Content-Type: application/json" --data @Payload 'h ``` Response { "data": { - "pagination": { - "count": 0, - "sort": "", - "from": 0, - "page": 1, - "total": 941, - "pages": 941, - "size": 0 - }, "hits": [], "aggregations": { "project.primary_site": { "buckets": [ { - "key": "Brain", - "doc_count": 1133 + "doc_count": 1202, + "key": "kidney" + }, + { + "doc_count": 1191, + "key": "brain" + }, + { + "doc_count": 1176, + "key": "bronchus and lung" + }, + { + "doc_count": 1156, + "key": "breast" + }, + { + "doc_count": 952, + "key": "colon" + }, + { + "doc_count": 947, + "key": "stomach" + }, + { + "doc_count": 878, + "key": "uterus, nos" + }, + { + "doc_count": 869, + "key": "ovary" + }, + { + "doc_count": 821, + "key": "corpus uteri" + }, + { + "doc_count": 789, + "key": "other and unspecified parts of tongue" + }, + { + "doc_count": 670, + "key": "connective, subcutaneous and other soft tissues" }, { - "key": "Breast", - "doc_count": 1098 + "doc_count": 633, + "key": "rectosigmoid junction" }, { - "key": "Lung", - "doc_count": 1089 + "doc_count": 586, + "key": "bones, joints and articular cartilage of other and unspecified sites" }, { - "key": "Kidney", - "doc_count": 941 + "doc_count": 565, + "key": "thyroid gland" }, { - "key": "Colorectal", - "doc_count": 635 + "doc_count": 528, + "key": "base of tongue" }, { - "key": "Uterus", - "doc_count": 617 + "doc_count": 528, + "key": "floor of mouth" }, { - "key": "Ovary", - "doc_count": 608 + "doc_count": 528, + "key": "gum" }, { - "key": "Head and Neck", - "doc_count": 528 + "doc_count": 528, + "key": "hypopharynx" }, { - "key": "Thyroid", - "doc_count": 507 + "doc_count": 528, + "key": "larynx" }, { - "key": "Prostate", - "doc_count": 500 + "doc_count": 528, + "key": "lip" }, { - "key": "Stomach", - "doc_count": 478 + "doc_count": 528, + "key": "oropharynx" }, { - "key": "Skin", - "doc_count": 470 + "doc_count": 528, + "key": "other and ill-defined sites in lip, oral cavity and pharynx" }, { - "key": "Bladder", - "doc_count": 412 + "doc_count": 528, + "key": "other and unspecified parts of mouth" }, { - "key": "Liver", - "doc_count": 377 + "doc_count": 528, + "key": "palate" }, { - "key": "Cervix", - "doc_count": 308 + "doc_count": 528, + "key": "tonsil" }, { - "key": "Adrenal Gland", - "doc_count": 271 + "doc_count": 500, + "key": "prostate gland" }, { - "key": "Soft Tissue", - "doc_count": 261 + "doc_count": 498, + "key": "retroperitoneum and peritoneum" }, { - "key": "Bone Marrow", - "doc_count": 200 + "doc_count": 470, + "key": "skin" }, { - "key": "Esophagus", - "doc_count": 185 + "doc_count": 448, + "key": "heart, mediastinum, and pleura" }, { - "key": "Pancreas", - "doc_count": 185 + "doc_count": 428, + "key": "liver and intrahepatic bile ducts" }, { - "key": "Testis", - "doc_count": 150 + "doc_count": 412, + "key": "bladder" }, { - "key": "Thymus", - "doc_count": 124 + "doc_count": 307, + "key": "cervix uteri" }, { - "key": "Pleura", - "doc_count": 87 + "doc_count": 271, + "key": "adrenal gland" }, { - "key": "Eye", - "doc_count": 80 + "doc_count": 261, + "key": "bones, joints and articular cartilage of limbs" }, { - "key": "Lymph Nodes", - "doc_count": 58 + "doc_count": 261, + "key": "meninges" }, { - "key": "Bile Duct", - "doc_count": 51 + "doc_count": 261, + "key": "other and unspecified male genital organs" + }, + { + "doc_count": 261, + "key": "peripheral nerves and autonomic nervous system" + }, + { + "doc_count": 258, + "key": "hematopoietic and reticuloendothelial systems" + }, + { + "doc_count": 208, + "key": "testis" + }, + { + "doc_count": 185, + "key": "esophagus" + }, + { + "doc_count": 185, + "key": "pancreas" + }, + { + "doc_count": 179, + "key": "other and ill-defined sites" + }, + { + "doc_count": 179, + "key": "other endocrine glands and related structures" + }, + { + "doc_count": 179, + "key": "spinal cord, cranial nerves, and other parts of central nervous system" + }, + { + "doc_count": 172, + "key": "rectum" + }, + { + "doc_count": 172, + "key": "unknown" + }, + { + "doc_count": 124, + "key": "thymus" + }, + { + "doc_count": 80, + "key": "eye and adnexa" + }, + { + "doc_count": 58, + "key": "lymph nodes" + }, + { + "doc_count": 58, + "key": "other and unspecified major salivary glands" + }, + { + "doc_count": 58, + "key": "small intestine" + }, + { + "doc_count": 51, + "key": "gallbladder" + }, + { + "doc_count": 51, + "key": "other and unspecified parts of biliary tract" } ] } + }, + "pagination": { + "count": 0, + "total": 1202, + "size": 0, + "from": 0, + "sort": "", + "page": 1, + "pages": 1202 } }, "warnings": {} @@ -2528,69 +2948,7 @@ The GDC Portal has a quicksearch functionality that allows for a project, case, curl "https://api.gdc.cancer.gov/v0/all?query=TCGA&size=5" ``` ```Response -{ - "data": { - "query": { - "hits": [ - { - "disease_type": [ - "Esophageal Carcinoma" - ], - "id": "UHJvamVjdDpUQ0dBLUVTQ0E=", - "name": "Esophageal Carcinoma", - "primary_site": [ - "Esophagus" - ], - "project_id": "TCGA-ESCA" - }, - { - "disease_type": [ - "Head and Neck Squamous Cell Carcinoma" - ], - "id": "UHJvamVjdDpUQ0dBLUhOU0M=", - "name": "Head and Neck Squamous Cell Carcinoma", - "primary_site": [ - "Head and Neck" - ], - "project_id": "TCGA-HNSC" - }, - { - "disease_type": [ - "Liver Hepatocellular Carcinoma" - ], - "id": "UHJvamVjdDpUQ0dBLUxJSEM=", - "name": "Liver Hepatocellular Carcinoma", - "primary_site": [ - "Liver" - ], - "project_id": "TCGA-LIHC" - }, - { - "disease_type": [ - "Colon Adenocarcinoma" - ], - "id": "UHJvamVjdDpUQ0dBLUNPQUQ=", - "name": "Colon Adenocarcinoma", - "primary_site": [ - "Colorectal" - ], - "project_id": "TCGA-COAD" - }, - { - "disease_type": [ - "Adrenocortical Carcinoma" - ], - "id": "UHJvamVjdDpUQ0dBLUFDQw==", - "name": "Adrenocortical Carcinoma", - "primary_site": [ - "Adrenal Gland" - ], - "project_id": "TCGA-ACC" - } - ] - } - } -} +{"data":{"query":{"hits":[{"disease_type":["Adenomas and Adenocarcinomas"],"id":"UHJvamVjdDpUQ0dBLUFDQw==","name":"Adrenocortical Carcinoma","primary_site":["Adrenal gland"],"project_id":"TCGA-ACC","project_quicksearch":"Adrenocortical Carcinoma"},{"disease_type":["Adenomas and Adenocarcinomas"],"id":"UHJvamVjdDpUQ0dBLUtJQ0g=","name":"Kidney Chromophobe","primary_site":["Kidney"],"project_id":"TCGA-KICH","project_quicksearch":"Kidney Chromophobe"},{"disease_type":["Adenomas and Adenocarcinomas"],"id":"UHJvamVjdDpUQ0dBLUxJSEM=","name":"Liver Hepatocellular Carcinoma","primary_site":["Liver and intrahepatic bile ducts"],"project_id":"TCGA-LIHC","project_quicksearch":"Liver Hepatocellular Carcinoma"},{"disease_type":["Myeloid Leukemias"],"id":"UHJvamVjdDpUQ0dBLUxBTUw=","name":"Acute Myeloid Leukemia","primary_site":["Hematopoietic and reticuloendothelial systems"],"project_id":"TCGA-LAML","project_quicksearch":"Acute Myeloid Leukemia"},{"disease_type":["Adenomas and Adenocarcinomas"],"id":"UHJvamVjdDpUQ0dBLUtJUlA=","name":"Kidney Renal Papillary Cell Carcinoma","primary_site":["Kidney"],"project_id":"TCGA-KIRP","project_quicksearch":"Kidney Renal Papillary Cell Carcinoma"}],"total":183550}}} ``` This endpoint can be used to quickly retrieve information about a file. For example, if a user wanted to know the UUID for `nationwidechildrens.org_biospecimen.TCGA-EL-A4K1.xml`, the following query could be used to quickly retrieve it programmatically: @@ -2599,20 +2957,7 @@ This endpoint can be used to quickly retrieve information about a file. For exa curl "https://api.gdc.cancer.gov/v0/all?query=nationwidechildrens.org_biospecimen.TCGA-EL-A4K1.xml&size=5" ``` ```Response -{ - "data": { - "query": { - "hits": [ - { - "file_id": "2a7a354b-e497-4ae6-8a85-a170951596c1", - "file_name": "nationwidechildrens.org_biospecimen.TCGA-EL-A4K1.xml", - "id": "RmlsZToyYTdhMzU0Yi1lNDk3LTRhZTYtOGE4NS1hMTcwOTUxNTk2YzE=", - "submitter_id": null - } - ] - } - } -} +{"data":{"query":{"hits":[{"file_id":"a74abfec-db78-4ed4-9e4b-604b66e30e30","file_name":"nationwidechildrens.org_biospecimen.TCGA-EL-A4K1.xml","id":"RmlsZTphNzRhYmZlYy1kYjc4LTRlZDQtOWU0Yi02MDRiNjZlMzBlMzA=","submitter_id":"nationwidechildrens.org_biospecimen.TCGA-EL-A4K1.xml"}],"total":1}}} ``` ## Additional Examples diff --git a/docs/API/Users_Guide/Submission.md b/docs/API/Users_Guide/Submission.md index d47acf23c..80cb1f4c7 100644 --- a/docs/API/Users_Guide/Submission.md +++ b/docs/API/Users_Guide/Submission.md @@ -48,7 +48,7 @@ Metadata files must be uploaded in raw, unencoded form. Binary mode should be us #### BCR XML -While JSON and TSV are the recommended formats for submitting metadata, the GDC API can also extract metadata elements from BCR XML files. Users wishing to submit metadata as BCR XML must contact GDC User Services and ensure that appropriate element mapping is in place before initiating XML submission. +While JSON and TSV are the recommended formats for submitting metadata, the GDC API can also extract metadata elements from BCR XML files. Users wishing to submit metadata as BCR XML must contact GDC User Services and ensure that appropriate element mapping is in place before initiating XML submission. Current mapping can be found in [GitHub](https://github.com/NCI-GDC/gdcdatamodel/tree/develop/gdcdatamodel/xml_mappings). To submit BCR XML, make `PUT` requests with the `Content-Type: application/xml` header to the following URLs, replacing Program.name and Project.code as desribed in [Submission Endpoint](#submission_endpoint) (above): @@ -63,12 +63,12 @@ The following is a sample shell command for submitting an XML file: curl --request PUT --header "X-Auth-Token: $token" --header 'Content-Type: application/xml' --data-binary @biospecimen.xml 'https://api.gdc.cancer.gov/v0/submission/GDC/INTERNAL/xml/biospecimen/bcr/_dry_run' -**NOTE:** A typical BCR XML file contains more information than what is extracted and indexed by the GDC. XML files submitted to the above endpoints are not retained or distributed to GDC data users, so the same files should also be submitted as data files (i.e. as clinical or biospecimen supplements). +>**NOTE:** A typical BCR XML file contains more information than what is extracted and indexed by the GDC. XML files submitted to the above endpoints are not retained or distributed to GDC data users, so the same files should also be submitted as data files (i.e. as clinical or biospecimen supplements). ### Data File Formats -The GDC API accepts a variety of data files after their metadata has been registered: BAM and FASTQ files, clinical and biospecimen supplements, slide images, and other file types. Supported data file formats are listed on the [GDC website](https://gdc.cancer.gov/node/266/). +The GDC API accepts a variety of data files after their metadata has been registered: BAM and FASTQ files, clinical and biospecimen supplements, slide images, and other file types. Supported data file formats are listed on the [GDC Data Dictionary](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-entity-list&anchor=submittable_data_file). ## GDC Data Model @@ -82,7 +82,7 @@ Submitters can assign UUIDs to all submittable entities other than those that co In addition to `id`, many entities also include a `submitter_id` field. This field can contain any string (e.g. a "barcode") that the submitter wishes to use to identify the entity. Typically this string identifies a corresponding entry in submitter's records. The GDC's only requirement with respect to `submitter_id` is that it be a string that is unique for all entities within a project. The GDC Submission API requires a `submitter_id` for most entities. -**Note:** For `case` entities, `submitter_id` must correspond to a `submitted_subject_id` of a study participant registered with the project in dbGaP. +>**Note:** For `case` entities, `submitter_id` must correspond to a `submitted_subject_id` of a study participant registered with the project in dbGaP. ### GDC Data Dictionary Endpoints @@ -163,18 +163,21 @@ The following is an example of a POST request, that simulates creating an entity ```Request { - "project_id": "TCGA-ALCH", + "project_id": "GDC-INTERNAL", "type": "case", - "submitter_id": "TCGA-ALCH-000001", - "projects": { - "code": "ALCH" + "submitter_id": "GDC-INTERNAL-000093", + "disease_type": "Blood Vessel Tumors", + "primary_site": "Base of tongue", + "projects": { + "code": "INTERNAL" } } + ``` ```Command token=$(**Note:** To check whether a dry run transaction was committed successfully, check the `state` of the transaction that executed the commit. The `state` of the dry run transaction itself does not represent the status of a subsequent commit. ## Creating and Updating Entities @@ -333,7 +338,7 @@ The GDC Submission API supports HTTP POST and HTTP PUT methods for creating enti The GDC suggests using POST for creating new entities, and using PUT only for updating entities. This helps to avoid inadvertent entity updates that can occur when using PUT for creating entities. -**Note:** Once a relationship has been created between two entities, it cannot be removed by updating an entity. To remove a relationship, the child entity must be [deleted](#deleting-entities). +>**Note:** Once a relationship has been created between two entities, it cannot be removed by updating an entity. To remove a relationship, the child entity must be [deleted](#deleting-entities). ### Example: Creating and Updating Case Entities (JSON) @@ -342,41 +347,43 @@ In this example, a case entity is created using POST. Then an attempt is made to The JSON in the request was generated using the `case` JSON template that can be obtained from the [GDC Data Dictionary Viewer](../../Data_Dictionary/index.md) and from `https://api.gdc.cancer.gov/v0/submission/template/case?format=json`. -**Note:** For `case` entities, `submitter_id` must correspond to a `submitted_subject_id` of a study participant registered with the project in dbGaP. +>**Note:** For `case` entities, `submitter_id` must correspond to a `submitted_subject_id` of a study participant registered with the project in dbGaP. ```Request1 { + "project_id": "GDC-INTERNAL", "type": "case", - "submitter_id": "TCGA-ALCH-000001", - "projects": { - "code": "ALCH" + "submitter_id": "GDC-INTERNAL-000093", + "disease_type": "Blood Vessel Tumors", + "primary_site": "Base of tongue", + "projects": { + "code": "INTERNAL" } - } ``` ```Command1 token=$(**NOTE:** Access to GDC Submission API GraphQL service is limited to authorized and authenticated submitters. Submitters may only access data in their own project using GraphQL. ### GraphQL IDE @@ -2536,7 +2548,7 @@ GDC data submitters can access the GDC Submission API GraphQL endpoint at: where __[API_version/]__ is the optional API version component (see [Getting Started](Getting_Started.md)). -**NOTE:** An authentication token is required for all requests to the `graphql` endpoint. Queries are restricted to those projects for which the submitter has obtained authorization. +>**NOTE:** An authentication token is required for all requests to the `graphql` endpoint. Queries are restricted to those projects for which the submitter has obtained authorization. ### Constructing a Query diff --git a/docs/API/Users_Guide/System_Information.md b/docs/API/Users_Guide/System_Information.md index 05ba49a46..022c7202b 100644 --- a/docs/API/Users_Guide/System_Information.md +++ b/docs/API/Users_Guide/System_Information.md @@ -23,7 +23,6 @@ Notifications will indicate the GDC `components` to which they apply: | Component | Description | |---------|----------------------------------------------------------------------| | PORTAL | The GDC Data Portal | -| LEGACY | The GDC Legacy Archive | | SUBMISSION | The GDC Data Submission Portal | | DOCUMENTATION | The GDC documentation site that contains GDC user guides, release notes, and the GDC Data Dictionary | | WEBSITE | The GDC project website that includes information about the system. This does not include any of the above-listed GDC components. | @@ -39,7 +38,7 @@ curl --request GET https://api.gdc.cancer.gov/v0/notifications { "level": "INFO", "components": [ - "SUBMISSION_API", + "SUBMISSION_API" "LEGACY_API" ], "message": "The system is up!" diff --git a/docs/API/Users_Guide/images/graphql-query.png b/docs/API/Users_Guide/images/graphql-query.png new file mode 100644 index 000000000..e09f3f9a5 Binary files /dev/null and b/docs/API/Users_Guide/images/graphql-query.png differ diff --git a/docs/API/Users_Guide/scripts/Authentication_Tokens.py b/docs/API/Users_Guide/scripts/Authentication_Tokens.py new file mode 100644 index 000000000..0b9b7a7cd --- /dev/null +++ b/docs/API/Users_Guide/scripts/Authentication_Tokens.py @@ -0,0 +1,27 @@ +import requests +import json +import re + +# This script will not work until $TOKEN_FILE_PATH is replaced with an actual path. + +with open("$TOKEN_FILE_PATH","r") as token: + token_string = str(token.read().strip()) + +headers = { + 'X-Auth-Token': token_string + } + +data_endpt = 'https://api.gdc.cancer.gov/data/' +data_uuid = 'fd89bfa5-b3a7-4079-bf90-709580c006e5' +headers = { + 'X-Auth-Token': token_string + } +response = requests.get(data_endpt + data_uuid, headers=headers) + +# The file name can be found in the header within the Content-Disposition key. +response_head_cd = response.headers["Content-Disposition"] + +file_name = re.findall("filename=(.+)", response_head_cd)[0] + +with open(file_name, "wb") as output_file: + output_file.write(response.content) diff --git a/docs/API/Users_Guide/scripts/Basic_Query.py b/docs/API/Users_Guide/scripts/Basic_Query.py index 5eb08266d..eedeb2432 100644 --- a/docs/API/Users_Guide/scripts/Basic_Query.py +++ b/docs/API/Users_Guide/scripts/Basic_Query.py @@ -3,7 +3,7 @@ cases_endpt = 'https://api.gdc.cancer.gov/cases' -# The fields parameter is passed as a comma-separated string of single names +# The 'fields' parameter is passed as a comma-separated string of single names. fields = [ "submitter_id", "case_id", @@ -22,4 +22,10 @@ response = requests.get(cases_endpt, params = params) +# OUTPUT METHOD 1: Write to a file. +file = open("basic_query.tsv", "w") +file.write(response.text) +file.close() + +# OUTPUT METHOD 2: View on screen. print(response.content) diff --git a/docs/API/Users_Guide/scripts/Basic_Troubleshooting.py b/docs/API/Users_Guide/scripts/Basic_Troubleshooting.py new file mode 100644 index 000000000..0374b112c --- /dev/null +++ b/docs/API/Users_Guide/scripts/Basic_Troubleshooting.py @@ -0,0 +1,11 @@ +import requests +status_endpt = "https://api.gdc.cancer.gov/status" +response = requests.get(status_endpt) + +# OUTPUT METHOD 1: Write to a file. +file = open("api_status.json", "w") +file.write(response.text) +file.close() + +# OUTPUT METHOD 2: View on screen. +print(response.content) \ No newline at end of file diff --git a/docs/API/Users_Guide/scripts/Complex_Query.py b/docs/API/Users_Guide/scripts/Complex_Query.py index e3df06f0d..ad9b70682 100644 --- a/docs/API/Users_Guide/scripts/Complex_Query.py +++ b/docs/API/Users_Guide/scripts/Complex_Query.py @@ -1,6 +1,7 @@ import requests import json +# The 'fields' parameter is passed as a comma-separated string of single names. fields = [ "file_name", "cases.submitter_id", @@ -52,4 +53,10 @@ # The parameters are passed to 'json' rather than 'params' in this case response = requests.post(files_endpt, headers = {"Content-Type": "application/json"}, json = params) -print(response.content.decode("utf-8")) +# OUTPUT METHOD 1: Write to a file. +file = open("complex_filters.tsv", "w") +file.write(response.text) +file.close() + +# OUTPUT METHOD 2: View on screen. +print(response.content.decode("utf-8")) \ No newline at end of file diff --git a/docs/API/Users_Guide/scripts/Filter_Query.py b/docs/API/Users_Guide/scripts/Filter_Query.py index 42c17761d..11bd6dcc9 100644 --- a/docs/API/Users_Guide/scripts/Filter_Query.py +++ b/docs/API/Users_Guide/scripts/Filter_Query.py @@ -1,6 +1,7 @@ import requests import json +# The 'fields' parameter is passed as a comma-separated string of single names. fields = [ "submitter_id", "case_id", @@ -21,8 +22,7 @@ } } -# With a GET request, the filters parameter needs to be converted -# from a dictionary to JSON-formatted string +# With a GET request, the filters parameter needs to be converted from a dictionary to JSON-formatted string params = { "filters": json.dumps(filters), @@ -33,4 +33,10 @@ response = requests.get(cases_endpt, params = params) -print(response.content) +# OUTPUT METHOD 1: Write to a file. +file = open("filtered_query.tsv", "w") +file.write(response.text) +file.close() + +# OUTPUT METHOD 2: View on screen. +print(response.content) \ No newline at end of file diff --git a/docs/API/Users_Guide/scripts/Sample_Request.py b/docs/API/Users_Guide/scripts/Sample_Request.py new file mode 100644 index 000000000..2652df479 --- /dev/null +++ b/docs/API/Users_Guide/scripts/Sample_Request.py @@ -0,0 +1,14 @@ +import requests +import json + +file_endpt = 'https://api.gdc.cancer.gov/files/' +file_uuid = 'cb92f61d-041c-4424-a3e9-891b7545f351' +response = requests.get(file_endpt + file_uuid) + +# OUTPUT METHOD 1: Write to a file. +file = open("sample_request.json", "w") +file.write(response.text) +file.close() + +# OUTPUT METHOD 2: View on screen. +print(json.dumps(response.json(), indent=2)) diff --git a/docs/Data/Bioinformatics_Pipelines/Aligned_reads_summary_metrics.md b/docs/Data/Bioinformatics_Pipelines/Aligned_reads_summary_metrics.md new file mode 100644 index 000000000..7dda5c7a6 --- /dev/null +++ b/docs/Data/Bioinformatics_Pipelines/Aligned_reads_summary_metrics.md @@ -0,0 +1,23 @@ +# Aligned Reads Summary Metrics + +Various summary metrics are added to the aligned reads entity for query by the user. These are generated by such tools as SAMtools, Picard, and GATK4. These may be helpful to determine underlying quality or summary information regarding the submitted data. Examples are included below: + +* average_base_quality +* average_insert_size +* average_read_length +* contamination +* contamination_error +* mean_coverage +* msi_score +* msi_status +* pairs_on_diff_chr +* proportion_base_mismatch +* proportion_coverage_10x +* proportion_coverage_30x +* proportion_reads_duplicated +* proportion_reads_mapped +* proportion_targets_no_coverage +* total_reads + + +For a complete list of the summary metrics as well as the tools used to generate them please visit the [Data Dictionary Viewer](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=aligned_reads). diff --git a/docs/Data/Bioinformatics_Pipelines/CNV_Pipeline.md b/docs/Data/Bioinformatics_Pipelines/CNV_Pipeline.md index bf0f9218a..f8441cff8 100644 --- a/docs/Data/Bioinformatics_Pipelines/CNV_Pipeline.md +++ b/docs/Data/Bioinformatics_Pipelines/CNV_Pipeline.md @@ -2,29 +2,84 @@ ## Introduction -The copy number variation (CNV) pipeline uses Affymetrix SNP 6.0 array data to identify genomic regions that are repeated and infer the copy number of these repeats. This pipeline is built onto the existing TCGA level 2 data generated by [Birdsuite](https://www.broadinstitute.org/scientific-community/science/programs/medical-and-population-genetics/birdsuite/birdsuite) and uses the [DNAcopy](http://www.bioconductor.org/packages/release/bioc/html/DNAcopy.html) R-package to perform a circular binary segmentation (CBS) analysis [[1]](http://biostatistics.oxfordjournals.org/content/5/4/557.short). CBS translates noisy intensity measurements into chromosomal regions of equal copy number. The final output files are segmented into genomic regions with the estimated copy number for each region. The GDC further transforms these copy number values into segment mean values, which are equal to log2(copy-number/ 2). Diploid regions will have a segment mean of zero, amplified regions will have positive values, and deletions will have negative values. The GRCh38 probe-set was produced by mapping probe sequences to the GRCh38 reference genome and can be downloaded at the [GDC Reference File Website](https://gdc.cancer.gov/about-data/data-harmonization-and-generation/gdc-reference-files). +The copy number variation (CNV) pipeline uses either NGS or Affymetrix SNP 6.0 (SNP6) array data to identify genomic regions that are repeated and infer the copy number of these repeats. Three sets of pipelines have been used for CNV inferences. +* ASCAT +* ABSOLUTE +* DNAcopy -## Data Processing Steps +The first set of CNV pipelines are built upon the ASCAT [[1]](https://www.pnas.org/content/107/39/16910) algorithm for both WGS and SNP6 data. ASCAT is able to generate Allele-specific Copy Number Segment data with integer copy number values, and the derived integer Gene-Level Copy Number. 1.) The WGS copy number analysis pipeline, [ascatNGS](https://github.com/cancerit/ascatNgs), is described in detail [here](https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline/#whole-genome-sequencing-variant-calling). 2.) The SNP6 copy number analysis pipeline, ASCAT2, is adopted from the [example ASCAT analysis](https://github.com/VanLoo-lab/ascat/blob/v2.5/ExampleData/ASCAT_examplePipeline.R). 3.) The SNP6 copy number analysis pipeline, ASCAT3, is an updated version of ASCAT2. The ASCAT3 analysis in TCGA was done by the [Vanloo lab](https://github.com/VanLoo-lab/ascat/tree/master/ReleasedData/TCGA_SNP6_hg38), and the GDC released a reformatted version of these calls. Both ASCAT2 and ASCAT3 generates data similar to ascatNGS. -A metadata preprocessing step is used to convert the GRCh37 (hg19) probe set coordinates to the newer GRCh38 (hg38) genome build coordinates. A minimum quality control step to verify that reference bases are consistent across two genome builds is used to filter out low quality liftover probe sets. +The second CNV pipeline, ABSOLUTE, also uses Affymetrix SNP 6.0 (SNP6) array data as input. The hg19 version of the segments were published as one of the [TCGA PanCancer analysis papers](https://doi.org/10.1016/j.ccell.2018.03.007) and the data is available in the [GDC publication page](https://gdc.cancer.gov/about-data/publications/pancanatlas). These calls have been manually curated and thus are considered of good quality. The GDC performed segment liftover and generated gene-level copy numbers. Note that the intermediate output of GRCh38 segments contain liftover artifacts and were not released in the GDC. Users can also obtain corresponding purity and ploidy measurements from the GDC publication page mentioned above. -The [Copy Number Liftover Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_liftover_workflow) uses the TCGA level 2 tangent.copynumber files described above. These files were generated by first normalizing array intensity values, estimating raw copy number, and performing tangent normalization, which subtracts variation that is found in a set of normal samples. Original array intensity values (TCGA level 1) are available in the [GDC Legacy Archive](https://portal.gdc.cancer.gov/legacy-archive/) under the "Data Format: CEL" and "Platform: Affymetrix SNP 6.0" filters. +The third set of CNV pipelines are built onto the existing TCGA level 2 SNP6 data generated by [Birdsuite](https://www.broadinstitute.org/scientific-community/science/programs/medical-and-population-genetics/birdsuite/birdsuite) and uses the [DNAcopy](http://www.bioconductor.org/packages/release/bioc/html/DNAcopy.html) R-package to perform a circular binary segmentation (CBS) analysis [[2]](http://biostatistics.oxfordjournals.org/content/5/4/557.short). CBS translates noisy intensity measurements into chromosomal regions of equal copy number. The final output files are segmented into genomic regions with the estimated copy number for each region. The GDC further transforms these copy number values into segment mean values, which are equal to log2(copy-number/ 2). Diploid regions will have a segment mean of zero, amplified regions will have positive values, and deletions will have negative values. -The Copy Number Liftover Workflow performs CBS analysis using the DNACopy R-package to process tangent normalized data into [Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) files, which associate contiguous chromosome regions with log2 ratio segment means in a tab-delimited format. The number of probes with intensity values associated with each chromosome region is also reported (probes with no intensity values are not included in this count). During copy number segmentation probe sets from Pseudo-Autosomal Regions (PARs) were removed from males and Y chromosome segments were removed from females. +## ASCAT Pipelines +### Data Processing Steps +#### Copy Number Segmentation + +The [Somatic Copy Number Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=somatic_copy_number_workflow) uses a tumor-normal pair of either SNP6 raw CEL data, or WGS data as input. The ASCAT algorithm derives allele-specific copy number segments while estimating and adjusting for tumor purity and ploidy [[1]](https://www.pnas.org/content/107/39/16910). Because there are two parental strands, the resulting Copy Number Segment or Allele-Specific Copy Number Segment files contain 3 different copy number integer values: Major_Copy_Number refers to the larger strand copy number, Minor_Copy_Number refers to the smaller strand copy number, Copy_Number is the sum of Major_Copy_Number and Minor_Copy_Number, and thus equals to the total copy number at the locus. -Masked copy number segments are generated with the same method except that a filtering step is performed that removes Y chromosome and probe sets that were previously indicated to have frequent germline copy-number variation. | I/O | Entity | Format | |---|---|---| -| Input | [Submitted Tangent Copy Number](/Data_Dictionary/viewer/#?view=table-definition-view&id=submitted_tangent_copy_number) | TXT | -| Output | [Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) or Masked Copy Number Segment | TXT | +| Input | [Submitted Genotype_Array](/Data_Dictionary/viewer/#?view=table-definition-view&id=submitted_genotyping_array) | CEL | +| Output | [Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) or [Allele-Specific Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) | TXT | + +| I/O | Entity | Format | +|---|---|---| +| Input | [Aligned Reads](/Data_Dictionary/viewer/#?view=table-definition-view&id=aligned_reads) | BAM | +| Output | [Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) or [Allele-Specific Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) | TXT | + +#### Gene-Level Copy Number + +Gene-level Copy Number is generated by inheriting the Copy_Number value of the residing segment in the Copy Number Segment file generated from ASCAT2, ASCAT3, or ascatNGS workflows. -## File Access and Availability +In some occasions, one gene may overlap with more than one segment. In this case, min_copy_number is the minimum value of all segments it overlaps, max_copy_number is the maximum value of all segments it overlaps, and copy_number is calculated as the weighted (on length of overlapped regions) median of copy number values from all overlapped segments. When there is a tie (very rare), the smaller number is used. If a gene overlaps with only one segment, copy_number = min_copy_number = max_copy_number. If a gene overlaps with no segments, the gene gets empty value "" in copy_number, min_copy_number and max_copy_number. + + +| I/O | Entity | Format | +|---|---|---| +| Input | [Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) or Allele-Specific Copy Number Segment | TXT | +| Output | [Copy Number Estimate](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_estimate) | TXT | + + +### File Access and Availability | Type | Description | Format | |---|---|---| -| Copy Number Segment| A table that associates contiguous chromosomal segments with genomic coordinates, mean array intensity, and the number of probes that bind to each segment. | TXT | -| Masked Copy Number Segment | A table with the same information as the Copy Number Segment except that segments with probes known to contain germline mutations are removed. | TXT | +| Copy Number Segment| A table that associates contiguous chromosomal segments with genomic coordinates, and integer copy numbers. | TXT | +| Allele-Specific Copy Number Segment| A table that associates contiguous chromosomal segments with genomic coordinates, and integer copy numbers. | TXT | +| Copy Number Estimate | A Gene-level Copy Number file that displays integer copy number on a gene level. Generated from Copy Number Segment or Allele-Specific Copy Number Segment files. | TXT | + +## ABSOLUTE Copy Number +### Data Processing Steps + +The source data were generated by external groups. Please check the [corresponding publication](https://doi.org/10.1016/j.ccell.2018.03.007) for details. + +### File Access and Availability + +File Access and Availability is similar to that from the ASCAT pipelines, except that only gene-level copy numbers are available, but not segmentation calls. + + +## DNACopy Pipeline +### Data Processing Steps + +The GRCh38 SNP6 probe-set was produced by mapping probe sequences to the GRCh38 reference genome and can be downloaded at the [GDC Reference File Website](https://gdc.cancer.gov/about-data/data-harmonization-and-generation/gdc-reference-files). + +#### Copy Number Segmentation + +The [Copy Number Liftover Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_liftover_workflow) uses TCGA level 2 tangent.copynumber files. These files were generated by first normalizing array intensity values, estimating raw copy number, and performing tangent normalization, which subtracts variation that is found in a set of normal samples. + +The Copy Number Liftover Workflow performs CBS analysis using the DNACopy R-package to process tangent normalized data into [Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) files, which associate contiguous chromosome regions with log2 ratio segment means in a tab-delimited format. The number of probes with intensity values associated with each chromosome region is also reported (probes with no intensity values are not included in this count). During copy number segmentation probe sets from Pseudo-Autosomal Regions (PARs) were removed from males and Y chromosome segments were removed from females. + +Masked copy number segments are generated using the same method except that a filtering step is performed that removes the Y chromosome and probe sets that were previously indicated to be associated with frequent germline copy-number variation. + +| I/O | Entity | Format | +|---|---|---| +| Input | [Submitted Tangent Copy Number](/Data_Dictionary/viewer/#?view=table-definition-view&id=submitted_tangent_copy_number) | TXT | +| Output | [Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) or [Masked Copy Number Segment](/Data_Dictionary/viewer/#?view=table-definition-view&id=copy_number_segment) | TXT | + +[1] Van Loo, P., Nordgard, S. H., Lingjaerde, O. C., Russnes, H. G., Rye, I. H., Sun, W. et al. "Allele-specific copy number analysis of tumors." Proceedings of the National Academy of Sciences, 107.39 (2010): 16910-16915. -[1] Olshen, Adam B., E. S. Venkatraman, Robert Lucito, and Michael Wigler. "Circular binary segmentation for the analysis of array-based DNA copy number data." Biostatistics 5, no. 4 (2004): 557-572. +[2] Olshen, Adam B., E. S. Venkatraman, Robert Lucito, and Michael Wigler. "Circular binary segmentation for the analysis of array-based DNA copy number data." Biostatistics 5, no. 4 (2004): 557-572. diff --git a/docs/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline.md b/docs/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline.md index 0c7e95651..470121b60 100644 --- a/docs/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline.md +++ b/docs/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline.md @@ -26,11 +26,6 @@ Prior to alignment, BAM files that were submitted to the GDC are split by read g DNA-Seq analysis begins with the [Alignment Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=alignment_workflow). Read groups are aligned to the reference genome using one of two [BWA](http://bio-bwa.sourceforge.net) algorithms [[1]](http://www.ncbi.nlm.nih.gov/pubmed/19451168). BWA-MEM is used if mean read length is greater than or equal to 70 bp. Otherwise BWA-aln is used. Each read group is aligned to the reference genome separately and all read group alignments that belong to a single aliquot are merged using [Picard Tools](http://broadinstitute.github.io/picard) [SortSam](https://broadinstitute.github.io/picard/command-line-overview.html#SortSam) and [MergeSamFiles](https://broadinstitute.github.io/picard/command-line-overview.html#MergeSamFiles). Duplicate reads, which may persist as PCR artifacts, are then flagged to prevent downstream variant call errors. -#### Quality Control - -Quality control metrics are collected before and after the alignment workflow and reviewed to identify potential low-quality data files. Basic metrics such as GC content and mean read length as well as quality score metrics are collected from unaligned reads using [FASTQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Quality metrics collected by the GDC for aligned reads include samtools idxstat and flagstat. Alignment information is collected using Picard [CollectMultipleMetrics](https://broadinstitute.github.io/picard/command-line-overview.html#CollectMultipleMetrics) for both WGS and WXS. Coverage information is collected using picard [CollectWgsMetrics](https://broadinstitute.github.io/picard/command-line-overview.html#CollectWgsMetrics) for WGS and picard [CollectHsMetrics](https://broadinstitute.github.io/picard/command-line-overview.html#CollectHsMetrics) for WXS. - -Quality control metrics for each file endpoint can be accessed through the API using the `expand=analysis.metadata.read_groups,analysis.metadata.read_groups.read_group_qcs` parameter. Click [here](https://api.gdc.cancer.gov/files/40e311a4-67aa-468a-8e09-1c7daa2d10bb?pretty=true&expand=analysis.metadata.read_groups,analysis.metadata.read_groups.read_group_qcs) for an example query. #### Reference Genome @@ -42,18 +37,20 @@ All alignments are performed using the human reference genome GRCh38.d1.vd1. Dec | Input | [Submitted Unaligned Reads](/Data_Dictionary/viewer/#?view=table-definition-view&id=submitted_unaligned_reads) or [Submitted Aligned Reads](/Data_Dictionary/viewer/#?view=table-definition-view&id=submitted_aligned_reads) | FASTQ or BAM | | Output | [Aligned Reads](/Data_Dictionary/viewer/#?view=table-definition-view&id=aligned_reads) | BAM | -![DNA-Seq Alignment Pipeline](images/dna-alignment-pipeline_0.png) +![DNA-Seq Alignment Pipeline](images/dna-alignment-pipeline_1.png) ### DNA-Seq Alignment Command Line Parameters -#### Step 1: Converting BAMs to FASTQs with Biobambam - biobambam2 2.0.54 +__Note that version numbers may vary in files downloaded from the GDC Portal due to ongoing pipeline development and improvement.__ + +#### Step 1: Converting BAMs to FASTQs with Biobambam - biobambam2 ```Shell bamtofastq \ collate=1 \ exclude=QCFAIL,SECONDARY,SUPPLEMENTARY \ filename= \ gz=1 \ -inputformat=bam +inputformat=bam \ level=5 \ outputdir= \ outputperreadgroup=1 \ @@ -64,7 +61,7 @@ outputperreadgroupsuffixO2=_o2.fq.gz \ outputperreadgroupsuffixS=_s.fq.gz \ tryoq=1 \ ``` -#### Step 2: BWA Alignment - bwa 0.7.15 - samtools 1.3.1 +#### Step 2: BWA Alignment - bwa - samtools If mean read length is greater than or equal to 70bp: ```Shell bwa mem \ @@ -86,7 +83,7 @@ bwa sampe -r \ SORT_ORDER=coordinate \ VALIDATION_STRINGENCY=STRICT ``` -#### Step 4: BAM Merge - picard 2.6.0 +#### Step 4: BAM Merge - picard 2 ```Shell java -jar picard.jar MergeSamFiles \ ASSUME_SORTED=false \ @@ -108,7 +105,7 @@ SORT_ORDER=coordinate \ USE_THREADING=true \ VALIDATION_STRINGENCY=STRICT ``` -#### Step 5: Mark Duplicates - picard 2.6.0 +#### Step 5: Mark Duplicates - picard 2 ```Shell java -jar picard.jar MarkDuplicates \ CREATE_INDEX=true \ @@ -122,11 +119,11 @@ The alignment quality is further improved by the [Co-cleaning workflow](/Data_Di #### Indel Local Realignment -Local realignment of insertions and deletions is performed using [IndelRealigner](https://software.broadinstitute.org/gatk/documentation/tooldocs/3.8-0/org_broadinstitute_gatk_tools_walkers_indels_IndelRealigner.php). This step locates regions that contain misalignments across BAM files, which can often be caused by insertion-deletion (indel) mutations with respect to the reference genome. Misalignment of indel mutations, which can often be erroneously scored as substitutions, reduces the accuracy of downstream variant calling steps. +Local realignment of insertions and deletions is performed using [IndelRealigner](https://github.com/broadinstitute/gatk-docs/blob/master/gatk3-tooldocs/3.8-0/org_broadinstitute_gatk_tools_walkers_indels_IndelRealigner.json). This step locates regions that contain misalignments across BAM files, which can often be caused by insertion-deletion (indel) mutations with respect to the reference genome. Misalignment of indel mutations, which can often be erroneously scored as substitutions, reduces the accuracy of downstream variant calling steps. #### Base Quality Score Recalibration -A base quality score recalibration (BQSR) step is then performed using [BaseRecalibrator](https://software.broadinstitute.org/gatk/documentation/tooldocs/3.8-0/org_broadinstitute_gatk_tools_walkers_bqsr_BaseRecalibrator.php). This step adjusts base quality scores based on detectable and systematic errors. This step also increases the accuracy of downstream variant calling algorithms. Note that the original quality scores are kept in the OQ field of co-cleaned BAM files. These scores should be used if conversion of BAM files to FASTQ format is desired. +A base quality score recalibration (BQSR) step is then performed using [BaseRecalibrator](https://gatk.broadinstitute.org/hc/en-us/articles/360036898312-BaseRecalibrator). This step adjusts base quality scores based on detectable and systematic errors. This step also increases the accuracy of downstream variant calling algorithms. Note that the original quality scores are kept in the OQ field of co-cleaned BAM files. These scores should be used if conversion of BAM files to FASTQ format is desired. | I/O | Entity | Format | @@ -183,9 +180,11 @@ java -jar GenomeAnalysisTK.jar \ Aligned and co-cleaned BAM files are processed through the [Somatic Mutation Calling Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=somatic_mutation_calling_workflow) as tumor-normal pairs. Variant calling is performed using four separate pipelines: - [MuSE](http://bioinformatics.mdanderson.org/main/MuSE) [[2]](http://www.biorxiv.org/content/early/2016/05/25/055467.abstract) -- [MuTect2](https://www.broadinstitute.org/cancer/cga/mutect) [[3]](http://www.nature.com/nbt/journal/v31/n3/abs/nbt.2514.html) +- [MuTect2](https://gatk.broadinstitute.org/hc/en-us/articles/360037593851-Mutect2) [[3]](http://www.nature.com/nbt/journal/v31/n3/abs/nbt.2514.html) - [VarScan2](http://dkoboldt.github.io/varscan/) [[4]](http://genome.cshlp.org/content/22/3/568.short) -- [SomaticSniper](http://gmt.genome.wustl.edu/packages/somatic-sniper/) [[5]](http://bioinformatics.oxfordjournals.org/content/28/3/311.short) +- [Pindel](https://github.com/ucscCancer/pindel-tool) + +Note that [SomaticSniper](http://gmt.genome.wustl.edu/packages/somatic-sniper/) [[5]](http://bioinformatics.oxfordjournals.org/content/28/3/311.short) was used and available on the GDC Data Portal prior to [GDC Data Release 35](https://docs.gdc.cancer.gov/Data/Release_Notes/Data_Release_Notes/#data-release-350). Variant calls are reported by each pipeline in a VCF formatted file. See the GDC [VCF Format](../File_Formats/VCF_Format/) documentation for details on each available field. At this point in the DNA-Seq pipeline, all downstream analyses are branched into four separate paths that correspond to their respective variant calling pipeline. @@ -194,15 +193,14 @@ Four separate variant calling pipelines are implemented for GDC data harmonizati The [MuTect2 pipeline](https://gdc.cancer.gov/files/public/image/Broad_MuTect_0.png) employs a "Panel of Normals" to identify additional germline mutations. This panel is generated using TCGA blood normal genomes from thousands of individuals that were curated and confidently assessed to be cancer-free. This method allows for a higher level of confidence to be assigned to somatic variants that were called by the MuTect2 pipeline. -Basic outlines for the other three pipelines can be found here: +Basic outlines for the other two pipelines can be found here: - [VarScan2 pipeline](https://gdc.cancer.gov/files/public/image/varscan-somatic-variant-calling-pipeline.png) - [MuSE pipeline](https://gdc.cancer.gov/files/public/image/muse-somatic-variant-calling-pipeline.png) -- [SomaticSniper pipeline](https://gdc.cancer.gov/files/public/image/somaticsniper-variant-calling-pipeline.png) #### Indels -Indel mutations that were generated with the MuTect2 and VarScan pipeline are detected and reported in GDC VCF files. +Indel mutations that were generated with the MuTect2, Pindel, and VarScan pipelines are detected and reported in GDC VCF files. #### Germline Variants At this time, germline variants are deliberately excluded as harmonized data. The GDC does not recommend using germline variants that were previously detected and stored in the Legacy Archive as they do not meet the GDC criteria for high-quality data. @@ -216,7 +214,7 @@ At this time, germline variants are deliberately excluded as harmonized data. Th #### MuSE -MuSEv1.0rc_submission_c039ffa; dbSNP v.144 +MuSEv1.0; dbSNP v.144 __Step 1:__ MuSE call @@ -243,7 +241,7 @@ __Note:__ -E is used for WXS data and -G can be used for WGS data. #### MuTect2 -GATK nightly-2016-02-25-gf39d340; dbSNP v.144 +GATK; dbSNP v.144 ```Shell java -jar GenomeAnalysisTK.jar \ @@ -261,34 +259,10 @@ java -jar GenomeAnalysisTK.jar \ --disable_auto_index_creation_and_locking_when_reading_rods ``` - - -#### SomaticSniper -Somatic-sniper v1.0.5.0 - -```Shell -bam-somaticsniper \ --q 1 \ --L \ --G \ --Q 15 \ --s 0.01 \ --T 0.85 \ --N 2 \ --r 0.001 \ --n NORMAL \ --t TUMOR \ --F vcf \ --f ref.fa \ - \ - \ - -``` - #### VarScan -__Step 1:__ Mpileup; Samtools 1.1 +__Step 1:__ Mpileup; Samtools ```Shell samtools mpileup \ -f \ @@ -299,7 +273,7 @@ samtools mpileup \ ``` -__Step 2:__ Varscan Somatic; Varscan.v2.3.9 +__Step 2:__ Varscan Somatic; Varscan.v2 ```Shell java -jar VarScan.jar somatic \ \ @@ -318,7 +292,7 @@ java -jar VarScan.jar somatic \ --output-vcf ``` -__Step 3:__ Varscan ProcessSomatic; Varscan.v2.3.9 +__Step 3:__ Varscan ProcessSomatic; Varscan.v2 ```Shell java -jar VarScan.jar processSomatic \ \ @@ -327,6 +301,123 @@ java -jar VarScan.jar processSomatic \ --p-value 0.07 ``` +#### Pindel + +__Step 1:__ Filter Reads + +Filter BAM reads that are not unmapped or duplicate or secondary_alignment or failed_quality_control or supplementary for both tumor and normal BAM files + +Tool: sambamba + +```Shell +Sambamba view $(input.bam) --filter "not (unmapped or duplicate or secondary_alignment or failed_quality_control or supplementary)" --format bam --nthreads 1 --output-filename $(output.bam) +``` + +__Step 2:__ Pindel + +[Pindel Repo](https://github.com/genome/pindel/releases/tag/v0.2.5b8) + +__Step 2a.:__ Calculate mean insert size +```Python +cmd = "samtools view -f66 %s | head -n 1000000" % (bam) +output = do_shell_command(cmd) +lines = output.decode('utf-8').split('\n') +b_sum = 0 +b_count = 0 +numlines = 0 +for line in lines: + numlines += 1 + tmp = line.split("\t") + if len(tmp) < 9: + break + if abs(int(tmp[8])) < 10000: + b_sum += abs(int(tmp[8])) + b_count += 1 +try: + mean = b_sum / b_count +``` +__Step 2b.:__ Write it to a config file +```Python +for inputBamFile, meanInsertSize, tag in zip(inputBamFiles, meanInsertSizes, tags): + fil.write("%s\t%s\t%s\n" %(inputBamFile, meanInsertSize, tag)) + fil.close() +``` +__Step 2c.:__ Run pindel +```Shell +pindel \ +-f GRCh38.d1.vd1.fa \ +-i config_file \ +-o $(output_prefix) \ +--exclude GRCh38.d1.vd1.centromeres.telomeres.bed + +``` +__Step 2d.:__ Merge DI and SI OUTPUT +```Python +with open(os.path.join(args.workdir, "pindel_somatic"), "w") as handle: + for p in pindel_files: + if p.endswith("_D"): + with open(p) as ihandle: + for line in ihandle: + if re.search("ChrID", line): + handle.write(line) + for p in pindel_files: + if p.endswith("_SI"): + with open(p) as ihandle: + for line in ihandle: + if re.search("ChrID", line): + handle.write(line) +``` +__Step 2e.:__ Create a config for pindel somatic filter +```Python +indel.filter.input = $(merged.pindel.output) +indel.filter.vaf = 0.08 +indel.filter.cov = 20 +indel.filter.hom = 6 +indel.filter.pindel2vcf = "/path/to/pindel/pindel2vcf4tcga" +indel.filter.reference = "GRCh38.d1.vd1.fa" +indel.filter.referencename = "GRCh38" +indel.filter.referencedate = datetime.datetime.now().strftime("%Y%m%d") +indel.filter.output = $(output.file.name.vcf) + +``` +__Step 2f.:__ Apply somatic filter on pindel output +Tool: pindel2vcf4tcga +```Perl +perl pindel/somatic_filter/somatic_indelfilter.pl $(somatic.indel.filter.config) +``` +__Step 3:__ Pindel +Tool: Picard.jar 2 +```Shell +java \ +-d64 \ +-XX: +UseSerialGC \ +-Xmx16G \ +-jar picard.jar \ +SortVcf \ +CREATE_INDEX=true \ +SEQUENCE_DICTIONARY=GRCh38.d1.vd1.dict \ +I=$(pindel.somatic.vcf) \ +OUTPUT=$(output.vcf.gz) +``` +__Step 5:__ Vt Normalization +Tool: GenomeAnalysisTK.jar nightly-2016-02-25-gf39d340 + +```Shell +java \ +-Xmx4G \ +-jar \ +/bin/GenomeAnalysisTK.jar \ +-T VariantFiltration \ +--disable_auto_index_creation_and_locking_when_reading_rods \ +--variant $(vt.normal.output.vcf.gz) \ +-R GRCh38.d1.vd1.fa \ +--filterExpression vc.isBiallelic() && vc.getGenotype(\"TUMOR\").getAD().1 < 3" \ +--filterName TALTDP \ +-o $(output.vcf.gz) + + +``` + ### Variant Call Annotation Workflow Raw VCF files are then annotated in the [Somatic Annotation Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=somatic_annotation_workflow) with the [Variant Effect Predictor (VEP)](https://www.ensembl.org/info/docs/tools/vep/index.html) v84 [[6]](http://dx.doi.org/10.1093/bioinformatics/btq330) along with VEP GDC plugins. @@ -345,17 +436,115 @@ The VEP uses the coordinates and alleles in the VCF file to infer biological con Due to licensing constraints COSMIC is not utilized for annotation in the GDC VEP workflow. -In addition to annotation, [False Positive Filter](https://github.com/ucscCancer/fpfilter-tool) is used to label low quality variants in VarScan and SomaticSniper outputs. Variants with SSQ < 25 in SomaticSniper are also removed. +In addition to annotation, [False Positive Filter](https://github.com/ucscCancer/fpfilter-tool) is used to label low quality variants in VarScan. | I/O | Entity | Format | |---|---|---| | Input | [Simple Somatic Mutation](/Data_Dictionary/viewer/#?view=table-definition-view&id=simple_somatic_mutation) | VCF | | Output | [Annotated Somatic Mutation](/Data_Dictionary/viewer/#?view=table-definition-view&id=annotated_somatic_mutation) | VCF | -### Somatic Aggregation Workflow +### Tumor-Only Variant Calling Workflow + +Tumor only variant calling is performed on a tumor sample with no paired normal at the request of the research group. This method takes advantage of the normal cell contamination that is present in most tumor samples. These calls are made using the version of MuTect2 included in GATK4. Tumor-only variant call files can be found in the GDC Portal by filtering for "Workflow Type: GATK4 MuTect2". + +### Tumor-Only Variant Call Command-Line Parameters +``` +GATK4 v4 + +## 1. Generate OXOG metrics: + +java -d64 -XX:+UseSerialGC -Xmx3G -jar /gatk/gatk.jar \ +CollectSequencingArtifactMetrics \ +-I Tumor_Sample_Alignment.bam \ +-O \ +--FILE_EXTENSION .txt \ +-R GRCh38.d1.vd1.fa ## Only chr1-22 + XYM + +## 2. Generate pileup summaries on tumor sample: + +java -d64 -XX:+UseSerialGC -Xmx3G -jar /gatk/gatk.jar \ +GetPileupSummaries +-I Tumor_Sample_Alignment.bam \ +-O .targeted_sequencing.table \ +-V af-only-gnomad-common-biallelic.grch38.main.vcf.gz \ # Germline reference from gnomad +-L intervals.bed \ ## Only chr1-22 + XYM +-R GRCh38.d1.vd1.fa + +## 3. Calculate contamination on tumor sample + +java -d64 -XX:+UseSerialGC -Xmx3G -jar /gatk/gatk.jar \ +CalculateContamination \ +-I .targeted_sequencing.table \ # From step 2 +-O .targeted_sequencing.contamination.table + +## 4. Find tumor sample name from BAM + +java -d64 -XX:+UseSerialGC -Xmx3G -jar /gatk/gatk.jar \ +GetSampleName \ +-I Tumor_Sample_Alignment.bam \ +-O .targeted_sequencing.sample_name + +## 5. Run MuTect2 using only tumor sample on chromosome level (25 commands with different intervals) + +java -Djava.io.tmpdir=/tmp/job_tmp_3 -d64 -jar -Xmx3G -XX:+UseSerialGC \ +/bin/gatk-4.2.4.0/gatk-package-4.2.4.0-local.jar \ +Mutect2 \ +-R GRCh38.d1.vd1.fa \ +-L chr4:1-190214555 \ # Specify chromosome +-I Tumor_Sample_Alignment.bam \ +-O 3.mt2.vcf \ +-tumor \ # From step 4 +--af-of-alleles-not-in-resource 2.5e-06 \ +--germline-resource af-only-gnomad.hg38.vcf.gz \ # Germline reference from gnomad +-pon gatk4_mutect2_4136_pon.vcf.gz # New panel of normal created by 4136 TCGA curated normal samples, using GATK4 + +## After this step, all chromosome level VCFs are merged into one. + +## 6. Sort VCF with Picard + +java -d64 -XX:+UseSerialGC -Xmx16G -jar /usr/local/bin/picard.jar \ +SortVcf \ +SEQUENCE_DICTIONARY=GRCh38.d1.vd1.dict \ +OUTPUT=.targeted_sequencing.mutect2.tumor_only.sorted.vcf.gz \ +I=merged_multi_gatk4_mutect2_tumor_only_calling.vcf \ # From step 5 +CREATE_INDEX=true + +## 7. Filter variant calls from MuTect +java -d64 -XX:+UseSerialGC -Xmx3G -jar /gatk/gatk.jar \ +FilterMutectCalls \ +-O .targeted_sequencing.mutect2.tumor_only.contFiltered.vcf.gz \ +-V .targeted_sequencing.mutect2.tumor_only.sorted.vcf.gz \ # From step 6 +--contamination-table .targeted_sequencing.contamination.table \ # From step 3 +-L intervals.bed + +## 8. Filter variants by orientation bias +java -d64 -XX:+UseSerialGC -Xmx3G -jar /gatk/gatk.jar \ +FilterByOrientationBias \ +-O .targeted_sequencing.tumor_only.gatk4_mutect2.raw_somatic_mutation.vcf.gz \ # final output +-P .pre_adapter_detail_metrics.txt \ # From step 1 +-V .targeted_sequencing.mutect2.tumor_only.contFiltered.vcf.gz \ # From step 7 +-L intervals.bed \ +-R GRCh38.d1.vd1.fa \ +-AM G/T \ +-AM C/T +``` + +### Tumor-Only Variant Annotation Workflow -The Somatic Aggregation Workflow generates one MAF file from multiple VCF files; see the [GDC MAF Format](/Data/File_Formats/MAF_Format/) guide for details on file structure. In this step, one MAF file is generated per variant calling pipeline for each project, and contains all available cases within this project. +After single-tumor variant calling is performed with MuTect2, a series of filters are applied to minimize the release of germline variants in downloadable VCFs. In all cases, the GDC applies a set of custom filters based on allele frequency, mapping quality, somatic/germline probability, and copy number. In some cases an additional variant classification step is applied before the GDC filters. +The [PureCN](https://bioconductor.org/packages/devel/bioc/html/PureCN.html) R-package [[7]](https://doi.org/10.1186/s13029-016-0060-z) [[8]](https://doi.org/10.1101/552711) is used to classify the variants by somatic/germline status and clonality based on tumor purity, ploidy, contamination, copy number, and loss of heterozygosity. The following steps are performed with this package: + +* __Interval Capture__ : Generates an interval file using a FASTA and BED file coordinates. +* __GC-Normalization__ : Calculates GC-normalized tumor/normal coverage data. +* __Normal DB Creation__ : Generates a normal database using the normalized coverage file and panel-of-normals VCF +* __Somatic Variant Calling__ : Classifies each of the previously called variants + +Note that PureCN will not be performed if there is insufficient data to produce a target capture kit specific normal database. In rare occasions, PureCN may not find a numeric solution. If PureCN is not performed or does not find a solution, this is indicated in the VCF header. VCF files that were annotated with these pipelines can be found in the GDC Portal by filtering for "Workflow Type: GATK4 MuTect2 Annotation". + +### Somatic Aggregation Workflow + +The Somatic Aggregation Workflow generates one MAF file from multiple VCF files; see the [GDC MAF Format](/Data/File_Formats/MAF_Format/) guide for details on file structure. In this step, one MAF file is generated per variant calling pipeline for each project and contains all available cases within this project. | I/O | Entity | Format | |---|---|---| @@ -366,15 +555,65 @@ The Somatic Aggregation Workflow generates one MAF file from multiple VCF files; The MAF files generated by Somatic Aggregation Workflow are controlled-access due to the presence of germline mutations. Open-access MAF files are modified for public release by removing columns and variants that could potentially contain germline mutation information. See the GDC [MAF Format](../File_Formats/MAF_Format/) for details about the criteria used to remove variants. -While these criteria cause the pipeline to over-filter some of the true positive somatic variants in open-access MAF files, they prevent personally identifiable germline mutation information from becoming publicly available. The GDC recommends that investigators explore both controlled and open-access MAF files if omission of certain somatic mutations is a concern. +While these criteria cause the pipeline to over-filter some of the true positive somatic variants in open-access MAF files, they prevent personally identifiable germline mutation information from becoming publicly available. The GDC recommends that investigators explore both controlled and open-access MAF files if omission of certain somatic mutations is a concern. | I/O | Entity | Format | |---|---|---| | Input | [Aggregated Somatic Mutation](/Data_Dictionary/viewer/#?view=table-definition-view&id=aggregated_somatic_mutation) | Protected MAF | | Output | [Masked Somatic Mutation](/Data_Dictionary/viewer/#?view=table-definition-view&id=masked_somatic_mutation) | Somatic MAF | -## File Access and Availability +### Whole Genome Sequencing Variant Calling + +Variant calls are generated from WGS data using a different pipeline than WXS and Targeted Sequencing samples. This pipeline, based on a [workflow generated by the Sanger Institute](https://github.com/cancerit/dockstore-cgpwgs), generates multiple downstream data types using the following software packages: + +* __CaVEMan:__ Single nucleotide variants, which are available in [VCF format](https://docs.gdc.cancer.gov/Data/File_Formats/VCF_Format/). +* __Pindel:__ Small indel variants, which are available in [VCF format](https://docs.gdc.cancer.gov/Data/File_Formats/VCF_Format/). +* __BRASS:__ Structural variants, which are available in *BEDPE format*. +* __AscatNGS:__ Copy number variants, which are available as copy number estimates or copy number segment files, data may be available in *tab separated values (.TSV) or plain text file (.TXT)* +#### BEDPE File Format + +[BEDPE file format](https://bedtools.readthedocs.io/en/latest/content/general-usage.html#bedpe-format), (**b**rowser **e**xtensible **d**ata **p**aired-**e**nd) is designed to concisely describe disjoint genome features, such as structural variations or paired-end sequence alignments. It's an enhanced version of the [BED format](http://genome.ucsc.edu/FAQ/FAQformat#format1), as BED does not allow inter-chromosomal feature definitions. In addition, BED only has one strand field, which is insufficient for paired-end sequence alignments, especially when studying structural variation. The BEDPE format is described below. + + +* __chr*x* (required):__ The name of the chromosome on which the *x*th end of the feature exists. (x is 1 or 2). Any string can be used. For example, "chr1", "III", "myChrom", "contig1112.23" (use "." for unknown). +* __start*x* (required):__ The zero-based starting position of the **first** end of the feature on chr*x*. The first base in a chromosome is numbered 0. The start position in each BEDPE feature is therefore interpreted to be 1 greater than the start position listed in the feature (use -1 for unknown). +* __end*x* (required):__ The one-based ending position of the first end of the feature on chr*x*. The end position in each BEDPE feature is one-based (use -1 for unknown). +* __name (optional):__ Defines the name of the BEDPE feature. Any string can be used. +* __score (optional):__ A score between 0 and 1000. If the track line *useScore* attribute is set to 1 for this annotation data set, the score value will determine the level of gray in which this feature is displayed (higher numbers = darker gray). Any string can be used. +* __strand*x* (optional):__ Defines the strand for the *x*th end of the feature. Either "." (unknown), "+", or "-". + +In addition to the above fields, bedtools allows for the addition of user-defined fields to the normal, 10-column BEDPE format as necessary. These columns are merely "passed through" pairToBed and pairToPair and are not part of any analysis. One would use these additional columns to add extra information (e.g., edit distance for each end of an alignment, or "deletion", "inversion", etc.) to each BEDPE feature. + +#### CNV from WGS File Format + +AscatNGS, originally developed by [Raine *et al* (2016)]( https://doi.org/10.1002/cpbi.17) ([GitHub page](https://github.com/cancerit)), indicates the DNA copy number changes affecting a tumor genome when comparing to a matched normal sample. See below for a description of the copy number segment and copy number estimation files produced by AscatNGS: + +* __GDC Aliquot:__ The GDC ID for the aliquot collected from the sample (copy number segment files only). +* __Gene ID:__ The gene ENSMBL ID (copy number variant only). +* __Gene Name:__ The gene symbol (copy number variant only). +* __Chromosome:__ The name of the chromosome on which the copy number change exists. +* __Start:__ The starting position of the copy. +* __End:__ The ending position of the copy. +* __Copy Number:__ The weighted median of the strand copy numbers [9]. +* __Major Copy Number:__ The greater strand copy number of the two strands of the DNA (copy number segment files only). +* __Minor Copy number:__ The smaller strand copy number of the two strands of the DNA (copy number segment files only). +* __Max. Copy number:__ The highest copy number for overlapped segment (copy number variant only). +* __Min. Copy number:__ The lowest copy number for overlapped segment (copy number variant only). + +## Microsatellite Instability Detection + +The GDC adopts [MSIsensor2](https://github.com/niu-lab/msisensor2) to derive Microsatellite Instability (MSI) information from tumor DNA-Seq data. The MSIsensor2 software uses only the tumor BAM as input, and calculates the numeric MSI score (number of msi sites / all valid sites). The MSI status of MSI (Microsatellite Instable) or MSS (Microsatellite Stable) is then determined using a MSI score cutoff value of 20%. + +The output `msi_score` and `msi_status` values are stored directly as properties of the `aligned_reads` (BAM files), and can be [accessible via API](https://api.gdc.cancer.gov/files/82488c57-9789-449c-a09d-594172381dc1?pretty=true&fields=msi_score,msi_status,file_id,file_name). In addition, the portal/API can be filtered using these proprties by choosing "Add a File Filter" in the [Repository Page](https://portal.gdc.cancer.gov/v1/repository) and selecting `msi_score` or `msi_status`. + +Please note: + +1. MSI status generated from DNA-Seq by the GDC is considered bioinformatics-derived information, and is not considered clinical data. If performed by the clinical lab, the clinical MSI test result would be stored as a `laboratory_test` in the molecular_test entity. +2. MSIsensor2 can theoretically be applied to WGS, WXS, or Targeted Sequencing data. Given the number of MSI sites available in some Targeted Sequencing data, please consider the results carefully. +3. It is possible that multiple MSI statuses exist within the same sample/case if more than one DNA-Seq BAM was generated. It is the users' responsibility to check for their consistency, especially when the MSI scores are close to 20%. + +## File Access and Availability Files from the GDC DNA-Seq analysis pipeline are available in the [GDC Data Portal](https://portal.gdc.cancer.gov) in BAM, VCF, and MAF formats. Descriptions are listed below for all available data types and their respective file formats. @@ -398,4 +637,10 @@ Files from the GDC DNA-Seq analysis pipeline are available in the [GDC Data Port [5]. Larson, David E., Christopher C. Harris, Ken Chen, Daniel C. Koboldt, Travis E. Abbott, David J. Dooling, Timothy J. Ley, Elaine R. Mardis, Richard K. Wilson, and Li Ding. "SomaticSniper: identification of somatic point mutations in whole genome sequencing data." Bioinformatics 28, no. 3 (2012): 311-317. -[6] McLaren, William, Bethan Pritchard, Daniel Rios, Yuan Chen, Paul Flicek, and Fiona Cunningham. "Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor." Bioinformatics 26, no. 16 (2010): 2069-2070. +[6]. McLaren, William, Bethan Pritchard, Daniel Rios, Yuan Chen, Paul Flicek, and Fiona Cunningham. "Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor." Bioinformatics 26, no. 16 (2010): 2069-2070. + +[7]. Riester, Markus, Angad P. Singh, A. Rose Brannon, Kun Yu, Catarina D. Campbell, Derek Y. Chiang, and Michael P. Morrissey. "PureCN: copy number calling and SNV classification using targeted short read sequencing." Source code for biology and medicine 11, no. 1 (2016): 13. + +[8]. Oh, Sehyun, Ludwig Geistlinger, Marcel Ramos, Martin Morgan, Levi Waldron, and Markus Riester. "Reliable analysis of clinical tumor-only whole exome sequencing data" bioRxiv 552711 (2019); + +[9]. Gene-level copy number data is generated by intersection of copy number segment and gene ranges. It is possible for one gene to overlap with multiple segments, and in this case, copy_number, min_copy_number and max_copy_number could take different values. In particular, the copy_number value is calculated as the median, weighted on length of overlapped bases, of segment copy numbers from all overlapped segments. diff --git a/docs/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline.md b/docs/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline.md index 0519ef59d..a45f0dbfe 100644 --- a/docs/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline.md +++ b/docs/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline.md @@ -1,14 +1,20 @@ # mRNA Analysis Pipeline ## Introduction -The GDC mRNA quantification analysis pipeline measures gene level expression in [HT-Seq](http://www-huber.embl.de/HTSeq/doc/overview.html) raw read count, Fragments per Kilobase of transcript per Million mapped reads (FPKM), and FPKM-UQ (upper quartile normalization). These values are generated through this pipeline by first aligning reads to the GRCh38 [reference genome](https://gdc.cancer.gov/download-gdc-reference-files) and then by quantifying the mapped reads. To facilitate harmonization across samples, all RNA-Seq reads are treated as unstranded during analyses. +The GDC mRNA quantification analysis pipeline measures gene level expression with [STAR](https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf) as raw read counts. Subsequently the counts are augmented with several transformations including Fragments per Kilobase of transcript per Million mapped reads (FPKM), upper quartile normalized FPKM (FPKM-UQ), and Transcripts per Million (TPM). These values are additionally annotated with the gene symbol and gene bio-type. These data are generated through this pipeline by first aligning reads to the GRCh38 [reference genome](https://gdc.cancer.gov/download-gdc-reference-files) and then by quantifying the mapped reads. To facilitate harmonization across samples, all RNA-Seq reads are treated as unstranded during analyses. ## Data Processing Steps ### RNA-Seq Alignment Workflow -The mRNA Analysis pipeline begins with the [Alignment Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=alignment_workflow), which is performed using a two-pass method with [STAR](http://labshare.cshl.edu/shares/gingeraslab/www-data/dobin/STAR/STAR.posix/doc/STARmanual.pdf). STAR aligns each [read group](/Data_Dictionary/viewer/#?view=table-definition-view&id=read_group) separately and then merges the resulting alignments into one. Following the methods used by the International Cancer Genome Consortium [ICGC](https://icgc.org/) ([github](https://github.com/akahles/icgc_rnaseq_align)), the two-pass method includes a splice junction detection step, which is used to generate the final alignment. This workflow outputs a BAM file, which contains both aligned and unaligned reads. Quality assessment is performed pre-alignment with [FASTQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and post-alignment with [RNA-SeQC](https://www.broadinstitute.org/cancer/cga/rna-seqc) and [Picard Tools](http://broadinstitute.github.io/picard/). +The mRNA Analysis pipeline begins with the [Alignment Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=alignment_workflow), which is performed using a two-pass method with [STAR](https://github.com/alexdobin/STAR/blob/master/doc/STARmanual.pdf). STAR aligns each [read group](/Data_Dictionary/viewer/#?view=table-definition-view&id=read_group) separately and then merges the resulting alignments into one. Following the methods used by the International Cancer Genome Consortium [ICGC](https://icgc.org/) ([github](https://github.com/akahles/icgc_rnaseq_align)), the two-pass method includes a splice junction detection step, which is used to generate the final alignment. This workflow outputs a genomic BAM file, which contains both aligned and unaligned reads. Quality assessment is performed pre-alignment with [FASTQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and post-alignment with [Picard Tools](http://broadinstitute.github.io/picard/). -[![RNA Alignment Pipeline](images/rna-alignment-pipeline-resized.png)](images/gene-expression-quantification-pipeline.png "Click to see the full image.") +Files that were processed after Data Release 14 have associated transcriptomic and chimeric alignments in addition to the genomic alignment detailed above. This only applies to aliquots with at least one set of paired-end reads. The chimeric BAM file contains reads that were mapped to different chromosomes or strands (fusion alignments). The genomic alignment files contain chimeric and unaligned reads to facilitate the retrieval of all original reads. The transcriptomic alignment reports aligned reads with transcript coordinates rather than genomic coordinates. The transcriptomic alignment is also sorted differently to facilitate downstream analyses. BAM index file pairing is not supported by this method of sorting, which does not allow for BAM slicing on these alignments. The splice-junction file for these alignments are also available. + +Files that were processed after Data Release 25 will have associated [gene fusion files](#fusion-pipelines). + +As of Data Release 32 the reference annotation will be updated to GENCODE v36 and HT-Seq will no longer be used. + +[![RNA Alignment Pipeline](images/RNA-Seq-DR32_Image.png)](images/RNA-Seq-DR32_Image.png "Click to see the full image.") | I/O | Entity | Format | |---|---|---| @@ -17,13 +23,13 @@ The mRNA Analysis pipeline begins with the [Alignment Workflow](/Data_Dictionary ### RNA-Seq Alignment Command Line Parameters -####STAR-2.4.2a +__Note that version numbers may vary in files downloaded from the GDC Data Portal due to ongoing pipeline development and improvement.__ -####ICGC STAR alignment pipeline +```Original +# STAR-2 -__For users with access to the ICGC pipeline:__ +### For users with access to the ICGC pipeline: -```Shell python star_align.py \ --genomeDir \ --FastqFileIn \ @@ -46,24 +52,21 @@ python star_align.py \ --sjdbOverhang 100 \ --outSAMstrandField intronMotif \ --outSAMunmapped Within -``` -__For users without access to the ICGC pipeline:__ +### For users without access to the ICGC pipeline: + +### Step 1: Building the STAR index.* -#### Step 1: Building the STAR index.* -```Shell STAR --runMode genomeGenerate --genomeDir --genomeFastaFiles --sjdbOverhang 100 ---sjdbGTFfile +--sjdbGTFfile --runThreadN 8 -``` -\*These indices are available for download at the [GDC Website](https://gdc.cancer.gov/about-data/data-harmonization-and-generation/gdc-reference-files) and do not need to be built again. -#### Step 2: Alignment 1st Pass. -```Shell +### Step 2: Alignment 1st Pass. + STAR --genomeDir --readFilesIn ,,... ,,... @@ -83,9 +86,9 @@ STAR --outSAMstrandField intronMotif --outSAMtype None --outSAMmode None -``` -#### Step 3: Intermediate Index Generation. -```Shell + +### Step 3: Intermediate Index Generation. + STAR --runMode genomeGenerate --genomeDir @@ -93,9 +96,9 @@ STAR --sjdbOverhang 100 --runThreadN --sjdbFileChrStartEnd -``` -#### Step 4: Alignment 2nd Pass. -```Shell + +### Step 4: Alignment 2nd Pass. + STAR --genomeDir --readFilesIn ,,... ,,... @@ -120,54 +123,152 @@ STAR --outSAMheaderHD @HD VN:1.4 --outSAMattrRGline ``` +```DR15Plus +# STAR-2 + +STAR \ +--readFilesIn \ +--outSAMattrRGline \ +--alignIntronMax 1000000 \ +--alignIntronMin 20 \ +--alignMatesGapMax 1000000 \ +--alignSJDBoverhangMin 1 \ +--alignSJoverhangMin 8 \ +--alignSoftClipAtReferenceEnds Yes \ +--chimJunctionOverhangMin 15 \ +--chimMainSegmentMultNmax 1 \ +--chimOutType Junctions SeparateSAMold WithinBAM SoftClip \ +--chimSegmentMin 15 \ +--genomeDir \ +--genomeLoad NoSharedMemory \ +--limitSjdbInsertNsj 1200000 \ +--outFileNamePrefix \ +--outFilterIntronMotifs None \ +--outFilterMatchNminOverLread 0.33 \ +--outFilterMismatchNmax 999 \ +--outFilterMismatchNoverLmax 0.1 \ +--outFilterMultimapNmax 20 \ +--outFilterScoreMinOverLread 0.33 \ +--outFilterType BySJout \ +--outSAMattributes NH HI AS nM NM ch \ +--outSAMstrandField intronMotif \ +--outSAMtype BAM Unsorted \ +--outSAMunmapped Within \ +--quantMode TranscriptomeSAM GeneCounts \ +--readFilesCommand \ +--runThreadN \ +--twopassMode Basic +``` +```DR32 +# STAR Genome Index +STAR +--runMode genomeGenerate +--genomeDir +--genomeFastaFiles +--sjdbOverhang 100 +--sjdbGTFfile +--runThreadN 8 + +# STAR Alignment +# STAR v2 +STAR +--readFilesIn \ +--outSAMattrRGline \ +--genomeDir \ +--readFilesCommand \ +--runThreadN \ +--twopassMode Basic \ +--outFilterMultimapNmax 20 \ +--alignSJoverhangMin 8 \ +--alignSJDBoverhangMin 1 \ +--outFilterMismatchNmax 999 \ +--outFilterMismatchNoverLmax 0.1 \ +--alignIntronMin 20 \ +--alignIntronMax 1000000 \ +--alignMatesGapMax 1000000 \ +--outFilterType BySJout \ +--outFilterScoreMinOverLread 0.33 \ +--outFilterMatchNminOverLread 0.33 \ +--limitSjdbInsertNsj 1200000 \ +--outFileNamePrefix \ +--outSAMstrandField intronMotif \ +--outFilterIntronMotifs None \ +--alignSoftClipAtReferenceEnds Yes \ +--quantMode TranscriptomeSAM GeneCounts \ +--outSAMtype BAM Unsorted \ +--outSAMunmapped Within \ +--genomeLoad NoSharedMemory \ +--chimSegmentMin 15 \ +--chimJunctionOverhangMin 15 \ +--chimOutType Junctions SeparateSAMold WithinBAM SoftClip \ +--chimOutJunctionFormat 1 \ +--chimMainSegmentMultNmax 1 \ +--outSAMattributes NH HI AS nM NM ch +``` + +\*These indices are available for download at the [GDC Website](https://gdc.cancer.gov/about-data/data-harmonization-and-generation/gdc-reference-files) and do not need to be built again. + ### mRNA Expression Workflow -Following alignment, BAM files are processed through the [RNA Expression Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=rna_expression_workflow). -First the BAM files are filtered for aligned reads using the [samtools](http://samtools.sourceforge.net) view function. The reads mapped to each gene are enumerated using HT-Seq count. Expression values are provided in a tab-delimited format. [GENCODE v22](http://www.gencodegenes.org/releases/22.html) was used for gene annotation. +The primary counting data is generated by STAR and includes a gene ID, unstranded, and stranded counts data. Following alignment, the raw counts files produced by STAR are augmented with commonly used counts transformations (FPKM, FPKM-UQ, and TPM) along with basic annotations as part of the [RNA Expression Workflow](/Data_Dictionary/viewer/#?view=table-definition-view&id=rna_expression_workflow). These data are provided in a tab-delimited format. [GENCODE v36](https://www.gencodegenes.org/human/release_36.html) was used for gene annotation. -[![Gene Expression Pipeline](images/gene-expression-quantification-pipeline.png)](images/gene-expression-quantification-pipeline.png "Click to see the full image.") +Note that the STAR counting results will not count reads that are mapped to more than one different gene. Below are two files that list genes that are completely encompassed by other genes and will likely display a value of zero. +* [Overlapped Genes (stranded)](/Data/Bioinformatics_Pipelines/overlap.gene.stranded.tsv) +* [Overlapped Genes (unstranded)](/Data/Bioinformatics_Pipelines/overlap.gene.strandless.tsv) | I/O | Entity | Format | |---|---|---| | Input | [Aligned Reads](/Data_Dictionary/viewer/#?view=table-definition-view&id=aligned_reads) | BAM | -| Output | [Gene Expression (HTSeq count/ FPKM/ FPKM-UQ)](/Data_Dictionary/viewer/#?view=table-definition-view&id=gene_expression) | TXT | +| Output | [Gene Expression](/Data_Dictionary/viewer/#?view=table-definition-view&id=gene_expression) | TXT | ### mRNA Quantification Command Line Parameters -Samtools v1.1; HTSeq-0.6.1p1 +HTSeq -```Shell -samtools view -F 4 | +```Current +Counts are produced by STAR concurrent with alignment. +``` +```Original htseq-count \ -m intersection-nonempty \ -i gene_id \ -r pos \ -s no \ - gencode.v22.annotation.gtf - +``` +```DR15-31 +htseq-count \ +-f bam \ +-r name \ +-s no \ +-a 10 \ +-t exon \ +-i gene_id \ +-m intersection-nonempty \ + \ + > ``` -## mRNA Expression Normalization +## mRNA Expression Transformation -RNA-Seq expression level read counts are normalized using two related methods: FPKM and FPKM-UQ. Normalized values should be used only within the context of the entire gene set. Users are encouraged to normalize raw read count values if a subset of genes is investigated. +RNA-Seq expression level read counts produced by the workflow are normalized using three commonly used methods: FPKM, FPKM-UQ, and TPM. Normalized values should be used only within the context of the entire gene set. Users are encouraged to normalize raw read count values if a subset of genes is investigated. ### FPKM -The Fragments per Kilobase of transcript per Million mapped reads (FPKM) calculation normalizes read count by dividing it by the gene length and the total number of reads mapped to protein-coding genes. +The fragments per kilobase of transcript per million mapped reads (FPKM) calculation aims to control for transcript length and overall sequencing quantity. ### Upper Quartile FPKM -The upper quartile FPKM (FPKM-UQ) is a modified FPKM calculation in which the total protein-coding read count is replaced by the 75th percentile read count value for the sample. +The upper quartile FPKM (FPKM-UQ) is a modified FPKM calculation in which the protein coding gene in the 75th percentile position is substituted for the sequencing quantity. This is thought to provide a more stable value than including the noisier genes at the extremes. -### Calculations +### TPM -[![FPKM Calculations](images/Calc_FPKM_andUQ.png)](images/Calc_FPKM_andUQ.png "Click to see the full image.") +The transcripts per million calculation is similar to FPKM, but the difference is that all transcripts are normalized for length first. Then, instead of using the total overall read count as a normalization for size, the sum of the length-normalized transcript values are used as an indicator of size. + +### Calculations -- __RCg:__ Number of reads mapped to the gene -- __RCpc:__ Number of reads mapped to all protein-coding genes -- __RCg75:__ The 75th percentile read count value for genes in the sample -- __L:__ Length of the gene in base pairs; Calculated as the sum of all exons in a gene +[![FPKM Calculations](images/normalizations_calc.png)](images/normalizations_calc.png "Click to see the full image.") __Note:__ The read count is multiplied by a scalar (109) during normalization to account for the kilobase and 'million mapped reads' units. @@ -179,18 +280,58 @@ __Sample 1: Gene A__ * 1,000 reads mapped to Gene A * 1,000,000 reads mapped to all protein-coding regions * Read count in Sample 1 for 75th percentile gene: 2,000 +* Number of protein coding genes on autosomes: 19,029 +* Sum of length-normalized transcript counts: 9,000,000 + +__FPKM for Gene A__ = 1,000 \* 10^9 / (3,000 \* 50,000,000) = __6.67__ + +__FPKM-UQ for Gene A__ = 1,000) \* 10^9 / (3,000 \* 2,000 \* 19,029) = __8.76__ + +__TPM for Gene A__ = (1,000 * 1,000 / 3,000) * 1,000,000 / (9,000,000) = __37.04__ + +## Fusion Pipelines + +The GDC uses two pipelines for the detection of gene fusions. + +### STAR-Fusion Pipeline +The GDC gene fusion pipeline uses the STAR-Fusion v1.6 algorithm to generate gene fusion data. +STAR-Fusion pipeline processes the output generated by STAR aligner to map junction reads +and spanning reads to a junction annotation set. It utilizes a chimeric junction file from +running the STAR aligner and produces a tab-limited gene fusion prediction file. +The prediction file provides fused gene names, junction read count and breakpoint information. + +### Arriba Fusion Pipeline + +The [Arriba gene fusion pipeline](https://github.com/suhrig/arriba) uses Arriba v1.1.0 to detect gene fusions from the RNA-Seq data of tumor samples. + + +## scRNA-Seq Pipeline (single-nuclei) + +The GDC processes single-cell RNA-Seq (scRNA-Seq) data using the [Cell Ranger pipeline](https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger) to calculate gene expression followed by [Seurat](https://satijalab.org/seurat/) for secondary expression analysis. + +### scRNA Gene Expression Pipeline + +The gene expression pipeline, which uses Cell Ranger, generates three files: + +* Aligned reads file (BAM) +* Raw counts matrix - contains all barcodes in [Market Exchange Format](https://math.nist.gov/MatrixMarket/formats.html) (MEX) +* Filtered counts matrix - contains only detected cellular barcodes (MEX) + +### scRNA Analysis Pipeline + +The analysis pipeline, which uses the Seurat software, generates three files from an input of Filtered counts matrix: -__FPKM for Gene A__ = (1,000)\*(10^9)/[(3,000)\*(1,000,000)] = __333.33__ +* Analysis - PCA, UMAP, tSNE values, and graph-based clustering results with associated metadata (TSV). +* Differential gene expression - DEG information comparing cells from one cluster to the rest of the cells (TSV). +* Full Seurat analysis log as a loom object in [HDF5](https://portal.hdfgroup.org/hdf5/v1_14/_u_g.html) format. -__FPKM-UQ for Gene A__ = (1,000)\*(10^9)/[(3,000)\*(2,000)] = __166,666.67__ +When the input RNA was extracted from nuclei instead of cytoplasm, a slightly modified quantification method is implemented to include introns. Currently, these single-nuclei RNA-Seq (snRNA-Seq) analyses share the same experimental strategy (scRNA-Seq) in the Data Portal, and can be filtered by querying for aliquot.analyte_type = "Nuclei RNA". ## File Access and Availability -To facilitate the use of harmonized data in user-created pipelines, RNA-Seq gene expression is accessible in the GDC Data Portal at several intermediate steps in the pipeline. Below is a description of each type of file available for download in the GDC Data Portal. +To facilitate the use of harmonized data in user-created pipelines, RNA-Seq gene expression is accessible in the GDC Data Portal at several intermediate steps in the pipeline. Below is a description of each type of file available for download in the GDC Data Portal. | Type | Description | Format | |---|---|---| -| RNA-Seq Alignment | RNA-Seq reads that have been aligned to the GRCh38 build. Reads that were not aligned are included to facilitate the availability of raw read sets | BAM | -| Raw Read Counts | The number of reads aligned to each gene, calculated by HT-Seq | TXT | -| FPKM | A normalized expression value that takes into account each gene length and the number of reads mapped to all protein-coding genes | TXT | -| FPKM-UQ | A modified version of the FPKM formula in which the 75th percentile read count is used as the denominator in place of the total number of protein-coding reads | TXT | +| RNA-Seq Alignment | RNA-Seq reads that have been aligned to the GRCh38 build. Reads that were not aligned are included to facilitate the availability of raw read sets. | BAM | +| STAR Read Counts | The number of reads aligned to each gene, calculated by STAR, along with values using common normalization methods. | TSV | diff --git a/docs/Data/Bioinformatics_Pipelines/Methylation_LO_Pipeline.md b/docs/Data/Bioinformatics_Pipelines/Methylation_LO_Pipeline.md deleted file mode 100644 index 637b2506c..000000000 --- a/docs/Data/Bioinformatics_Pipelines/Methylation_LO_Pipeline.md +++ /dev/null @@ -1,41 +0,0 @@ -# Methylation Liftover Pipeline - -## Introduction - -The [DNA Methylation Liftover Pipeline](https://gdc-docs.nci.nih.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=methylation_liftover_workflow) uses data from the Illumina Infinium Human Methylation 27 (HM27) and HumanMethylation450 (HM450) arrays to measure the level of methylation at known CpG sites as beta values, calculated from array intensities (Level 2 data) as Beta = M/(M+U). - -Using probe sequence information provided in the manufacturer's manifest, HM27 and HM450 probes were remapped to the GRCh38 reference genome [1]. Type II probes with a mapping quality of <10, or Type I probes for which the methylated and unmethylated probes map to different locations in the genome, and/or had a mapping quality of <10, had an entry of '\*' for the 'chr' field, and '-1' for coordinates. These coordinates were then used to identify the associated transcripts from GENCODE v22, the associated CpG island (CGI), and the CpG sites' distance from each of these features. Multiple transcripts overlapping the target CpG were separated with semicolons. Beta values were inherited from existing TCGA Level 3 DNA methylation data (hg19-based) based on Probe IDs. - - -## Methylation Beta Values Table Format - -Descriptions for fields present in GDC Harmonized Methylation Beta Values Table are detailed below: - -| Field | Definition | -|---|---| -| Composite Element | A unique ID for the array probe associated with a CpG site | -| Beta Value | Represents the ratio between the methylated array intensity and total array intensity, falls between 0 (lower levels of methylation) and 1 (higher levels of methylation) | -| Chromosome | The chromosome in which the probe binding site is located | -| Start | The start of the CpG site on the chromosome | -| End | The end of the CpG site on the chromosome | -| Gene Symbol | The symbol for genes associated with the CpG site. Genes that fall within 1,500 bp upstream of the transcription start site (TSS) to the end of the gene body are used. | -| Gene Type | A general classification for each gene (e.g. protein coding, miRNA, pseudogene) | -| Transcript ID | Ensembl transcript IDs for each transcript associated with the genes detailed above | -| Position to TSS | Distance in base pairs from the CpG site to each associated transcript's start site | -| CGI Coordinate | The start and end coordinates of the CpG island associated with the CpG site | -| Feature Type | The position of the CpG site in reference to the island: Island, N_Shore or S_Shore (0-2 kb upstream or downstream from CGI), or N_Shelf or S_Shelf (2-4 kbp upstream or downstream from CGI) | - ---- -| I/O | Entity | Format | -|---|---|---| -| Input | [Submitted Methylation Beta Values](/Data_Dictionary/viewer/#?view=table-definition-view&id=submitted_methylation_beta_value) | TXT | -| Output | [Methylation Beta Values](/Data_Dictionary/viewer/#?view=table-definition-view&id=methylation_beta_value) or Masked Copy Number Segment | TXT | - -## File Access and Availability - -| Type | Description | Format | -|---|---|---| -| Methylation Beta Value | A table that associates array probes with CpG sites and associated metadata. | TXT | - - -[1]. Zhou, Wanding, Laird Peter L., and Hui Shen. "Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes." Nucleic Acids Research. (2016): doi: 10.1093/nar/gkw967 diff --git a/docs/Data/Bioinformatics_Pipelines/Methylation_Pipeline.md b/docs/Data/Bioinformatics_Pipelines/Methylation_Pipeline.md new file mode 100644 index 000000000..73e01b48a --- /dev/null +++ b/docs/Data/Bioinformatics_Pipelines/Methylation_Pipeline.md @@ -0,0 +1,73 @@ +# Methylation Analysis + +## Methylation Array Harmonization Workflow + +### Introduction + +The [Methylation Array Harmonization Workflow](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=methylation_array_harmonization_workflow) uses raw methylation array data from multiple generations of Illumina Infinium DNA methylation arrays, namely Human Methylation 27 (HM27), HumanMethylation 450 (HM450) and EPIC platforms, to measure the level of methylation at known CpG sites as beta values, calculated from array intensities (Level 2 data) as Beta = M/(M+U). This differs from the [Methylation Liftover Pipeline](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=methylation_liftover_workflow) in that the raw methylation array data is used instead of submitted methylation beta values, and the data is processed through the software package [SeSAMe](https://github.com/zwdzwd/sesame)[1]. Additionally, the analysis results from the Methylation Array Harmonization Workflow are expected to be of higher quality than results from the Methylation Liftover Pipeline. + +SeSAMe offers correction to detection failures that occur in other DNA methylation array software commonly due to germline and somatic deletions by utilizing a novel way to calculate the significance of detected signals in methylation arrays. By correcting for these artifacts as well as other improvements to DNA methylation data processing, SeSAMe improves upon detection calling and quality control of processed DNA methylation data. SeSAMe output files include: two Masked Methylation Array IDAT files, one for each color channel, that contains channel data from a raw methylation array after masking potential genotyping information; and a subsequent Methylation Beta Value TXT file derived from the two Masked Methylation Array IDAT files, that displays the calculated methylation beta value for CpG sites. + +### SeSAMe Methylation Beta Values File Format + +Descriptions for fields present in GDC Harmonized Methylation Beta Values File are detailed below: + +| Field | Definition | +|---|---| +| Composite Element | A unique ID for the array probe associated with a CpG site | +| Beta Value | Represents the ratio between the methylated array intensity and total array intensity, falls between 0 (lower levels of methylation) and 1 (higher levels of methylation) | + +--- + +| I/O | Entity | Format | +|---|---|---| +| Input | [Raw Methylation Array](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=raw_methylation_array) | IDAT | +| Output | [Masked Methylation Array](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=masked_methylation_array) | IDAT | +| Output | [Methylation Beta Values](/Data_Dictionary/viewer/#?view=table-definition-view&id=methylation_beta_value) | TXT | + + +## Methylation Liftover Pipeline + +### Note: as of Data Release 32, Methylation Liftover files are no longer supported and do not appear in the GDC Data Portal. + +### Introduction + +The [DNA Methylation Liftover Pipeline](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=methylation_liftover_workflow) uses data from the Illumina Infinium Human Methylation 27 (HM27) and HumanMethylation450 (HM450) arrays to measure the level of methylation at known CpG sites as beta values, calculated from array intensities (Level 2 data) as Beta = M/(M+U). + +Using probe sequence information provided in the manufacturer's manifest, HM27 and HM450 probes were remapped to the GRCh38 reference genome [2]. Type II probes with a mapping quality of <10, or Type I probes for which the methylated and unmethylated probes map to different locations in the genome, and/or had a mapping quality of <10, had an entry of '\*' for the 'chr' field, and '-1' for coordinates. These coordinates were then used to identify the associated transcripts from GENCODE v22, the associated CpG island (CGI), and the CpG sites' distance from each of these features. Multiple transcripts overlapping the target CpG were separated with semicolons. Beta values were inherited from existing TCGA Level 3 DNA methylation data (hg19-based) based on Probe IDs. + +### Methylation Liftover Pipeline Table Format + +| Field | Definition | +|---|---| +| Composite Element | A unique ID for the array probe associated with a CpG site | +| Beta Value | Represents the ratio between the methylated array intensity and total array intensity, falls between 0 (lower levels of methylation) and 1 (higher levels of methylation) | +| Chromosome | The chromosome in which the probe binding site is located | +| Start | The start of the CpG site on the chromosome | +| End | The end of the CpG site on the chromosome | +| Gene Symbol | The symbol for genes associated with the CpG site. Genes that fall within 1,500 bp upstream of the transcription start site (TSS) to the end of the gene body are used. | +| Gene Type | A general classification for each gene (e.g. protein coding, miRNA, pseudogene) | +| Transcript ID | Ensembl transcript IDs for each transcript associated with the genes detailed above | +| Position to TSS | Distance in base pairs from the CpG site to each associated transcript's start site | +| CGI Coordinate | The start and end coordinates of the CpG island associated with the CpG site | +| Feature Type | The position of the CpG site in reference to the island: Island, N_Shore or S_Shore (0-2 kb upstream or downstream from CGI), or N_Shelf or S_Shelf (2-4 kbp upstream or downstream from CGI) | + +--- + +| I/O | Entity | Format | +|---|---|---| +| Input | [Submitted Methylation Beta Values](/Data_Dictionary/viewer/#?view=table-definition-view&id=submitted_methylation_beta_value) | TXT | +| Output | [Methylation Beta Values](/Data_Dictionary/viewer/#?view=table-definition-view&id=methylation_beta_value) or [Masked Methylation Array](/Data_Dictionary/viewer/#?view=table-definition-view&id=masked_methylation_array) | TXT/IDAT | + + +## File Access and Availability + +| Type | Description | Format | +|---|---|---| +| Methylation Beta Value | A table that associates array probes with CpG sites and associated metadata. | TXT | +| Masked Methylation Array | A data file that contains channel data from a raw methylation array after masking of potential genotyping information. | IDAT | + + +[1]. Zhou, Wanding, Triche Timothy J., Laird Peter W. and Shen Hui. "SeSAMe: Reducing artifactual detection of DNA methylation by Infinium BeadChips in genomic deletions." Nucleic Acids Research. (2018): doi: 10.1093/nar/gky691 + +[2]. Zhou, Wanding, Laird Peter L., and Hui Shen. "Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes." Nucleic Acids Research. (2016): doi: 10.1093/nar/gkw967 diff --git a/docs/Data/Bioinformatics_Pipelines/RPPA_intro.md b/docs/Data/Bioinformatics_Pipelines/RPPA_intro.md new file mode 100644 index 000000000..a070d334d --- /dev/null +++ b/docs/Data/Bioinformatics_Pipelines/RPPA_intro.md @@ -0,0 +1,46 @@ +# Protein Expression - RPPA + +## Introduction + +**R**everse **P**hase **P**rotein **A**rray (RPPA) is a high-throughput antibody-based technique with a procedure similar to that of Western blots. In the procedure carried by [MD Anderson Cancer Center](https://www.mdanderson.org/), hundreds to thousands of different cell lysates are immobilized on a nitrocellulose-coated slide as many individual spots, followed by incubations with one protein-specific antibody, and detection. A group (often several hundreds) of antibodies form a *set*, which are used for each assay. Occasionally, antibodies may be added to or removed from the set depending on feasibility/functionality, which forms a new set. + +To quantify protein expression, a "standard curve" is constructed from spots on each slide (one slide probed for one antibody). These spots include serial dilutions of each sample plus QC spots of standard lysates at different concentrations. + +The technique is capable of the following types of analyses: + +* Patient tumor classification +* DNA, RNA, and Protein correlation +* Prognosis +* Response prediction for targeted therapies +* Pharmacodynamics and biologically relevant dose +* Determination of appropriate handling procedures for clinical samples (based on antigen stability analysis) + +## RPPA Data in the GDC + +The antigens used for RPPA are available at ref [5], with the following information available: + +* ```AGID```: The antigen unique ID +* ```peptide_target```: The unique ID for the target site that the antigen binds to +* ```gene_symbol```: The unique gene name abbreviation that codes the peptide +* ```antibody_origin```: The species that the antibody originated from +* ```source```: The antibody vendor company +* ```catalog_number```: Antibody vendor's catalog number +* ```validation_status```: Indicating how trustworthy those antibodies are, based on QC tests of antibody quality by the MD Anderson. + +The GDC protein expression quantification data set is available in TSV format and contains ```AGID```, ```catalog_number```, and ```peptide_target``` from the reference file, plus the following fields: + +* ```lab_id```: The unique antibody ID +* ```set_id```: The ID for a set, ie list of antibodies (eg refs [3] & [4]). +* ```protein_expression```: Relative levels of protein expression - interpolation of each dilution curve to the "standard curve" (supercurve) of the slide (antibody). + +## References + +[1]. https://bioinformatics.mdanderson.org/public-software/tcpa/ + +[2]. https://www.mdanderson.org/research/research-resources/core-facilities/functional-proteomics-rppa-core/rppa-process.html + +[3]. https://www.mdanderson.org/content/dam/mdanderson/documents/core-facilities/Functional%20Proteomics%20RPPA%20Core%20Facility/RPPA_Expanded_Ab_List_Updated.xlsx + +[4]. https://www.mdanderson.org/content/dam/mdanderson/documents/core-facilities/Functional%20Proteomics%20RPPA%20Core%20Facility/RPPA_Standard_Ab_List_Updated.xlsx + +[5]. https://gdc.cancer.gov/about-data/gdc-data-processing/gdc-reference-files diff --git a/docs/Data/Bioinformatics_Pipelines/fpkm.gif b/docs/Data/Bioinformatics_Pipelines/fpkm.gif new file mode 100644 index 000000000..664d69051 Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/fpkm.gif differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/RNA-Seq-DR32_Image.png b/docs/Data/Bioinformatics_Pipelines/images/RNA-Seq-DR32_Image.png new file mode 100644 index 000000000..34c3b83a7 Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/RNA-Seq-DR32_Image.png differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/RNA_Expression_WF.graphml b/docs/Data/Bioinformatics_Pipelines/images/RNA_Expression_WF.graphml new file mode 100644 index 000000000..7b2a0347d --- /dev/null +++ b/docs/Data/Bioinformatics_Pipelines/images/RNA_Expression_WF.graphml @@ -0,0 +1,406 @@ + + + + + + + + + + + + + + + + + + + + + + + BAM + + + + + + + + + + + + FASTQ + + + + + + + + + + + + Convert to +FASTQ +(Biobambam) + + + + + + + + + + + + Alignment & +Splice Junction +Detection +(STAR 2 TwoPass) + + + + + + + + + + + + Splice +Junction* + + + + + + + + + + + + Aligned +Transcriptomic +BAM* + + + + + + + + + + + + Aligned +Genomic +BAM + + + + + + + + + + + + Aligned +Chimeric +BAM* + + + + + + + + + + + + Gene +Expression +Counts + + + + + + + + + + + + Stranded and +unstranded counts, +FPKM, FPKM-UQ +TPM*** + + + + + + + + + + + + Augment +Gene +Counts + + + + + + + + + + + + Transcript +Fusion +(Arriba) + + + + + + + + + + + + Transcript +Fusion +(STAR-Fusion) + + + + + + + + + + + + Transcript +Fusion** + + + + + + + + + + + + Transcript +Fusion** + + + + + + + + + + + + * Data Release 14+ +** Data Release 25+ +*** Data Release 32+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/docs/Data/Bioinformatics_Pipelines/images/RNA_Expression_WF_Flowchart.png b/docs/Data/Bioinformatics_Pipelines/images/RNA_Expression_WF_Flowchart.png new file mode 100644 index 000000000..ff7277d05 Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/RNA_Expression_WF_Flowchart.png differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/dna-alignment-pipeline_1.png b/docs/Data/Bioinformatics_Pipelines/images/dna-alignment-pipeline_1.png new file mode 100644 index 000000000..990903b5f Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/dna-alignment-pipeline_1.png differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/fpkm.gif b/docs/Data/Bioinformatics_Pipelines/images/fpkm.gif new file mode 100644 index 000000000..664d69051 Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/fpkm.gif differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/fpkm_fpkm-uq_tpm_formulas.png b/docs/Data/Bioinformatics_Pipelines/images/fpkm_fpkm-uq_tpm_formulas.png new file mode 100644 index 000000000..73ba045eb Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/fpkm_fpkm-uq_tpm_formulas.png differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/fpkm_fpkm-uq_tpm_formulas.svg b/docs/Data/Bioinformatics_Pipelines/images/fpkm_fpkm-uq_tpm_formulas.svg new file mode 100644 index 000000000..1c05e95a3 --- /dev/null +++ b/docs/Data/Bioinformatics_Pipelines/images/fpkm_fpkm-uq_tpm_formulas.svg @@ -0,0 +1,417 @@ + + + + + + + + + + image/svg+xml + + + + + + + N = number of protein coding genesCg = count of reads aligned to gene gLg = union length of exons of gene gG = number of protein coding genes on autosomesCqtl(0.75) = count of reads aligned to gene at quantile 0.75 + + FPKM = + FPKM-UQ = + TPM = + + (Cg * 1e3 / Lg) * 1e6 + + (Cg * 1e3 / Lg) + ∑ + g=1 + N + + + + + Cqtl(0.75) * G * Lg + Cg * 1e9 + + + + Cg * 1e9 + + + ∑ + i=1 + N + Ci + Lg + ) + ( + + + + + diff --git a/docs/Data/Bioinformatics_Pipelines/images/gene-expression-quantification-pipeline-v2.png b/docs/Data/Bioinformatics_Pipelines/images/gene-expression-quantification-pipeline-v2.png new file mode 100644 index 000000000..f628bf30b Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/gene-expression-quantification-pipeline-v2.png differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/gene-expression-quantification-pipeline-v3.png b/docs/Data/Bioinformatics_Pipelines/images/gene-expression-quantification-pipeline-v3.png new file mode 100644 index 000000000..749d545ba Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/gene-expression-quantification-pipeline-v3.png differ diff --git a/docs/Data/Bioinformatics_Pipelines/images/normalizations_calc.png b/docs/Data/Bioinformatics_Pipelines/images/normalizations_calc.png new file mode 100644 index 000000000..7c8bce502 Binary files /dev/null and b/docs/Data/Bioinformatics_Pipelines/images/normalizations_calc.png differ diff --git a/docs/Data/Bioinformatics_Pipelines/overlap.gene.stranded.tsv b/docs/Data/Bioinformatics_Pipelines/overlap.gene.stranded.tsv new file mode 100644 index 000000000..74ae86ef3 --- /dev/null +++ b/docs/Data/Bioinformatics_Pipelines/overlap.gene.stranded.tsv @@ -0,0 +1,963 @@ +seqname start end strand gene_id gene_name gene_type +chr1 30366 30503 + ENSG00000274890.1 MIR1302-9 miRNA +chr1 89551 91105 - ENSG00000239945.1 RP11-34P13.8 lincRNA +chr1 258568 259024 - ENSG00000241670.3 AP006222.1 processed_pseudogene +chr1 965110 965166 + ENSG00000277294.1 AL645608.1 miRNA +chr1 1055033 1056116 + ENSG00000242590.1 RP11-54O7.14 sense_intronic +chr1 1312502 1312566 - ENSG00000274153.1 MIR6727 miRNA +chr1 1405460 1405752 - ENSG00000264293.2 RN7SL657P misc_RNA +chr1 9983141 9984568 + ENSG00000241326.1 RP11-807G9.2 sense_intronic +chr1 10306465 10306757 + ENSG00000264501.2 RN7SL731P misc_RNA +chr1 11843812 11843984 + ENSG00000276470.1 NPPA-AS1_1 misc_RNA +chr1 11845549 11845697 + ENSG00000278852.1 NPPA-AS1_2 misc_RNA +chr1 11847442 11847549 + ENSG00000275915.1 NPPA-AS1_3 misc_RNA +chr1 12824942 12828663 - ENSG00000279195.1 PRAMEF11 protein_coding +chr1 15659869 15661722 + ENSG00000215695.1 RSC1A1 protein_coding +chr1 15684472 15684558 + ENSG00000264048.1 AL121992.1 miRNA +chr1 16873708 16873851 + ENSG00000277234.1 U1 snRNA +chr1 17413631 17413694 - ENSG00000266727.1 AC004824.1 miRNA +chr1 20633679 20633788 + ENSG00000273695.1 MIR6084 miRNA +chr1 23370254 23370346 + ENSG00000201405.1 Y_RNA misc_RNA +chr1 25831913 25832134 - ENSG00000272478.1 RP1-317E23.7 antisense +chr1 27325470 27325553 + ENSG00000281023.1 FO393419.1 miRNA +chr1 28507366 28507571 + ENSG00000274266.1 SNORA73A snoRNA +chr1 28579764 28579893 - ENSG00000278274.1 SNORA61 snoRNA +chr1 28580381 28580512 - ENSG00000273544.1 SNORA44 snoRNA +chr1 28580920 28581054 - ENSG00000280498.1 SNORA16A snoRNA +chr1 28580920 28581056 - ENSG00000274582.1 SNORA16A snoRNA +chr1 28648600 28648730 + ENSG00000270103.3 RNU11 lincRNA +chr1 32170733 32176568 + ENSG00000250135.1 RP4-622L5.2 sense_intronic +chr1 35925832 35929610 + ENSG00000280133.1 RP4-789D17.3 TEC +chr1 37480230 37480289 + ENSG00000278228.1 MIR6732 miRNA +chr1 43364648 43364715 - ENSG00000277622.1 MIR6734 miRNA +chr1 44103945 44104079 + ENSG00000281534.1 AL139220.1 miRNA +chr1 44775864 44775943 + ENSG00000264294.1 SNORD55 snoRNA +chr1 44778390 44778456 + ENSG00000207421.1 SNORD38B snoRNA +chr1 44778390 44778458 + ENSG00000281859.1 SNORD38B snoRNA +chr1 44819883 44819997 - ENSG00000202444.1 RNU5E-6P snRNA +chr1 47761132 47765547 - ENSG00000223814.1 RP11-543D5.2 lincRNA +chr1 52150329 52150412 + ENSG00000281172.1 AL139156.1 miRNA +chr1 62211557 62211666 + ENSG00000200174.1 Y_RNA misc_RNA +chr1 67320369 67395580 + ENSG00000281152.1 IL12RB2 protein_coding +chr1 75787072 75787150 + ENSG00000206620.1 SNORD45C snoRNA +chr1 75787889 75787972 + ENSG00000207241.1 SNORD45A snoRNA +chr1 75789477 75789548 + ENSG00000201487.1 SNORD45B snoRNA +chr1 81990753 81990806 + ENSG00000274207.1 AC113949.1 miRNA +chr1 92229256 92229339 - ENSG00000265543.1 AL451010.1 miRNA +chr1 92837289 92837383 + ENSG00000206680.1 SNORD21 snoRNA +chr1 98045242 98045351 - ENSG00000276280.1 MIR2682 miRNA +chr1 98046070 98046171 - ENSG00000277990.1 MIR137 miRNA +chr1 103569553 103570674 + ENSG00000236085.1 ACTG1P4 processed_pseudogene +chr1 109100193 109100612 + ENSG00000278249.1 SCARNA2 scaRNA +chr1 109596225 109597781 + ENSG00000225113.1 RP5-1160K1.3 sense_overlapping +chr1 109598893 109598967 + ENSG00000207709.2 MIR197 miRNA +chr1 145281116 145281279 + ENSG00000207501.1 RNVU1-14 snRNA +chr1 151765709 151766389 + ENSG00000232937.1 RP11-98D18.2 sense_intronic +chr1 155925958 155926085 - ENSG00000280466.1 SCARNA15 scaRNA +chr1 158578919 158579899 - ENSG00000186400.3 OR10X1 protein_coding +chr1 158578919 158579899 - ENSG00000279111.1 OR10X1 polymorphic_pseudogene +chr1 160205377 160205464 + ENSG00000265381.1 AL121987.1 miRNA +chr1 165662585 165662687 - ENSG00000206990.1 Y_RNA misc_RNA +chr1 170370213 170370295 - ENSG00000263384.1 AL354732.1 miRNA +chr1 172138798 172138907 - ENSG00000207949.1 MIR214 miRNA +chr1 182944402 182944454 - ENSG00000281615.1 AL450304.2 miRNA +chr1 182959485 182959575 - ENSG00000264768.1 AL450304.1 miRNA +chr1 186311825 186311928 - ENSG00000202025.1 RNU6-1240P snRNA +chr1 201464383 201465146 - ENSG00000224818.1 RP11-134G8.10 3prime_overlapping_ncrna +chr1 201520056 201520549 + ENSG00000242150.2 RP11-134G8.6 transcribed_processed_pseudogene +chr1 202873294 202874326 + ENSG00000243113.1 RP11-480I12.9 transcribed_processed_pseudogene +chr1 207801845 207801956 - ENSG00000275668.1 AL035209.1 miRNA +chr1 207802440 207802523 - ENSG00000276752.1 MIR29B2 miRNA +chr1 218442626 218443996 + ENSG00000281453.1 TGFB2-OT1 3prime_overlapping_ncrna +chr1 220571834 220571899 - ENSG00000281158.1 AC096640.1 miRNA +chr1 220825776 220825893 + ENSG00000276642.1 U6atac snRNA +chr1 225922080 225922142 - ENSG00000274674.1 MIR6741 miRNA +chr1 227430526 227430976 + ENSG00000242757.1 CTD-2090I13.3 processed_pseudogene +chr1 228097263 228097341 + ENSG00000264944.1 MIR3620 miRNA +chr1 228397048 228397109 - ENSG00000278067.1 MIR6742 miRNA +chr1 228628176 228628234 - ENSG00000281588.1 AL713899.1 miRNA +chr1 229304857 229305504 + ENSG00000213029.3 SPHAR protein_coding +chr1 229440284 229441020 - ENSG00000226920.1 RP5-1068B5.5 3prime_overlapping_ncrna +chr1 231019828 231019924 - ENSG00000221290.1 MIR1182 miRNA +chr1 232223059 232223141 + ENSG00000281475.1 BX323014.1 miRNA +chr1 236483165 236484468 + ENSG00000244457.2 ENO1P1 transcribed_processed_pseudogene +chr1 237926831 237927605 + ENSG00000243781.1 RP11-193H5.2 transcribed_processed_pseudogene +chr1 245749563 246355081 - ENSG00000280657.1 SMYD3 protein_coding +chr1 247201967 247202060 - ENSG00000263568.1 MIR3916 miRNA +chr1 247948858 247949796 + ENSG00000196936.3 OR2L8 protein_coding +chr1 247948858 247949796 + ENSG00000279263.1 OR2L8 polymorphic_pseudogene +chr1 248626178 248627128 - ENSG00000183130.3 OR2T11 protein_coding +chr1 248721993 248722201 - ENSG00000242529.1 AHCYP8 processed_pseudogene +chr2 10691538 10691831 + ENSG00000277446.1 Metazoa_SRP misc_RNA +chr2 20401650 20401706 - ENSG00000281337.1 AC007041.1 miRNA +chr2 31823018 31823106 - ENSG00000265267.1 AL121652.3 miRNA +chr2 60925909 60931610 + ENSG00000267520.2 RP11-373L24.1 3prime_overlapping_ncrna +chr2 61177554 61177636 + ENSG00000280672.1 AC016747.1 miRNA +chr2 62146413 62147153 + ENSG00000242735.1 AC018462.3 processed_pseudogene +chr2 64817586 64817668 + ENSG00000280945.1 AC007880.2 miRNA +chr2 65667256 65667346 + ENSG00000265899.1 AC007389.4 miRNA +chr2 85567662 85567737 - ENSG00000280656.1 AC016753.1 miRNA +chr2 88860886 88860922 - ENSG00000211594.2 IGKJ4 IG_J_gene +chr2 88861221 88861258 - ENSG00000211595.2 IGKJ3 IG_J_gene +chr2 88861525 88861563 - ENSG00000211596.3 IGKJ2 IG_J_gene +chr2 88861886 88861923 - ENSG00000211597.2 IGKJ1 IG_J_gene +chr2 96809473 96809614 + ENSG00000280510.1 AC092636.2 miRNA +chr2 110126732 110126824 - ENSG00000212091.1 AC013268.1 miRNA +chr2 113596000 113596067 + ENSG00000276624.1 AL078621.1 miRNA +chr2 127846736 127847084 - ENSG00000244563.1 AC006011.4 processed_pseudogene +chr2 130929762 130929883 - ENSG00000281159.1 SCARNA15 scaRNA +chr2 131491160 131491236 - ENSG00000265575.1 MIR4784 miRNA +chr2 132152243 132152349 - ENSG00000239108.1 RNU6-1132P snRNA +chr2 144518447 144518574 + ENSG00000275372.1 ZEB2_AS1_1 misc_RNA +chr2 144520456 144520555 + ENSG00000273537.1 ZEB2_AS1_3 misc_RNA +chr2 144521039 144521116 + ENSG00000277444.1 ZEB2_AS1_4 misc_RNA +chr2 159462417 159463256 - ENSG00000225369.1 AC009506.2 processed_pseudogene +chr2 160407810 160407882 - ENSG00000263948.1 MIR4785 miRNA +chr2 175176493 175176586 - ENSG00000200121.2 Y_RNA misc_RNA +chr2 176188843 176188901 + ENSG00000277284.1 MIR7704 miRNA +chr2 177212726 177212799 + ENSG00000263721.1 MIR4444-1 miRNA +chr2 178831371 178831449 - ENSG00000238542.1 RNU7-104P snRNA +chr2 179934402 179934527 - ENSG00000202216.2 SNORA17 snoRNA +chr2 182314454 182314536 + ENSG00000281257.1 AC012500.1 miRNA +chr2 182788098 182788435 + ENSG00000232430.1 RPL31P15 processed_pseudogene +chr2 188974419 188974555 + ENSG00000281204.1 AC066694.1 miRNA +chr2 189311671 189311761 - ENSG00000266817.1 AC118063.1 miRNA +chr2 190880854 190880942 + ENSG00000280517.1 AC005540.1 miRNA +chr2 192775943 192776073 + ENSG00000278406.1 PCGEM1 misc_RNA +chr2 201166965 201167546 + ENSG00000234431.2 AC007283.5 3prime_overlapping_ncrna +chr2 201621646 201623430 - ENSG00000241790.2 ENO1P4 processed_pseudogene +chr2 202115167 202115260 - ENSG00000274633.1 AC079354.1 miRNA +chr2 202333642 202333724 + ENSG00000281619.1 AC064836.1 miRNA +chr2 202773720 202774360 - ENSG00000240761.1 AC098831.4 processed_pseudogene +chr2 203190780 203191277 + ENSG00000204196.5 AC011737.2 processed_pseudogene +chr2 203764707 203764798 - ENSG00000211573.2 AC125238.1 miRNA +chr2 206116110 206116500 - ENSG00000237580.1 GCSHP3 processed_pseudogene +chr2 206160843 206161024 + ENSG00000277502.1 uc_338 misc_RNA +chr2 206162228 206162359 + ENSG00000207406.1 SNORA41 snoRNA +chr2 207754807 207754881 + ENSG00000264900.1 MIR4775 miRNA +chr2 218280125 218280188 - ENSG00000274203.1 MIR6513 miRNA +chr2 230176665 230221721 - ENSG00000280755.1 SP110 protein_coding +chr2 231456444 231456523 - ENSG00000207280.1 SNORD20 snoRNA +chr2 231711525 231711647 + ENSG00000277986.1 U4 snRNA +chr2 232550474 232550573 - ENSG00000266620.1 MIR5001 miRNA +chr2 233865496 233867359 - ENSG00000279809.1 AC005538.3 TEC +chr2 239091759 239091836 - ENSG00000281838.1 AC017028.12 miRNA +chr3 8931506 8931631 + ENSG00000199815.2 SNORA17 snoRNA +chr3 12071038 12071121 + ENSG00000265870.1 AC026166.1 miRNA +chr3 12840294 12840396 - ENSG00000281117.1 AC034198.1 miRNA +chr3 12840312 12840450 - ENSG00000207496.1 SNORA7A snoRNA +chr3 12850659 12850860 + ENSG00000250939.2 AC034198.7 transcribed_unprocessed_pseudogene +chr3 15738657 15738718 + ENSG00000281814.1 AC090950.1 miRNA +chr3 16933196 16933260 + ENSG00000264818.1 MIR3714 miRNA +chr3 24096512 24097360 - ENSG00000242109.1 NPM1P23 transcribed_processed_pseudogene +chr3 30304321 30304536 - ENSG00000281710.1 U3 snoRNA +chr3 32259728 32259819 + ENSG00000207857.2 AC097639.1 miRNA +chr3 38125292 38125394 - ENSG00000201965.1 Y_RNA misc_RNA +chr3 39408389 39408539 + ENSG00000206760.1 SNORA6 snoRNA +chr3 39411054 39411206 + ENSG00000202363.1 SNORA62 snoRNA +chr3 44629284 44629372 + ENSG00000280942.1 AC099669.1 miRNA +chr3 44861888 44861981 + ENSG00000207783.1 MIR564 miRNA +chr3 48094801 48094876 - ENSG00000281068.1 AC124916.1 miRNA +chr3 48094888 48094957 - ENSG00000281238.1 AC124916.2 miRNA +chr3 48465811 48467645 + ENSG00000213689.8 TREX1 protein_coding +chr3 48633636 48633698 - ENSG00000274831.1 MIR6824 miRNA +chr3 49099854 49099914 - ENSG00000274888.1 MIR6890 miRNA +chr3 49806137 49806245 - ENSG00000263506.1 MIR5193 miRNA +chr3 49863381 49863464 - ENSG00000281278.1 AC139451.2 miRNA +chr3 50273236 50273297 + ENSG00000274596.1 MIR6872 miRNA +chr3 52690744 52690827 + ENSG00000238862.1 SNORD19B snoRNA +chr3 64099273 64101122 + ENSG00000241572.1 PRICKLE2-AS1 antisense +chr3 98264285 98265262 + ENSG00000230301.4 OR5H6 protein_coding +chr3 98264285 98265262 + ENSG00000279922.1 OR5H6 polymorphic_pseudogene +chr3 116716460 116716624 + ENSG00000278072.1 AC108713.1 misc_RNA +chr3 123161794 123161879 + ENSG00000275891.1 MIR7110 miRNA +chr3 124723788 124726325 + ENSG00000260391.2 RP11-71H17.7 sense_overlapping +chr3 124792319 124792562 - ENSG00000276626.1 7SK misc_RNA +chr3 126571789 126572636 - ENSG00000206483.5 TXNRD3NB protein_coding +chr3 128673691 128673771 - ENSG00000280957.1 AC079945.1 miRNA +chr3 134437827 134437906 + ENSG00000263554.1 MIR4788 miRNA +chr3 139233414 139233520 + ENSG00000276304.1 PISRT1 misc_RNA +chr3 139494618 139494701 + ENSG00000263538.1 AC097103.1 miRNA +chr3 149779009 149779108 - ENSG00000251854.1 RNU6-507P snRNA +chr3 151079506 151079584 + ENSG00000276055.1 CLRN1-AS1 misc_RNA +chr3 169764610 169765047 - ENSG00000277925.1 Telomerase-vert misc_RNA +chr3 169945987 169946754 - ENSG00000244193.1 RP11-379K17.5 transcribed_processed_pseudogene +chr3 181610498 181610729 + ENSG00000276074.1 SOX2OT_exon1 misc_RNA +chr3 181699608 181699883 + ENSG00000276690.1 SOX2OT_exon3 misc_RNA +chr3 181699705 181699783 + ENSG00000281596.1 AC117415.1 miRNA +chr3 183453814 183453944 + ENSG00000199363.1 SNORA63 snoRNA +chr3 186784796 186784864 + ENSG00000238942.1 SNORD2 snoRNA +chr3 186786323 186786445 + ENSG00000200418.1 SNORA63 snoRNA +chr3 186786672 186786777 + ENSG00000281017.1 MIR1248 miRNA +chr3 186786675 186786852 + ENSG00000221420.2 SNORA81 snoRNA +chr3 186787300 186787431 + ENSG00000200320.1 SNORA63 snoRNA +chr3 186787612 186787749 + ENSG00000263776.1 SNORA4 snoRNA +chr3 190659216 190659750 + ENSG00000273370.1 RP11-268E23.2 lincRNA +chr3 195658096 195685904 + ENSG00000215837.7 SDHAP2 transcribed_unprocessed_pseudogene +chr3 195688008 195688120 + ENSG00000276635.1 AC233280.3 miRNA +chr3 197674496 197674576 - ENSG00000216042.1 MIR922 miRNA +chr4 1986384 1986477 - ENSG00000216105.1 MIR943 miRNA +chr4 2250077 2250156 - ENSG00000265080.1 MIR4800 miRNA +chr4 56097422 56097481 + ENSG00000280464.1 AC092627.1 miRNA +chr4 56794354 56794438 - ENSG00000281241.1 AC022483.1 miRNA +chr4 88275205 88275308 - ENSG00000200469.1 RNU6-112P snRNA +chr4 88521573 88521789 - ENSG00000255072.1 PIGY protein_coding +chr4 88710147 88710265 + ENSG00000278151.1 FAM13A-AS1_1 misc_RNA +chr4 98929914 98929993 - ENSG00000238449.2 AC019131.1 miRNA +chr4 108789200 108789262 - ENSG00000265522.1 AC097473.1 miRNA +chr4 118279190 118279320 + ENSG00000275994.1 SNORA24 snoRNA +chr4 122827014 122827090 + ENSG00000253069.1 AC021205.1 miRNA +chr4 135371590 135371681 - ENSG00000207849.2 AC108867.1 miRNA +chr4 146639261 146639343 + ENSG00000264323.1 AC093887.1 miRNA +chr4 151103827 151103891 + ENSG00000208797.1 SNORD73A snoRNA +chr4 152536428 152536516 + ENSG00000277685.1 MIR4453 miRNA +chr4 190065233 190065914 + ENSG00000277162.1 DBET processed_pseudogene +chr4 190175141 190175224 + ENSG00000274222.1 AC215524.1 miRNA +chr5 8460925 8460999 + ENSG00000273868.1 MIR4458 miRNA +chr5 10195187 10197622 - ENSG00000271998.1 CTD-2199O4.7 lincRNA +chr5 18958153 18958237 - ENSG00000281138.1 AC114981.1 miRNA +chr5 31249879 31250200 + ENSG00000250482.2 RP11-152K4.1 processed_pseudogene +chr5 32379407 32379467 - ENSG00000222961.1 AC008949.1 miRNA +chr5 52903908 52904478 + ENSG00000241809.1 CTD-2207L17.1 processed_pseudogene +chr5 57481820 57481903 - ENSG00000264748.1 AC025470.1 miRNA +chr5 60487713 60487929 + ENSG00000273701.1 PART1_1 misc_RNA +chr5 60488078 60488327 + ENSG00000275634.1 PART1_2 misc_RNA +chr5 60546219 60546349 + ENSG00000276233.1 PART1_3 misc_RNA +chr5 69160808 69160939 + ENSG00000280894.1 SNORA76 snoRNA +chr5 74779309 74779413 + ENSG00000199645.1 RNU6-1330P snRNA +chr5 88666853 88666939 - ENSG00000273878.1 MIR9-2 miRNA +chr5 91313057 91314402 - ENSG00000271762.1 RP11-213H15.4 lincRNA +chr5 91844022 91844116 - ENSG00000276426.1 uc_338 misc_RNA +chr5 93620696 93620788 - ENSG00000251725.1 MIR2277 miRNA +chr5 131427266 131635030 - ENSG00000281164.1 RAPGEF6 protein_coding +chr5 136080497 136080597 - ENSG00000278815.1 VTRNA2-1 misc_RNA +chr5 136133696 136133826 + ENSG00000275646.1 SMAD5-AS1_2 misc_RNA +chr5 140563671 140563751 - ENSG00000274910.1 MIR6831 miRNA +chr5 140861224 140863521 + ENSG00000249504.3 PCDHA14 transcribed_unprocessed_pseudogene +chr5 141479535 141479617 + ENSG00000281646.1 AC008781.1 miRNA +chr5 149430646 149430733 + ENSG00000276365.1 MIR145 miRNA +chr5 155845469 155845527 + ENSG00000280546.1 AC140677.1 miRNA +chr5 160485352 160485450 + ENSG00000277727.1 MIR146A miRNA +chr5 168552277 168553727 - ENSG00000253861.1 SLC2A3P1 processed_pseudogene +chr5 178884715 178884879 + ENSG00000206624.1 RNU1-39P snRNA +chr5 181241814 181241892 - ENSG00000272296.1 SNORD96A snoRNA +chr5 181243312 181243379 - ENSG00000264549.1 SNORD95 snoRNA +chr6 6347081 6347381 - ENSG00000241216.1 SNAPC5P1 transcribed_processed_pseudogene +chr6 8653558 8653797 + ENSG00000276019.1 HULC misc_RNA +chr6 16301693 16301824 - ENSG00000281447.1 AL009031.1 miRNA +chr6 20421686 20421749 - ENSG00000281428.1 AL136303.2 miRNA +chr6 24839967 24840065 - ENSG00000263391.1 AL512428.1 miRNA +chr6 27837957 27838094 + ENSG00000281435.1 Z98744.1 miRNA +chr6 28977613 28977709 + ENSG00000280628.1 AL662791.1 miRNA +chr6 29396700 29397623 + ENSG00000168787.6 OR12D2 protein_coding +chr6 29440016 29440954 + ENSG00000279941.1 OR10C1 protein_coding +chr6 29726669 29727139 - ENSG00000239257.1 RPL23AP1 transcribed_processed_pseudogene +chr6 30061080 30061183 + ENSG00000278773.1 ZNRD1-AS1_3 misc_RNA +chr6 30890883 30890972 + ENSG00000264594.1 MIR4640 miRNA +chr6 31532757 31532869 - ENSG00000276877.1 AL662801.1 miRNA +chr6 31541101 31541178 - ENSG00000265236.1 SNORD84 snoRNA +chr6 31837076 31837142 + ENSG00000201754.1 SNORD52 snoRNA +chr6 31956839 31956940 - ENSG00000221267.1 MIR1236 miRNA +chr6 32936916 32937010 - ENSG00000212066.1 AL645941.1 miRNA +chr6 33290245 33290325 + ENSG00000275010.1 MIR6834 miRNA +chr6 34873831 34873927 + ENSG00000252106.2 RNY3P15 misc_RNA +chr6 41787662 41789898 + ENSG00000214736.6 TOMM6 protein_coding +chr6 42155426 42163439 + ENSG00000214732.2 RP1-139D8.6 protein_coding +chr6 44254206 44254285 - ENSG00000265700.1 MIR4647 miRNA +chr6 53090961 53091257 + ENSG00000242865.3 RN7SL244P misc_RNA +chr6 56432379 56432442 - ENSG00000266793.1 AL137008.1 miRNA +chr6 71585089 71585201 + ENSG00000211530.1 AL354933.1 miRNA +chr6 85677294 85677368 - ENSG00000281147.1 SNORD50A snoRNA +chr6 85677589 85677658 - ENSG00000275072.1 SNORD50B snoRNA +chr6 88276125 88276208 - ENSG00000281199.1 AL139042.1 miRNA +chr6 110440082 110440165 - ENSG00000281088.1 AC002464.1 miRNA +chr6 112361848 112361939 - ENSG00000266485.1 AL365214.1 miRNA +chr6 116457732 116457822 - ENSG00000265516.1 Z84488.1 miRNA +chr6 136034553 136034886 - ENSG00000213111.5 COX5BP2 transcribed_processed_pseudogene +chr6 136343193 136343249 - ENSG00000276943.1 AL023284.1 miRNA +chr6 159785594 159785733 - ENSG00000206910.1 SNORA29 snoRNA +chr6 166099853 166099924 + ENSG00000276643.1 SNORD45 snoRNA +chr7 2257515 2257577 - ENSG00000277102.1 MIR6836 miRNA +chr7 5528103 5528186 - ENSG00000263900.1 AC006483.1 miRNA +chr7 7742091 7742535 - ENSG00000269721.1 RPL23AP51 transcribed_processed_pseudogene +chr7 12654179 12654985 + ENSG00000229233.1 CTD-2320J21.2 sense_overlapping +chr7 27096124 27096248 + ENSG00000276528.1 HOTAIRM1_1 misc_RNA +chr7 27098900 27099114 + ENSG00000276771.1 HOTAIRM1_2 misc_RNA +chr7 27099778 27099836 + ENSG00000274864.1 HOTAIRM1_3 misc_RNA +chr7 27099856 27099957 + ENSG00000274396.1 HOTAIRM1_4 misc_RNA +chr7 27099967 27100111 + ENSG00000277694.1 HOTAIRM1_5 misc_RNA +chr7 27169480 27169564 - ENSG00000207584.1 MIR196B miRNA +chr7 27185433 27185530 + ENSG00000273961.1 HOXA11-AS1_1 misc_RNA +chr7 27185832 27186018 + ENSG00000278334.1 HOXA11-AS1_2 misc_RNA +chr7 27186166 27186263 + ENSG00000276496.1 HOXA11-AS1_3 misc_RNA +chr7 27188816 27188994 + ENSG00000278020.1 HOXA11-AS1_6 misc_RNA +chr7 27200465 27200521 + ENSG00000276609.1 HOTTIP_1 misc_RNA +chr7 27201844 27202219 + ENSG00000278708.1 HOTTIP_2 misc_RNA +chr7 27202302 27202638 + ENSG00000277469.1 HOTTIP_3 misc_RNA +chr7 27206139 27206303 + ENSG00000277553.1 HOTTIP_4 misc_RNA +chr7 30157531 30159534 + ENSG00000251660.1 AC007036.5 sense_overlapping +chr7 39609717 39610280 + ENSG00000106540.4 AC004837.3 processed_pseudogene +chr7 40128121 40128232 - ENSG00000199273.1 Y_RNA misc_RNA +chr7 44051766 44051829 + ENSG00000274083.1 MIR6837 miRNA +chr7 44064908 44066079 + ENSG00000239775.1 AC017116.11 sense_overlapping +chr7 44110849 44110912 + ENSG00000264652.1 MIR4649 miRNA +chr7 44881748 44881800 - ENSG00000264326.1 MIR4657 miRNA +chr7 44985378 44985510 - ENSG00000277184.1 SNORA9 snoRNA +chr7 45105968 45106099 - ENSG00000200656.1 SNORA5B snoRNA +chr7 65038372 65038565 + ENSG00000239985.2 RP11-460N20.3 unprocessed_pseudogene +chr7 66980335 66980409 + ENSG00000280772.1 AC079920.1 miRNA +chr7 75237293 75237405 - ENSG00000275121.1 CH17-232I21.1 processed_pseudogene +chr7 75474707 75486108 - ENSG00000242073.2 AC006014.7 transcribed_unprocessed_pseudogene +chr7 75915197 75915269 + ENSG00000265020.1 MIR4651 miRNA +chr7 84939349 84940245 - ENSG00000232019.1 AC074183.4 lincRNA +chr7 90403434 90513391 + ENSG00000273299.1 CTB-13L3.1 processed_transcript +chr7 95156606 95156671 - ENSG00000277296.1 AC002429.1 miRNA +chr7 100352360 100353692 + ENSG00000235333.3 PVRIG2P transcribed_unprocessed_pseudogene +chr7 100356651 100356721 + ENSG00000278005.1 MIR6840 miRNA +chr7 100868036 100868107 + ENSG00000273985.1 MIR6875 miRNA +chr7 101058299 101058567 + ENSG00000222636.1 RN7SKP54 misc_RNA +chr7 102465742 102465826 + ENSG00000266715.1 MIR5090 miRNA +chr7 102471469 102471531 + ENSG00000264471.1 MIR4467 miRNA +chr7 105014152 105014199 - ENSG00000280574.1 AC007384.1 miRNA +chr7 112288623 112288952 + ENSG00000202406.1 RN7SKP187 misc_RNA +chr7 114629855 114629956 + ENSG00000266229.1 AC020606.1 miRNA +chr7 116954480 116954679 + ENSG00000273596.1 ST7-OT4_1 misc_RNA +chr7 116956431 116956723 + ENSG00000276100.1 ST7-OT4_3 misc_RNA +chr7 116959593 116959805 + ENSG00000274606.1 ST7-OT4_4 misc_RNA +chr7 117020211 117020319 + ENSG00000275870.1 MIR6132 miRNA +chr7 117184126 117184199 + ENSG00000275054.1 ST7-OT3_1 misc_RNA +chr7 117191647 117191761 + ENSG00000278482.1 ST7-OT3_3 misc_RNA +chr7 121050927 121051203 + ENSG00000234927.1 HMGN1P18 processed_pseudogene +chr7 128466563 128469171 + ENSG00000272601.1 RP11-155G14.5 transcribed_unprocessed_pseudogene +chr7 129756266 129756377 + ENSG00000212238.1 RNA5SP244 rRNA +chr7 130877459 130877539 - ENSG00000274250.1 MIR29B1 miRNA +chr7 135927274 135927450 - ENSG00000267697.1 LUZP6 protein_coding +chr7 138123758 138123821 + ENSG00000266193.1 MIR4468 miRNA +chr7 140645966 140646034 + ENSG00000280499.1 AC006452.2 miRNA +chr7 142797119 142797166 + ENSG00000211769.1 TRBJ2-5 TR_J_gene +chr7 142797239 142797291 + ENSG00000211770.1 TRBJ2-6 TR_J_gene +chr7 143959971 143960924 + ENSG00000279723.1 OR2F1 protein_coding +chr7 151238421 151238538 + ENSG00000211517.1 MIR671 miRNA +chr8 8582352 8582427 - ENSG00000281480.1 AC114550.1 miRNA +chr8 9903388 9903472 - ENSG00000275677.1 MIR124-1 miRNA +chr8 20290174 20290289 + ENSG00000274467.1 5S_rRNA rRNA +chr8 27610601 27610751 - ENSG00000273705.1 MIR6843 miRNA +chr8 56073835 56073901 - ENSG00000238650.1 SNORD54 snoRNA +chr8 66922467 66922555 - ENSG00000254341.2 SNORD87 snoRNA +chr8 70480192 70480487 - ENSG00000275128.1 Metazoa_SRP misc_RNA +chr8 73982125 73982467 + ENSG00000244295.2 RPS20P21 processed_pseudogene +chr8 80484589 80484683 - ENSG00000277604.1 Y_RNA misc_RNA +chr8 86657870 86657952 - ENSG00000221137.1 AC013751.1 miRNA +chr8 93916022 93916119 - ENSG00000276513.1 MIR378D2 miRNA +chr8 98192205 98192313 - ENSG00000252558.1 RNU6-914P snRNA +chr8 100702968 100703024 - ENSG00000277719.1 MIR7705 miRNA +chr8 116874728 116874800 - ENSG00000264875.1 MIR3610 miRNA +chr8 117164179 117164255 + ENSG00000281002.1 AC084114.1 miRNA +chr8 127794541 127794734 + ENSG00000276443.1 PVT1_1 misc_RNA +chr8 127795962 127796028 + ENSG00000275264.1 MIR1204 miRNA +chr8 127890626 127890720 + ENSG00000278324.1 PVT1_3 misc_RNA +chr8 133229056 133229697 + ENSG00000270132.1 WISP1-OT1 sense_intronic +chr8 134598071 134598149 + ENSG00000276140.1 ZFAT-AS1_1 misc_RNA +chr8 134598318 134598518 + ENSG00000277732.1 ZFAT-AS1_2 misc_RNA +chr8 134600257 134600336 + ENSG00000278454.1 ZFAT-AS1_3 misc_RNA +chr8 143542110 143542398 + ENSG00000275558.1 7SK misc_RNA +chr8 143579636 143580670 + ENSG00000254741.1 RP11-661A12.7 antisense +chr8 143837756 143837816 - ENSG00000274094.1 MIR6845 miRNA +chr8 144079874 144079942 + ENSG00000276472.1 MIR6847 miRNA +chr8 144262673 144262737 - ENSG00000277158.1 MIR7112 miRNA +chr8 144314590 144315138 - ENSG00000254690.1 GS1-393G12.12 antisense +chr8 144394149 144394230 - ENSG00000216133.1 MIR939 miRNA +chr8 144400086 144400165 - ENSG00000266624.1 MIR1234 miRNA +chr8 144400277 144400345 - ENSG00000274683.1 MIR6849 miRNA +chr9 30144 30281 + ENSG00000278579.1 MIR1302-2 miRNA +chr9 4834156 4860275 + ENSG00000281007.1 AL158147.2 protein_coding +chr9 30774228 30774319 + ENSG00000211510.2 AL590726.1 miRNA +chr9 33042109 33042216 - ENSG00000222169.1 AL162590.1 miRNA +chr9 35449748 35450352 + ENSG00000244213.1 ZFAND6P1 processed_pseudogene +chr9 35657754 35658017 - ENSG00000277027.1 RNase_MRP ribozyme +chr9 35811476 35811550 - ENSG00000263448.1 AL133410.1 miRNA +chr9 35957139 35958098 - ENSG00000122718.5 OR2S2 protein_coding +chr9 37434177 37434586 + ENSG00000236156.2 CHCHD4P3 processed_pseudogene +chr9 38542314 38542569 - ENSG00000259898.1 CYP4F33P processed_pseudogene +chr9 38542389 38543215 - ENSG00000272934.1 RP11-392E22.10 processed_transcript +chr9 38543104 38543446 - ENSG00000250989.1 RP11-392E22.5 processed_pseudogene +chr9 39173794 39174513 - ENSG00000243695.1 RP11-290L7.3 processed_pseudogene +chr9 41280460 41280787 + ENSG00000278647.1 RP11-4L24.2 transcribed_processed_pseudogene +chr9 69428248 69428721 - ENSG00000243888.1 RP11-548B3.3 3prime_overlapping_ncrna +chr9 76785782 76786190 + ENSG00000277320.1 PCA3_2 misc_RNA +chr9 79726069 79726321 + ENSG00000240979.1 RP11-79D8.2 processed_pseudogene +chr9 83969748 83969857 - ENSG00000207603.1 MIR7-1 miRNA +chr9 97700234 97700325 + ENSG00000266608.1 AL445531.1 miRNA +chr9 100732033 100732116 + ENSG00000281312.1 AL390876.1 miRNA +chr9 122628579 122629535 - ENSG00000171484.4 OR1B1 protein_coding +chr9 123111546 123111643 - ENSG00000274325.1 MIR600 miRNA +chr9 127690687 127690795 - ENSG00000264329.1 MIR3911 miRNA +chr9 127785833 127785923 + ENSG00000266070.1 MIR3960 miRNA +chr9 127785836 127785905 + ENSG00000281546.1 AL162586.1 miRNA +chr9 128260749 128260817 - ENSG00000274982.1 AL590708.3 miRNA +chr9 128391461 128392016 + ENSG00000272593.1 RP11-339B21.11 lincRNA +chr9 128392618 128392714 - ENSG00000273685.1 MIR219B miRNA +chr9 129040566 129040674 + ENSG00000280692.1 AL592211.1 miRNA +chr9 133349396 133349470 + ENSG00000206611.1 SNORD24 snoRNA +chr9 133350095 133350168 + ENSG00000200831.1 SNORD36B snoRNA +chr9 133350456 133350528 + ENSG00000199744.1 SNORD36A snoRNA +chr9 136726104 136726239 - ENSG00000280496.1 SNORA43 snoRNA +chr9 136726105 136726234 - ENSG00000276161.1 SNORA17 snoRNA +chr9 136726747 136726879 - ENSG00000274998.1 SNORA17 snoRNA +chr9 136726748 136726879 - ENSG00000281808.1 SNORA17 snoRNA +chr9 137450026 137450086 - ENSG00000276682.1 MIR7114 miRNA +chr10 5861805 5862594 - ENSG00000240180.1 RP11-318E3.4 processed_pseudogene +chr10 32346864 32346946 - ENSG00000222309.1 AL391839.1 miRNA +chr10 35641172 35641252 - ENSG00000264780.1 MIR4683 miRNA +chr10 42470082 42470268 - ENSG00000279239.1 RP11-178A10.3 transcribed_unprocessed_pseudogene +chr10 77912280 77912362 - ENSG00000281632.1 AL391421.1 miRNA +chr10 86751611 86751772 - ENSG00000281735.1 Clostridiales-1 sRNA +chr10 86970237 86970826 - ENSG00000273413.1 RP11-96C23.15 antisense +chr10 87001636 87009905 + ENSG00000261011.1 RP11-96C23.11 transcribed_unprocessed_pseudogene +chr10 89644603 89645223 - ENSG00000249962.1 RP11-80H5.5 processed_pseudogene +chr10 102409042 102409102 - ENSG00000275957.1 AL121928.1 miRNA +chr10 110898090 110898155 + ENSG00000265827.1 MIR4680 miRNA +chr10 114174105 114174179 - ENSG00000238742.1 MIR2110 miRNA +chr10 127013501 127026475 - ENSG00000232935.2 RP11-223P11.2 antisense +chr11 209336 209406 + ENSG00000274298.1 MIR6743 miRNA +chr11 811681 811814 + ENSG00000199785.1 SNORA52 snoRNA +chr11 1996730 1996842 - ENSG00000278648.1 AC051649.1 miRNA +chr11 2129121 2129964 - ENSG00000240801.1 AC132217.4 3prime_overlapping_ncrna +chr11 3856062 3856141 + ENSG00000263421.1 MIR4687 miRNA +chr11 4367351 4368295 - ENSG00000280253.1 OR52B4 protein_coding +chr11 4768979 4769917 - ENSG00000188069.4 OR51F1 protein_coding +chr11 4803433 4804380 - ENSG00000176937.9 OR52R1 protein_coding +chr11 4803433 4804380 - ENSG00000279270.1 OR52R1 polymorphic_pseudogene +chr11 4923374 4924339 - ENSG00000176879.3 OR51G1 protein_coding +chr11 5069572 5070461 + ENSG00000236621.3 OR52E1 pseudogene +chr11 5323359 5324297 - ENSG00000184881.3 OR51B2 protein_coding +chr11 6608667 6610135 - ENSG00000254641.1 RP11-732A19.2 sense_overlapping +chr11 6785038 6785988 + ENSG00000170803.5 OR2AG1 protein_coding +chr11 7927718 7928662 - ENSG00000175393.3 OR10A6 protein_coding +chr11 8684204 8684314 + ENSG00000280884.1 AC091053.1 miRNA +chr11 8684227 8684356 + ENSG00000200983.1 SNORA45A snoRNA +chr11 9578028 9578131 + ENSG00000238387.1 snoU13 snoRNA +chr11 9958744 9959790 - ENSG00000254765.1 RP11-1H15.1 processed_pseudogene +chr11 15969533 15969621 - ENSG00000274140.1 MIR6073 miRNA +chr11 17075779 17075868 - ENSG00000201403.1 SNORD14B snoRNA +chr11 32435738 32435846 + ENSG00000278822.1 WT1-AS_1 misc_RNA +chr11 32436797 32437030 + ENSG00000278045.1 WT1-AS_3 misc_RNA +chr11 32439086 32439206 + ENSG00000276530.1 WT1-AS_6 misc_RNA +chr11 32439716 32440009 + ENSG00000273908.1 WT1-AS_7 misc_RNA +chr11 32440109 32440383 + ENSG00000277119.1 WT1-AS_8 misc_RNA +chr11 33354465 33354545 + ENSG00000223134.1 AL122015.1 miRNA +chr11 35860654 35860744 - ENSG00000266590.1 AC090692.1 miRNA +chr11 48245104 48246015 + ENSG00000279556.1 OR4X2 protein_coding +chr11 48263861 48264778 + ENSG00000176567.1 OR4X1 protein_coding +chr11 48263861 48264778 + ENSG00000279260.1 OR4X1 polymorphic_pseudogene +chr11 55572128 55573060 + ENSG00000181935.3 OR4C16 protein_coding +chr11 55572128 55573060 + ENSG00000279514.1 OR4C16 polymorphic_pseudogene +chr11 55773438 55774382 + ENSG00000198877.1 OR5D13 protein_coding +chr11 55773438 55774382 + ENSG00000279761.1 OR5D13 polymorphic_pseudogene +chr11 55811467 55812402 + ENSG00000186117.3 OR5L1 protein_coding +chr11 56318307 56319245 + ENSG00000181689.1 OR8K3 protein_coding +chr11 56318307 56319245 + ENSG00000280314.1 OR8K3 polymorphic_pseudogene +chr11 56412744 56413668 + ENSG00000181395.6 OR5AL1 pseudogene +chr11 56417258 56418232 - ENSG00000174942.1 OR5R1 protein_coding +chr11 56417258 56418232 - ENSG00000279961.1 OR5R1 polymorphic_pseudogene +chr11 56663686 56664618 + ENSG00000279911.1 OR5AR1 protein_coding +chr11 58030953 58031906 + ENSG00000172381.4 OR6Q1 protein_coding +chr11 58214745 58215722 + ENSG00000172774.7 OR1S1 protein_coding +chr11 61792495 61792561 - ENSG00000207601.1 MIR611 miRNA +chr11 61815161 61815240 - ENSG00000222326.1 MIR1908 miRNA +chr11 62372656 62372719 + ENSG00000265696.1 AP003064.2 miRNA +chr11 62665422 62665570 + ENSG00000206597.1 SNORA57 snoRNA +chr11 62789815 62789885 + ENSG00000274856.1 MIR6748 miRNA +chr11 62841619 62841809 - ENSG00000222328.1 RNU2-2P snRNA +chr11 62852910 62853035 - ENSG00000277194.1 SNORD22 snoRNA +chr11 62854161 62854285 - ENSG00000278527.1 SNORD22 snoRNA +chr11 62854621 62854695 - ENSG00000274544.1 SNORD28 snoRNA +chr11 62855012 62855083 - ENSG00000275996.1 SNORD27 snoRNA +chr11 62855292 62855366 - ENSG00000276788.1 SNORD26 snoRNA +chr11 62855564 62855632 - ENSG00000275043.1 SNORD25 snoRNA +chr11 64313860 64313950 + ENSG00000278148.1 AP001453.1 miRNA +chr11 64891132 64891243 - ENSG00000207648.2 MIR192 miRNA +chr11 64891355 64891439 - ENSG00000277225.1 MIR194-2 miRNA +chr11 65129916 65129978 - ENSG00000277547.1 MIR6751 miRNA +chr11 65175035 65175502 - ENSG00000249251.1 PGAM1P8 processed_pseudogene +chr11 65423273 65423392 + ENSG00000278144.1 NEAT1_1 misc_RNA +chr11 65423638 65423742 + ENSG00000278050.1 NEAT1_2 misc_RNA +chr11 65423960 65424118 + ENSG00000277599.1 NEAT1_3 misc_RNA +chr11 65444458 65444557 + ENSG00000273834.1 MIR612 miRNA +chr11 65502914 65503008 + ENSG00000278217.1 MALAT1 misc_RNA +chr11 65506117 65506173 + ENSG00000274072.1 mascRNA-menRNA sRNA +chr11 67435510 67438067 - ENSG00000213402.2 PTPRCAP protein_coding +chr11 68032864 68032922 + ENSG00000277703.1 MIR7113 miRNA +chr11 68033897 68033981 + ENSG00000266737.1 MIR4691 miRNA +chr11 75742270 75742331 + ENSG00000281528.1 AP001922.1 miRNA +chr11 78016971 78079865 - ENSG00000259112.1 NDUFC2-KCTD14 protein_coding +chr11 82957423 82958216 + ENSG00000242279.1 RP11-659G9.1 processed_pseudogene +chr11 83213005 83213404 + ENSG00000241020.1 RP11-727A23.1 processed_pseudogene +chr11 86278333 86278398 + ENSG00000273630.1 MIR6755 miRNA +chr11 93721542 93721621 + ENSG00000275146.1 snoU2_19 snoRNA +chr11 93730513 93730646 - ENSG00000207112.1 SNORA25 snoRNA +chr11 93730979 93731099 - ENSG00000206799.1 SNORA32 snoRNA +chr11 93732004 93732133 - ENSG00000206834.1 SNORA1 snoRNA +chr11 93732361 93732499 - ENSG00000207304.1 SNORA8 snoRNA +chr11 93732435 93732501 - ENSG00000281293.1 AP001273.1 miRNA +chr11 93733228 93733300 - ENSG00000239195.1 SNORD5 snoRNA +chr11 93733466 93733597 - ENSG00000207145.1 SNORA18 snoRNA +chr11 93733674 93733764 - ENSG00000221170.1 MIR1304 miRNA +chr11 93735111 93735236 - ENSG00000210825.1 SNORA40 snoRNA +chr11 112218326 112218720 + ENSG00000243930.1 RPS12P21 processed_pseudogene +chr11 113789242 113790027 + ENSG00000255870.1 RP11-667M19.5 processed_pseudogene +chr11 114312063 114312207 + ENSG00000280653.1 AP002518.1 miRNA +chr11 117820163 117876667 - ENSG00000255245.3 FXYD6-FXYD2 protein_coding +chr11 118644000 118644079 + ENSG00000275466.1 MIR6716 miRNA +chr11 119018944 119019012 + ENSG00000266398.1 MIR3656 miRNA +chr11 119312950 119313012 - ENSG00000277325.1 MIR6756 miRNA +chr11 119338942 119340883 - ENSG00000223953.4 C1QTNF5 protein_coding +chr11 119821829 119821927 - ENSG00000276827.1 AP001994.1 miRNA +chr11 120986258 120986353 + ENSG00000281726.1 GRIK4_3p_UTR misc_RNA +chr11 123058909 123058995 - ENSG00000207118.1 SNORD14D snoRNA +chr11 123059335 123059422 - ENSG00000202252.1 SNORD14C snoRNA +chr11 124319262 124320197 - ENSG00000197263.3 OR8D2 protein_coding +chr11 124423942 124424871 - ENSG00000198657.5 OR8B4 protein_coding +chr11 124636491 124636552 + ENSG00000280773.1 AP001524.1 miRNA +chr11 133898504 133898581 - ENSG00000264919.1 MIR4697 miRNA +chr12 3726222 3726327 - ENSG00000222338.1 RNU6-174P snRNA +chr12 4809176 4813412 + ENSG00000151079.7 KCNA6 protein_coding +chr12 6510275 6510522 + ENSG00000276232.1 SCARNA10 sense_intronic +chr12 9127871 9127985 + ENSG00000211542.1 AC007436.1 miRNA +chr12 9695384 9696227 + ENSG00000213443.2 RP11-75L1.2 processed_pseudogene +chr12 12915829 12915918 + ENSG00000207817.1 MIR614 miRNA +chr12 22195469 22195629 - ENSG00000212172.1 RNU1-149P snRNA +chr12 39443048 39443116 - ENSG00000252974.1 AC121334.1 miRNA +chr12 48487946 48488408 + ENSG00000240443.1 RPS10P20 transcribed_processed_pseudogene +chr12 52951708 52951795 + ENSG00000265039.1 AC107016.1 miRNA +chr12 53464720 53464901 + ENSG00000273658.1 uc_338 misc_RNA +chr12 53506690 53507638 - ENSG00000139574.8 NPFF protein_coding +chr12 54231397 54231476 - ENSG00000265371.1 MIR3198-2 miRNA +chr12 55870941 55871219 - ENSG00000265119.2 RN7SL676P misc_RNA +chr12 57512688 57512750 + ENSG00000275657.1 MIR6758 miRNA +chr12 57806154 57806260 - ENSG00000206749.1 RNU6-1083P snRNA +chr12 62260359 62260454 + ENSG00000276811.1 MIR6125 miRNA +chr12 62934507 62934607 - ENSG00000275729.1 AC078814.1 miRNA +chr12 66251082 66251157 + ENSG00000275058.1 MIR6502 miRNA +chr12 68841946 68842384 + ENSG00000256664.1 RP11-611O2.3 processed_pseudogene +chr12 91986626 91993403 - ENSG00000279037.1 C12orf79 protein_coding +chr12 91986682 91993403 - ENSG00000280112.1 C12orf79 protein_coding +chr12 93509487 93509768 + ENSG00000243015.2 RN7SL737P misc_RNA +chr12 94571231 94571352 - ENSG00000277302.1 MIR7844 miRNA +chr12 94834398 94834513 + ENSG00000208038.1 MIR492 miRNA +chr12 97492462 97492597 + ENSG00000273942.1 RMST_2 misc_RNA +chr12 97530656 97530858 + ENSG00000275971.1 RMST_6 misc_RNA +chr12 97532691 97532958 + ENSG00000274819.1 RMST_7 misc_RNA +chr12 97564174 97564327 + ENSG00000277081.1 RMST_10 misc_RNA +chr12 100157256 100157338 - ENSG00000221770.1 AC010203.1 miRNA +chr12 100158502 100158765 - ENSG00000266610.2 RN7SL176P misc_RNA +chr12 103930425 103930555 + ENSG00000265072.1 MIR3652 miRNA +chr12 104125268 104125329 + ENSG00000280646.1 AC089983.1 miRNA +chr12 107650789 107650892 + ENSG00000222160.1 Y_RNA misc_RNA +chr12 109567975 109568115 - ENSG00000200274.1 RNU4-32P snRNA +chr12 110360456 110360538 - ENSG00000281030.1 AC006088.1 miRNA +chr12 110496352 110496421 - ENSG00000202335.1 SNORD50 snoRNA +chr12 111598951 111599031 - ENSG00000281280.1 AC137055.1 miRNA +chr12 111899263 111901391 + ENSG00000229186.4 ADAM1A unitary_pseudogene +chr12 119713634 119713724 - ENSG00000221323.1 MIR1178 miRNA +chr12 120723193 120723266 + ENSG00000265455.1 MIR4700 miRNA +chr12 123364764 123364843 - ENSG00000277700.1 MIR8072 miRNA +chr12 130977562 130978768 + ENSG00000256204.1 RP11-243M5.1 lincRNA +chr12 132835374 132835500 - ENSG00000252079.1 RNU6-327P snRNA +chr13 25944606 25944673 + ENSG00000281497.1 AL138815.1 miRNA +chr13 27255064 27255135 + ENSG00000207500.1 SNORD102 snoRNA +chr13 27255401 27255526 + ENSG00000207051.1 SNORA27 snoRNA +chr13 30206616 30206699 - ENSG00000266816.1 AL356750.1 miRNA +chr13 45336314 45336447 - ENSG00000253051.1 SNORA31 snoRNA +chr13 45732089 45732172 - ENSG00000280848.1 AL139320.1 miRNA +chr13 46437394 46437988 - ENSG00000241353.3 PPP1R2P4 processed_pseudogene +chr13 50082295 50082484 + ENSG00000276089.1 DLEU1_1 misc_RNA +chr13 50104833 50105174 + ENSG00000273541.1 DLEU1_2 misc_RNA +chr13 90231182 90231277 + ENSG00000207858.1 MIR622 miRNA +chr13 91350605 91350688 + ENSG00000275042.1 MIR17 miRNA +chr13 91350743 91350834 + ENSG00000274160.1 AL162375.1 miRNA +chr13 91350891 91350972 + ENSG00000277328.1 MIR19A miRNA +chr13 91351065 91351135 + ENSG00000275534.1 MIR20A miRNA +chr13 91351192 91351278 + ENSG00000275802.1 MIR19B1 miRNA +chr13 91351314 91351393 + ENSG00000276018.1 MIR92A1 miRNA +chr13 97363007 97363069 - ENSG00000281389.1 AL442067.1 miRNA +chr14 20343075 20343407 - ENSG00000277209.1 RNaseP_nuc ribozyme +chr14 21023314 21023386 - ENSG00000278629.1 MIR6717 miRNA +chr14 22281105 22281748 + ENSG00000211817.2 TRAV38-2DV8 TR_V_gene +chr14 22450089 22450139 + ENSG00000211825.1 TRDJ1 TR_J_gene +chr14 22509341 22509406 + ENSG00000211857.1 TRAJ32 TR_J_gene +chr14 22956950 22957029 - ENSG00000265037.1 MIR4707 miRNA +chr14 23033530 23033638 - ENSG00000207765.1 AL132780.1 miRNA +chr14 24143489 24143565 - ENSG00000276511.1 MIR7703 miRNA +chr14 35809212 35809300 - ENSG00000266264.1 AL162311.1 miRNA +chr14 49577392 49577794 - ENSG00000244270.1 RPL32P29 processed_pseudogene +chr14 49586580 49586878 + ENSG00000276168.1 RN7SL1 misc_RNA +chr14 49586722 49586791 + ENSG00000281893.1 AL139099.3 miRNA +chr14 49853703 49853772 - ENSG00000279868.2 AL627171.1 miRNA +chr14 49862638 49862707 - ENSG00000280602.1 AL627171.3 miRNA +chr14 53153049 53153115 - ENSG00000266552.1 AL356020.1 miRNA +chr14 55413556 55414059 - ENSG00000239199.1 RPL21P6 processed_pseudogene +chr14 60972272 60972466 - ENSG00000258656.1 RP11-193F5.4 processed_pseudogene +chr14 68887785 68888084 - ENSG00000258967.1 HMGN1P3 processed_pseudogene +chr14 74480133 74480204 - ENSG00000265649.1 MIR4709 miRNA +chr14 76778952 76782249 + ENSG00000258610.1 RP11-488C13.7 lincRNA +chr14 95185117 95185854 - ENSG00000259143.1 CTD-2240H23.2 sense_overlapping +chr14 95662480 95662598 + ENSG00000275033.1 TCL6_2 misc_RNA +chr14 95670441 95670577 + ENSG00000277468.1 TCL6_3 misc_RNA +chr14 100829350 100829454 + ENSG00000276919.1 MEG3_2 misc_RNA +chr14 100894817 100894913 + ENSG00000276225.1 MEG8_1 misc_RNA +chr14 100898958 100899079 + ENSG00000275134.1 MEG8_2 misc_RNA +chr14 100987046 100987117 + ENSG00000200413.1 SNORD114-26 snoRNA +chr14 101560287 101560422 - ENSG00000277601.1 MIR1247 miRNA +chr14 102501676 102501779 + ENSG00000212330.1 RNU6-244P snRNA +chr14 105863198 105863258 - ENSG00000211900.2 IGHJ6 IG_J_gene +chr14 105863814 105863862 - ENSG00000242472.1 IGHJ5 IG_J_gene +chr14 105864215 105864260 - ENSG00000240041.1 IGHJ4 IG_J_gene +chr14 106636704 106636763 + ENSG00000280494.1 AC245369.3 miRNA +chr15 20759311 20774794 - ENSG00000259383.1 RP11-403B2.6 lincRNA +chr15 24981994 24982068 + ENSG00000276314.1 SNORD107 snoRNA +chr15 24985100 24985166 + ENSG00000276610.1 SNORD64 snoRNA +chr15 24986925 24986995 + ENSG00000239014.1 SNORD108 snoRNA +chr15 25041974 25042040 + ENSG00000274640.1 SNORD109B snoRNA +chr15 25087662 25087753 + ENSG00000278715.1 SNORD116-20 snoRNA +chr15 25088804 25088895 + ENSG00000277785.1 SNORD116-21 snoRNA +chr15 25104642 25104732 + ENSG00000278123.1 SNORD116-28 snoRNA +chr15 25182385 25182466 + ENSG00000278089.1 SNORD115-7 snoRNA +chr15 25193321 25193402 + ENSG00000273835.1 SNORD115-13 snoRNA +chr15 25218617 25218698 + ENSG00000275524.1 SNORD115-26 snoRNA +chr15 30380353 30386987 - ENSG00000263070.1 RP11-382B18.3 transcribed_unprocessed_pseudogene +chr15 34373789 34373871 - ENSG00000266205.1 AC025678.1 miRNA +chr15 40331537 40331648 - ENSG00000252714.1 RNA5SP392 rRNA +chr15 45214906 45215033 - ENSG00000261709.3 SNORA11 snoRNA +chr15 45433050 45433129 + ENSG00000211519.1 MIR147B miRNA +chr15 50360329 50360410 + ENSG00000264109.1 MIR4712 miRNA +chr15 62246284 62246349 - ENSG00000277779.1 AC126323.2 miRNA +chr15 66379337 66379915 - ENSG00000240821.1 RPL9P25 processed_pseudogene +chr15 66501250 66501318 - ENSG00000199574.1 SNORD18C snoRNA +chr15 66502019 66502089 - ENSG00000280554.1 snoU18 snoRNA +chr15 66502020 66502091 - ENSG00000202529.1 SNORD18B snoRNA +chr15 66502812 66502910 - ENSG00000199673.1 SNORD16 snoRNA +chr15 66503243 66503314 - ENSG00000200623.1 SNORD18A snoRNA +chr15 69160651 69160724 + ENSG00000266374.1 AC026512.1 miRNA +chr15 69406441 69406552 + ENSG00000207395.1 Y_RNA misc_RNA +chr15 72587217 72587313 + ENSG00000207690.1 MIR630 miRNA +chr15 72589691 72591845 + ENSG00000260534.1 RP11-1006G14.4 sense_overlapping +chr15 74303005 74304343 + ENSG00000261384.1 RP11-60L3.2 sense_intronic +chr15 75762215 75762315 - ENSG00000274496.1 MIR4313 miRNA +chr15 82726550 82726633 - ENSG00000266697.1 AC105339.2 miRNA +chr15 82755945 82756071 + ENSG00000277864.1 SCARNA15 scaRNA +chr15 82756006 82756069 + ENSG00000280933.1 AC105339.3 miRNA +chr15 83113617 83114566 - ENSG00000260579.1 RP11-382A20.2 antisense +chr15 84204516 84204599 - ENSG00000221008.1 AC136698.1 miRNA +chr15 84633874 84634635 + ENSG00000254779.4 EGLN1P1 transcribed_processed_pseudogene +chr15 84642487 84642763 - ENSG00000277578.1 Metazoa_SRP misc_RNA +chr15 85380596 85380662 + ENSG00000276648.1 MIR7706 miRNA +chr15 90275129 90275716 + ENSG00000228998.4 RP11-697E2.7 transcribed_processed_pseudogene +chr15 90294059 90294142 + ENSG00000280965.1 AC091167.2 miRNA +chr15 91029888 91029996 + ENSG00000258542.1 AC068831.11 transcribed_processed_pseudogene +chr15 96333261 96333307 + ENSG00000222651.1 MIR1469 miRNA +chr15 99792297 99792379 + ENSG00000221511.1 AC090825.1 miRNA +chr16 1962334 1962466 - ENSG00000206811.1 SNORA10 snoRNA +chr16 1962973 1963106 - ENSG00000207405.1 SNORA64 snoRNA +chr16 1963745 1964095 - ENSG00000255513.1 AC005363.9 transcribed_processed_pseudogene +chr16 1965184 1965310 + ENSG00000273587.1 SNORA78 snoRNA +chr16 2155025 2155104 - ENSG00000281010.1 snoR1 snoRNA +chr16 2271737 2271846 + ENSG00000274753.1 MIR940 miRNA +chr16 2769872 2769949 + ENSG00000265864.1 AC092117.2 miRNA +chr16 3069523 3069651 + ENSG00000252561.1 RNU1-125P snRNA +chr16 3308609 3308816 + ENSG00000262554.1 LA16c-360H6.2 transcribed_processed_pseudogene +chr16 8683461 8683543 + ENSG00000281170.1 AC007224.1 miRNA +chr16 9104848 9113181 + ENSG00000263244.2 RP11-473I1.9 3prime_overlapping_ncrna +chr16 11915661 11915738 - ENSG00000266163.1 AC007216.1 miRNA +chr16 14901508 14901591 + ENSG00000274301.1 MIR3179-3 miRNA +chr16 15611030 15611095 - ENSG00000275184.1 MIR6506 miRNA +chr16 15643281 15643390 + ENSG00000272213.2 AC026401.1 miRNA +chr16 19498610 19498747 + ENSG00000222750.1 RNU4-46P snRNA +chr16 21519830 21520365 - ENSG00000258186.2 SLC7A5P2 transcribed_processed_pseudogene +chr16 23061406 23064173 - ENSG00000260566.2 RP11-20G6.3 3prime_overlapping_ncrna +chr16 23670011 23675499 + ENSG00000260482.3 CTD-2196E14.9 3prime_overlapping_ncrna +chr16 28958583 28958661 + ENSG00000266868.1 MIR4517 miRNA +chr16 28982014 28982130 + ENSG00000281146.1 AC109460.1 miRNA +chr16 30670160 30670297 + ENSG00000280843.1 AC093249.1 miRNA +chr16 31109211 31109318 + ENSG00000252809.3 AC135050.1 miRNA +chr16 35023339 35023765 + ENSG00000262885.1 CTD-2144E22.11 processed_pseudogene +chr16 48447904 48448398 - ENSG00000261802.1 RP11-44I10.6 sense_overlapping +chr16 58559796 58559929 - ENSG00000206952.3 SNORA76A snoRNA +chr16 66550457 66550567 + ENSG00000275745.1 Y_RNA misc_RNA +chr16 67019727 67019811 + ENSG00000281589.1 AC009084.1 miRNA +chr16 67390691 67390850 - ENSG00000239194.1 RNU1-123P snRNA +chr16 67877657 67877740 + ENSG00000221526.1 AC040162.1 miRNA +chr16 68233426 68233499 - ENSG00000276151.1 MIR6773 miRNA +chr16 68742495 68742551 + ENSG00000281454.1 AC099314.1 miRNA +chr16 69328644 69334871 - ENSG00000272617.1 RP11-343C2.12 protein_coding +chr16 69463844 69466264 + ENSG00000260108.1 RP11-140H17.1 3prime_overlapping_ncrna +chr16 69703065 69704652 + ENSG00000260772.1 RP11-311C24.1 3prime_overlapping_ncrna +chr16 72787693 72787773 - ENSG00000265573.1 AC004943.1 miRNA +chr16 81170740 81181213 - ENSG00000279362.1 PKD1L2 protein_coding +chr16 81385018 81385093 + ENSG00000273048.1 MIR4720 miRNA +chr16 81385463 81387560 + ENSG00000272923.1 RP11-391L3.1 lincRNA +chr16 81961926 81962243 + ENSG00000260682.3 7SK misc_RNA +chr16 89561434 89561517 + ENSG00000200084.1 SNORD68 snoRNA +chr17 1713895 1714005 - ENSG00000275595.1 AC130343.2 miRNA +chr17 2041936 2043430 + ENSG00000262664.2 OVCA2 protein_coding +chr17 2329119 2329213 - ENSG00000212552.3 SNORD91B snoRNA +chr17 2330276 2330370 - ENSG00000274802.1 SNORD91A snoRNA +chr17 3310312 3311189 + ENSG00000180068.8 OR3A4P transcribed_unprocessed_pseudogene +chr17 5514209 5514270 - ENSG00000280489.1 U7 snRNA +chr17 6651914 6652270 + ENSG00000279257.1 C17orf100 protein_coding +chr17 7017615 7017701 - ENSG00000275739.1 MIR195 miRNA +chr17 7017911 7018022 - ENSG00000273895.1 MIR497 miRNA +chr17 7574713 7574847 + ENSG00000209582.1 SNORA48 snoRNA +chr17 7576811 7576952 + ENSG00000238917.1 SNORD10 snoRNA +chr17 7577955 7578091 + ENSG00000277985.1 SNORA67 snoRNA +chr17 8144994 8145071 - ENSG00000278027.1 MIR6883 miRNA +chr17 8173454 8173587 - ENSG00000200463.1 SNORD118 snoRNA +chr17 16044621 16044961 + ENSG00000243686.2 RPLP1P11 processed_pseudogene +chr17 16439505 16439576 + ENSG00000277108.1 SNORD49 snoRNA +chr17 16440036 16440106 + ENSG00000277370.1 SNORD49A snoRNA +chr17 16441226 16441298 + ENSG00000277512.1 SNORD65 snoRNA +chr17 16812447 16812651 + ENSG00000264892.1 NOS2P4 processed_pseudogene +chr17 17242564 17242647 + ENSG00000265109.1 AC055811.1 miRNA +chr17 18340814 18340886 - ENSG00000275820.1 MIR6778 miRNA +chr17 18388871 18389459 + ENSG00000267441.1 RP1-37N7.5 processed_pseudogene +chr17 19061912 19062128 + ENSG00000280523.1 SNORD3B-2 snoRNA +chr17 19061912 19062129 + ENSG00000276271.1 SNORD3B-2 snoRNA +chr17 19063919 19064136 - ENSG00000274088.1 SNORD3B-1 snoRNA +chr17 19063920 19064136 - ENSG00000281187.1 SNORD3B-2 snoRNA +chr17 19112419 19112636 - ENSG00000277947.1 SNORD3D snoRNA +chr17 19112420 19112636 - ENSG00000281000.1 SNORD3D snoRNA +chr17 19188016 19188232 + ENSG00000281298.1 SNORD3A snoRNA +chr17 19188016 19188233 + ENSG00000277813.1 SNORD3A snoRNA +chr17 19190028 19190245 - ENSG00000275303.1 SNORD3C snoRNA +chr17 19190029 19190245 - ENSG00000280847.1 SNORD3C snoRNA +chr17 19557560 19557711 + ENSG00000276660.1 SNORA59A snoRNA +chr17 19649494 19649587 - ENSG00000275982.1 Y_RNA misc_RNA +chr17 20981489 20981654 + ENSG00000266009.1 RP11-746M1.2 transcribed_processed_pseudogene +chr17 22435629 22436064 + ENSG00000265705.1 RP11-744K17.8 transcribed_processed_pseudogene +chr17 28276463 28276553 - ENSG00000207844.1 AC061975.1 miRNA +chr17 28360654 28360734 + ENSG00000264302.1 MIR4723 miRNA +chr17 28723429 28723492 + ENSG00000238649.1 SNORD42A snoRNA +chr17 28723682 28723753 + ENSG00000238597.1 SNORD4B snoRNA +chr17 28861369 28861440 - ENSG00000273915.1 MIR451A miRNA +chr17 28861514 28861624 - ENSG00000277441.1 AC024267.1 miRNA +chr17 28861655 28861730 - ENSG00000278521.1 MIR4732 miRNA +chr17 29390662 29390730 + ENSG00000263719.1 MIR4523 miRNA +chr17 30059054 30059147 - ENSG00000267482.1 RNY4P13 unprocessed_pseudogene +chr17 30117079 30117172 + ENSG00000199071.2 MIR423 miRNA +chr17 30702506 30702586 - ENSG00000281673.1 AC005562.2 miRNA +chr17 31534883 31534971 + ENSG00000266459.1 MIR4724 miRNA +chr17 35097560 35097657 - ENSG00000252328.1 Vault misc_RNA +chr17 38851524 38851659 - ENSG00000252699.1 SNORA21 snoRNA +chr17 38852863 38852994 - ENSG00000199293.1 SNORA21 snoRNA +chr17 39081065 39081187 + ENSG00000222494.1 AC091178.1 miRNA +chr17 40026332 40026409 - ENSG00000275267.1 MIR6884 miRNA +chr17 43387226 43387417 - ENSG00000277084.1 U2 snRNA +chr17 43444806 43444885 + ENSG00000278547.1 MIR2117 miRNA +chr17 44123539 44123649 - ENSG00000274433.1 AC023855.1 miRNA +chr17 44899712 44905390 + ENSG00000214447.4 FAM187A protein_coding +chr17 45637110 45637206 + ENSG00000273917.1 AC126544.1 miRNA +chr17 46537734 46537813 + ENSG00000280583.1 AC138645.1 miRNA +chr17 47042025 47042104 + ENSG00000281864.1 AC068152.1 miRNA +chr17 48048365 48048430 + ENSG00000273862.1 AC004477.1 miRNA +chr17 48382371 48382586 - ENSG00000200538.2 U3 snoRNA +chr17 48579838 48579947 - ENSG00000274592.1 MIR10A miRNA +chr17 49049540 49049624 + ENSG00000264552.1 AC105030.1 miRNA +chr17 51166831 51171507 + ENSG00000280803.1 NME1-NME2 protein_coding +chr17 56891270 56891355 - ENSG00000265238.1 MIR3614 miRNA +chr17 58331215 58331325 - ENSG00000273667.1 AC004687.1 miRNA +chr17 59841266 59841337 + ENSG00000199004.1 MIR21 miRNA +chr17 60810957 60811052 + ENSG00000211515.1 AC079005.1 miRNA +chr17 62005737 62006016 - ENSG00000242398.3 RN7SL800P misc_RNA +chr17 64146337 64146471 + ENSG00000281311.1 SNORA76C snoRNA +chr17 64146339 64146471 + ENSG00000277887.1 SNORA76C snoRNA +chr17 64500773 64500839 - ENSG00000265695.1 MIR3064 miRNA +chr17 64501214 64501313 - ENSG00000266241.1 MIR5047 miRNA +chr17 64749918 64758603 - ENSG00000266820.1 RP13-104F24.1 transcribed_unprocessed_pseudogene +chr17 64940606 64940717 + ENSG00000272346.2 RP11-927P21.11 transcribed_unprocessed_pseudogene +chr17 75498548 75498628 + ENSG00000276372.1 MIR6785 miRNA +chr17 75784521 75784607 - ENSG00000263565.1 MIR4738 miRNA +chr17 75910723 75938149 - ENSG00000281844.1 FBF1 protein_coding +chr17 76558791 76558868 + ENSG00000274091.1 SNORD1C snoRNA +chr17 76561634 76561705 + ENSG00000278261.1 SNORD1A snoRNA +chr17 76736450 76736548 - ENSG00000207556.1 MIR636 miRNA +chr17 77089307 77089493 + ENSG00000275143.1 SCARNA16 scaRNA +chr17 77089417 77089497 + ENSG00000281678.1 MIR6516 miRNA +chr17 81511026 81511109 - ENSG00000266077.1 AC139149.1 miRNA +chr17 82236668 82236728 + ENSG00000275505.1 MIR6787 miRNA +chr18 14074912 14075741 - ENSG00000267756.1 RP11-411B10.4 unprocessed_pseudogene +chr18 21712017 21712119 - ENSG00000281568.1 AC106037.1 miRNA +chr18 21825698 21825785 - ENSG00000276792.1 MIR133A1 miRNA +chr18 21828996 21829106 - ENSG00000278753.1 AC103987.1 miRNA +chr18 22933349 22933438 + ENSG00000264817.1 MIR4741 miRNA +chr18 26689316 26689529 - ENSG00000275900.1 U3 snoRNA +chr18 27452623 27452712 - ENSG00000280492.1 AC068408.1 miRNA +chr18 35466938 35466991 - ENSG00000277489.1 AC007998.1 miRNA +chr18 49487373 49487422 + ENSG00000278544.1 MIR1539 miRNA +chr18 49489245 49489308 - ENSG00000202093.1 SNORD58C snoRNA +chr18 49491283 49491347 - ENSG00000206602.1 SNORD58A snoRNA +chr18 49491664 49491729 - ENSG00000271982.1 SNORD58B snoRNA +chr18 49814133 49814276 + ENSG00000251992.1 SCARNA17 scaRNA +chr18 49814361 49814443 + ENSG00000252139.1 SCARNA18 scaRNA +chr18 57435821 57435880 + ENSG00000266636.1 AC090340.1 miRNA +chr18 58451068 58451176 + ENSG00000207778.2 MIR122 miRNA +chr19 804940 805001 + ENSG00000265767.1 MIR4745 miRNA +chr19 1816159 1816238 - ENSG00000223244.1 MIR1909 miRNA +chr19 2235829 2235926 - ENSG00000276587.1 MIR6789 miRNA +chr19 2250639 2250718 + ENSG00000267021.1 MIR4321 miRNA +chr19 3961414 3961512 - ENSG00000207733.1 MIR637 miRNA +chr19 6176256 6176442 - ENSG00000267415.1 CTC-503J8.2 transcribed_processed_pseudogene +chr19 6736712 6736778 - ENSG00000277714.1 MIR6791 miRNA +chr19 10403458 10403538 - ENSG00000221566.1 MIR1181 miRNA +chr19 12379746 12383687 - ENSG00000248406.1 CTD-3105H18.4 transcribed_unprocessed_pseudogene +chr19 14073361 14073479 + ENSG00000277805.1 MIR1199 miRNA +chr19 14213241 14213321 + ENSG00000280955.1 AC011509.1 miRNA +chr19 15834730 15834804 + ENSG00000273782.1 UCA1 misc_RNA +chr19 16910496 16910579 - ENSG00000280536.1 AC008737.1 miRNA +chr19 17862588 17862720 + ENSG00000207166.1 SNORA68 snoRNA +chr19 18868545 18896096 - ENSG00000130283.8 GDF1 protein_coding +chr19 20125044 20125484 + ENSG00000224864.4 CTC-260E6.2 transcribed_processed_pseudogene +chr19 21188598 21188953 + ENSG00000268995.1 VN1R82P unprocessed_pseudogene +chr19 21753011 21753083 + ENSG00000265084.1 AC092364.1 miRNA +chr19 22601485 22601707 + ENSG00000240713.3 RN7SL860P misc_RNA +chr19 33207129 33207639 + ENSG00000273420.1 CTD-2540B15.13 3prime_overlapping_ncrna +chr19 34645662 34646070 + ENSG00000269811.2 SCGB2B3P processed_pseudogene +chr19 35122700 35122764 + ENSG00000278663.1 MIR6887 miRNA +chr19 44758657 44758721 + ENSG00000277736.1 MIR8085 miRNA +chr19 45149750 45150605 - ENSG00000267037.1 AC005757.7 lincRNA +chr19 45638994 45639087 - ENSG00000199066.1 MIR330 miRNA +chr19 45938139 45938282 - ENSG00000280818.1 AC008623.1 miRNA +chr19 47581231 47581313 + ENSG00000281476.1 AC010331.1 miRNA +chr19 47755853 47755962 + ENSG00000221803.1 SNORD23 snoRNA +chr19 49489965 49490048 + ENSG00000201675.1 SNORD32A snoRNA +chr19 49490615 49490699 + ENSG00000199631.1 SNORD33 snoRNA +chr19 49490904 49490974 + ENSG00000202503.1 SNORD34 snoRNA +chr19 49491175 49491260 + ENSG00000200259.1 SNORD35A snoRNA +chr19 49497720 49497806 + ENSG00000200530.1 SNORD35B snoRNA +chr19 49832018 49832099 + ENSG00000277609.1 MIR6800 miRNA +chr19 49888175 49888230 + ENSG00000263462.1 MIR4750 miRNA +chr19 49933064 49933137 + ENSG00000265438.1 MIR4751 miRNA +chr19 49949316 49949527 - ENSG00000221125.2 U3 snoRNA +chr19 50799032 50799122 - ENSG00000221381.1 SNORD88B snoRNA +chr19 50802328 50802418 - ENSG00000220988.1 SNORD88C snoRNA +chr19 52564076 52564231 + ENSG00000242255.1 RPL39P34 transcribed_unprocessed_pseudogene +chr19 53386233 53386388 + ENSG00000241069.1 CTD-3141N22.1 transcribed_processed_pseudogene +chr19 53495887 53496037 + ENSG00000241434.1 CTD-2224J9.4 transcribed_processed_pseudogene +chr19 53762335 53762445 + ENSG00000280835.1 AC011453.2 miRNA +chr19 53982307 53982397 + ENSG00000215998.1 MIR935 miRNA +chr19 54589441 54590287 + ENSG00000269271.1 CTB-83J4.2 lincRNA +chr19 55388181 55388242 + ENSG00000277326.1 MIR6805 miRNA +chr19 55707550 55707855 + ENSG00000268593.3 CTD-2611O12.6 processed_pseudogene +chr19 56840905 56840992 + ENSG00000281440.1 MIMT1_1 sRNA +chr19 56848068 56848204 + ENSG00000274777.1 MIMT1_2 misc_RNA +chr19 58582024 58582609 + ENSG00000268784.1 MGC2752 transcribed_unprocessed_pseudogene +chr19 58586158 58586356 + ENSG00000269032.1 AC016629.7 transcribed_processed_pseudogene +chr20 1392900 1392961 - ENSG00000276741.1 MIR6869 miRNA +chr20 2652777 2652842 + ENSG00000221062.1 MIR1292 miRNA +chr20 2654212 2654286 + ENSG00000221116.1 SNORD110 snoRNA +chr20 2656097 2656182 + ENSG00000212498.1 SNORD86 snoRNA +chr20 2656624 2656694 + ENSG00000229686.1 SNORD56 snoRNA +chr20 2656939 2657010 + ENSG00000226572.1 SNORD57 snoRNA +chr20 22733210 22733301 - ENSG00000265151.1 AL158175.1 miRNA +chr20 31581089 31581192 + ENSG00000201770.1 RNU6-384P snRNA +chr20 32237795 32237847 + ENSG00000221667.1 MIR1825 miRNA +chr20 36255716 36255820 + ENSG00000281193.1 AL121895.1 miRNA +chr20 38421647 38421774 - ENSG00000277034.1 SNORA71 snoRNA +chr20 38425198 38425331 - ENSG00000273718.1 SNORA71 snoRNA +chr20 38448084 38448215 + ENSG00000274309.1 SNORA71E snoRNA +chr20 47651067 47651156 + ENSG00000280970.1 AL034418.1 miRNA +chr20 49278427 49278624 + ENSG00000277830.1 ZNFX1-AS1_1 misc_RNA +chr20 49279116 49279208 + ENSG00000274760.1 ZNFX1-AS1_2 misc_RNA +chr20 49280485 49280571 + ENSG00000277967.1 ZNFX1-AS1_3 misc_RNA +chr20 49280683 49280772 + ENSG00000212304.1 SNORD12 snoRNA +chr20 58817615 58817694 - ENSG00000276373.1 MIR296 miRNA +chr20 61953546 61953662 - ENSG00000221417.1 MIR1257 miRNA +chr20 63696668 63698684 + ENSG00000243509.4 TNFRSF6B protein_coding +chr20 63941465 63941544 - ENSG00000272045.1 MIR1914 miRNA +chr21 6994374 6997737 - ENSG00000279313.1 CH507-145C22.4 lincRNA +chr21 14143581 14144158 + ENSG00000240755.1 ERLEC1P1 processed_pseudogene +chr21 25573980 25574044 + ENSG00000275402.1 MIR155 miRNA +chr21 33550662 33550728 + ENSG00000275224.1 MIR6501 miRNA +chr21 39171462 39171560 - ENSG00000276873.1 uc_338 misc_RNA +chr21 44328944 44330221 - ENSG00000241728.4 AP001062.8 sense_overlapping +chr22 15826566 15827187 + ENSG00000271672.1 DUXAP8 transcribed_processed_pseudogene +chr22 16961936 17008222 - ENSG00000215568.6 GAB4 protein_coding +chr22 17021398 17022570 - ENSG00000276400.1 VN1R9P processed_pseudogene +chr22 18101612 18101888 + ENSG00000235617.1 XXbac-B476C20.10 unprocessed_pseudogene +chr22 19722945 19724771 + ENSG00000203618.5 GP1BB protein_coding +chr22 20085746 20085833 + ENSG00000266567.1 MIR3618 miRNA +chr22 20086042 20086150 + ENSG00000221366.2 MIR1306 miRNA +chr22 20126402 20126526 + ENSG00000264346.1 SNORA77 snoRNA +chr22 20483225 20483316 - ENSG00000265300.1 AC007731.1 miRNA +chr22 22895375 22895834 + ENSG00000211675.2 IGLC1 IG_C_gene +chr22 26671402 26671550 + ENSG00000277941.1 MIAT_exon5_1 misc_RNA +chr22 26672164 26672248 + ENSG00000275942.1 MIAT_exon5_2 misc_RNA +chr22 26673254 26673630 + ENSG00000276991.1 MIAT_exon5_3 misc_RNA +chr22 27919384 27919545 + ENSG00000277460.1 TTC28-AS1_1 misc_RNA +chr22 27922022 27922178 + ENSG00000276150.1 TTC28-AS1_2 misc_RNA +chr22 28002484 28002595 + ENSG00000276675.1 TTC28-AS1_4 misc_RNA +chr22 28992721 29018620 + ENSG00000235786.1 ZNRF3-IT1 sense_intronic +chr22 29073078 29168333 + ENSG00000183762.11 KREMEN1 protein_coding +chr22 29134014 29134120 + ENSG00000200871.1 RNU6-810P snRNA +chr22 29333163 29333258 - ENSG00000239127.1 SNORD125 snoRNA +chr22 29711820 29719714 - ENSG00000239446.1 RP1-76B20.12 antisense +chr22 30971005 30971149 + ENSG00000276664.1 TUG1_1 misc_RNA +chr22 30971296 30971382 + ENSG00000276057.1 TUG1_2 misc_RNA +chr22 30972857 30973093 + ENSG00000276965.1 TUG1_3 misc_RNA +chr22 30973417 30973597 + ENSG00000275307.1 TUG1_4 misc_RNA +chr22 31059989 31060285 + ENSG00000240186.3 RN7SL633P misc_RNA +chr22 31621467 31621531 - ENSG00000275382.1 MIR7109 miRNA +chr22 31837238 31837298 + ENSG00000252909.1 RNU6-201P snRNA +chr22 33704786 33704920 - ENSG00000253007.2 SNORA76 snoRNA +chr22 35164304 35165347 + ENSG00000238153.1 CTA-714B7.4 processed_pseudogene +chr22 37844272 37844371 - ENSG00000207945.1 MIR658 miRNA +chr22 37891347 37891448 + ENSG00000207227.1 RNU6-900P snRNA +chr22 37950965 37951778 + ENSG00000272582.1 RP5-1039K5.17 antisense +chr22 37967563 37967624 + ENSG00000277321.1 MIR6820 miRNA +chr22 37988794 37988853 + ENSG00000264505.1 MIR4534 miRNA +chr22 39120293 39120566 - ENSG00000226024.1 COX5BP7 processed_pseudogene +chr22 39313819 39313911 - ENSG00000209480.1 SNORD83B snoRNA +chr22 39319050 39319113 - ENSG00000263764.1 SNORD43 snoRNA +chr22 41092513 41092566 + ENSG00000221160.1 MIR1281 miRNA +chr22 41923222 41923297 - ENSG00000263463.1 MIR378I miRNA +chr22 42569147 42569250 - ENSG00000251913.1 RNU6-513P snRNA +chr22 42615244 42615393 + ENSG00000276027.1 RNU12 snRNA +chr22 45976878 45976954 - ENSG00000265610.1 CR536603.1 miRNA +chr22 46112732 46112840 + ENSG00000198986.2 MIRLET7A3 miRNA +chr22 46113566 46113657 + ENSG00000264147.1 MIR4763 miRNA +chr22 46113686 46113768 + ENSG00000207875.1 MIRLET7B miRNA +chrX 3607258 3607365 - ENSG00000207332.1 RNU6-146P snRNA +chrX 21872707 21872808 + ENSG00000206639.1 Y_RNA misc_RNA +chrX 37441523 37442068 + ENSG00000241607.1 RP11-357K9.2 unprocessed_pseudogene +chrX 41233633 41234283 + ENSG00000269941.1 RP5-1172N10.4 sense_intronic +chrX 52063347 52063474 - ENSG00000221705.1 SNORA11E snoRNA +chrX 52190621 52190748 + ENSG00000221475.1 SNORA11D snoRNA +chrX 53143034 53143117 - ENSG00000266700.1 AL139396.1 miRNA +chrX 54927305 54927433 + ENSG00000221750.1 SNORA11 snoRNA +chrX 66018870 66018979 + ENSG00000207939.1 MIR223 miRNA +chrX 67545277 67545422 + ENSG00000280956.1 AL049564.1 miRNA +chrX 70846080 70846295 - ENSG00000280704.1 U3 snoRNA +chrX 73821657 73821724 - ENSG00000274655.1 XIST_intron misc_RNA +chrX 73831145 73831270 - ENSG00000277577.1 Xist_exon4 misc_RNA +chrX 73944332 73944466 + ENSG00000274430.1 JPX_1 misc_RNA +chrX 73944595 73944663 + ENSG00000276784.1 JPX_2 misc_RNA +chrX 80024067 80031111 + ENSG00000281700.1 TBX22 protein_coding +chrX 85244095 85244171 + ENSG00000264517.1 AC003001.1 miRNA +chrX 92460452 92460545 + ENSG00000211526.1 AL121869.1 miRNA +chrX 107428989 107429079 + ENSG00000207846.1 AL035088.1 miRNA +chrX 112780718 112780788 - ENSG00000263351.1 MIR4329 miRNA +chrX 115622308 115649561 + ENSG00000281638.1 AL589842.1 protein_coding +chrX 115703812 115703867 + ENSG00000264759.1 AC005000.1 miRNA +chrX 120877496 120878924 - ENSG00000278646.1 RP1-321E8.5 protein_coding +chrX 136879199 136879271 - ENSG00000206979.1 SNORD61 snoRNA +chrX 140086058 140086145 + ENSG00000280833.1 AL589987.1 miRNA +chrX 148501098 148991332 + ENSG00000281817.1 AFF2 protein_coding +chrX 151956683 151956778 - ENSG00000264120.1 AF274855.1 miRNA +chrX 151958578 151958658 - ENSG00000207621.1 MIR224 miRNA +chrX 151959607 151959719 - ENSG00000207753.2 MIR452 miRNA +chrX 154400281 154400415 + ENSG00000207165.1 SNORA70 snoRNA +chrX 154768596 154768656 + ENSG00000281135.1 MIR664B miRNA +chrX 154774998 154775126 + ENSG00000206693.1 SNORA56 snoRNA +chrX 156022631 156022698 + ENSG00000276543.3 AJ271736.1 miRNA +chrY 5573928 5574019 + ENSG00000252059.2 AC012667.1 miRNA +chrY 7378672 7378779 + ENSG00000252155.1 RNU6-941P snRNA +chrY 57209151 57209218 + ENSGR0000276543.3 AJ271736.1 miRNA diff --git a/docs/Data/Bioinformatics_Pipelines/overlap.gene.strandless.tsv b/docs/Data/Bioinformatics_Pipelines/overlap.gene.strandless.tsv new file mode 100644 index 000000000..702d9b31b --- /dev/null +++ b/docs/Data/Bioinformatics_Pipelines/overlap.gene.strandless.tsv @@ -0,0 +1,1727 @@ +seqname start end strand gene_id gene_name gene_type +chr1 30366 30503 + ENSG00000274890.1 MIR1302-9 miRNA +chr1 89551 91105 - ENSG00000239945.1 RP11-34P13.8 lincRNA +chr1 258568 259024 - ENSG00000241670.3 AP006222.1 processed_pseudogene +chr1 632325 632413 - ENSG00000278791.1 MIR6723 miRNA +chr1 965110 965166 + ENSG00000277294.1 AL645608.1 miRNA +chr1 1055033 1056116 + ENSG00000242590.1 RP11-54O7.14 sense_intronic +chr1 1312502 1312566 - ENSG00000274153.1 MIR6727 miRNA +chr1 1405460 1405752 - ENSG00000264293.2 RN7SL657P misc_RNA +chr1 3736943 3737103 + ENSG00000276189.1 TP73-AS1 misc_RNA +chr1 6393555 6394391 + ENSG00000271746.1 RP1-202O8.3 antisense +chr1 9848318 9850154 + ENSG00000223989.1 RP11-84A14.5 antisense +chr1 9983141 9984568 + ENSG00000241326.1 RP11-807G9.2 sense_intronic +chr1 10306465 10306757 + ENSG00000264501.2 RN7SL731P misc_RNA +chr1 10458555 10459338 + ENSG00000203469.2 RP5-1113E3.3 antisense +chr1 11843812 11843984 + ENSG00000276470.1 NPPA-AS1_1 misc_RNA +chr1 11845549 11845697 + ENSG00000278852.1 NPPA-AS1_2 misc_RNA +chr1 11847442 11847549 + ENSG00000275915.1 NPPA-AS1_3 misc_RNA +chr1 12824942 12828663 - ENSG00000279195.1 PRAMEF11 protein_coding +chr1 15659869 15661722 + ENSG00000215695.1 RSC1A1 protein_coding +chr1 15684472 15684558 + ENSG00000264048.1 AL121992.1 miRNA +chr1 16006160 16006671 - ENSG00000233078.1 RP11-5P18.5 antisense +chr1 16197854 16198357 + ENSG00000234166.1 ARHGEF19-AS1 antisense +chr1 16408508 16408583 + ENSG00000281598.1 AL358794.1 miRNA +chr1 16873708 16873851 + ENSG00000277234.1 U1 snRNA +chr1 17406760 17407382 + ENSG00000227751.1 RP1-20B21.4 antisense +chr1 17413631 17413694 - ENSG00000266727.1 AC004824.1 miRNA +chr1 20633679 20633788 + ENSG00000273695.1 MIR6084 miRNA +chr1 23370254 23370346 + ENSG00000201405.1 Y_RNA misc_RNA +chr1 25831913 25832134 - ENSG00000272478.1 RP1-317E23.7 antisense +chr1 26876133 26878245 + ENSG00000226698.1 RP1-50O24.6 antisense +chr1 27325470 27325553 + ENSG00000281023.1 FO393419.1 miRNA +chr1 27850574 27850744 - ENSG00000278868.1 AL109927.1 protein_coding +chr1 28507366 28507571 + ENSG00000274266.1 SNORA73A snoRNA +chr1 28579764 28579893 - ENSG00000278274.1 SNORA61 snoRNA +chr1 28580381 28580512 - ENSG00000273544.1 SNORA44 snoRNA +chr1 28580920 28581054 - ENSG00000280498.1 SNORA16A snoRNA +chr1 28580920 28581056 - ENSG00000274582.1 SNORA16A snoRNA +chr1 28648600 28648730 + ENSG00000270103.3 RNU11 lincRNA +chr1 32170733 32176568 + ENSG00000250135.1 RP4-622L5.2 sense_intronic +chr1 35925832 35929610 + ENSG00000280133.1 RP4-789D17.3 TEC +chr1 37480230 37480289 + ENSG00000278228.1 MIR6732 miRNA +chr1 37799720 37800879 - ENSG00000233728.1 RP11-109P14.9 antisense +chr1 37860697 37861580 + ENSG00000230955.1 RP11-109P14.10 antisense +chr1 40984853 40984919 - ENSG00000281712.1 AL391730.2 miRNA +chr1 43364648 43364715 - ENSG00000277622.1 MIR6734 miRNA +chr1 43448539 43448611 + ENSG00000274975.1 MIR6735 miRNA +chr1 44103945 44104079 + ENSG00000281534.1 AL139220.1 miRNA +chr1 44775864 44775943 + ENSG00000264294.1 SNORD55 snoRNA +chr1 44778390 44778456 + ENSG00000207421.1 SNORD38B snoRNA +chr1 44778390 44778458 + ENSG00000281859.1 SNORD38B snoRNA +chr1 44819883 44819997 - ENSG00000202444.1 RNU5E-6P snRNA +chr1 47761132 47765547 - ENSG00000223814.1 RP11-543D5.2 lincRNA +chr1 52150329 52150412 + ENSG00000281172.1 AL139156.1 miRNA +chr1 53069938 53085502 - ENSG00000232993.1 RP11-334A14.5 antisense +chr1 53073110 53073389 - ENSG00000227644.2 HIGD1AP11 processed_pseudogene +chr1 54099968 54100224 - ENSG00000279049.1 AL353898.1 pseudogene +chr1 54980950 54992274 - ENSG00000233271.1 RP11-12C17.2 antisense +chr1 62211557 62211666 + ENSG00000200174.1 Y_RNA misc_RNA +chr1 63548977 63549112 - ENSG00000276884.1 DLEU2_6 misc_RNA +chr1 63549133 63549216 - ENSG00000278287.1 DLEU2_5 misc_RNA +chr1 63549227 63549284 - ENSG00000277565.1 DLEU2_4 misc_RNA +chr1 63549294 63549366 - ENSG00000275823.1 DLEU2_3 misc_RNA +chr1 63549374 63549463 - ENSG00000277689.1 DLEU2_2 misc_RNA +chr1 63549489 63549608 - ENSG00000274199.1 DLEU2_1 misc_RNA +chr1 67320369 67395580 + ENSG00000281152.1 IL12RB2 protein_coding +chr1 75787072 75787150 + ENSG00000206620.1 SNORD45C snoRNA +chr1 75787889 75787972 + ENSG00000207241.1 SNORD45A snoRNA +chr1 75789477 75789548 + ENSG00000201487.1 SNORD45B snoRNA +chr1 81990753 81990806 + ENSG00000274207.1 AC113949.1 miRNA +chr1 89260582 89269754 + ENSG00000237568.1 RP4-620F22.2 antisense +chr1 92229256 92229339 - ENSG00000265543.1 AL451010.1 miRNA +chr1 92837289 92837383 + ENSG00000206680.1 SNORD21 snoRNA +chr1 98045242 98045351 - ENSG00000276280.1 MIR2682 miRNA +chr1 98046070 98046171 - ENSG00000277990.1 MIR137 miRNA +chr1 100894928 100895356 + ENSG00000273204.1 RP4-549L20.3 antisense +chr1 103569553 103570674 + ENSG00000236085.1 ACTG1P4 processed_pseudogene +chr1 109100193 109100612 + ENSG00000278249.1 SCARNA2 scaRNA +chr1 109539906 109543837 - ENSG00000254942.1 RP5-1160K1.8 antisense +chr1 109596225 109597781 + ENSG00000225113.1 RP5-1160K1.3 sense_overlapping +chr1 109598893 109598967 + ENSG00000207709.2 MIR197 miRNA +chr1 109628417 109630305 - ENSG00000228703.1 RP5-1160K1.6 antisense +chr1 110456505 110457354 - ENSG00000270380.1 RP11-470L19.5 antisense +chr1 111181374 111181491 - ENSG00000272982.1 RP5-1180E21.4 antisense +chr1 111184415 111185061 - ENSG00000273221.1 RP5-1180E21.5 antisense +chr1 113125321 113126883 - ENSG00000237278.2 RLIMP2 processed_pseudogene +chr1 145281116 145281279 + ENSG00000207501.1 RNVU1-14 snRNA +chr1 145961388 145964422 + ENSG00000278431.1 CH17-270A2.1 antisense +chr1 147757185 147758434 + ENSG00000274415.1 RP11-433J22.2 antisense +chr1 148295792 148297271 - ENSG00000244252.1 RP11-495P10.7 lincRNA +chr1 149842355 149842495 + ENSG00000281134.1 AC239868.3 miRNA +chr1 149845816 149846486 + ENSG00000272993.1 RP11-196G18.24 lincRNA +chr1 149851317 149851457 - ENSG00000280874.1 AC239868.2 miRNA +chr1 149887178 149887318 - ENSG00000280566.1 AC239868.1 miRNA +chr1 150965245 150966256 + ENSG00000259357.2 RP11-316M1.12 antisense +chr1 151340648 151341966 + ENSG00000224645.1 RP11-126K1.8 antisense +chr1 151765709 151766389 + ENSG00000232937.1 RP11-98D18.2 sense_intronic +chr1 153772371 153774079 - ENSG00000279767.1 AL513523.2 protein_coding +chr1 154480012 154481501 + ENSG00000273110.1 RP11-350G8.9 antisense +chr1 154579065 154579663 - ENSG00000233875.1 RP11-61L14.6 antisense +chr1 155211151 155213819 - ENSG00000236263.1 RP11-263K19.6 antisense +chr1 155925958 155926085 - ENSG00000280466.1 SCARNA15 scaRNA +chr1 156077373 156077454 + ENSG00000222611.1 AL355388.1 miRNA +chr1 158578919 158579899 - ENSG00000186400.3 OR10X1 protein_coding +chr1 158578919 158579899 - ENSG00000279111.1 OR10X1 polymorphic_pseudogene +chr1 160205377 160205464 + ENSG00000265381.1 AL121987.1 miRNA +chr1 161364731 161367874 - ENSG00000188931.3 CFAP126 protein_coding +chr1 165662585 165662687 - ENSG00000206990.1 Y_RNA misc_RNA +chr1 168245565 168247343 - ENSG00000214262.4 ANKRD36BP1 transcribed_processed_pseudogene +chr1 170370213 170370295 - ENSG00000263384.1 AL354732.1 miRNA +chr1 171345105 171345307 - ENSG00000268062.1 TOP1P1 processed_pseudogene +chr1 172138798 172138907 - ENSG00000207949.1 MIR214 miRNA +chr1 178479247 178482365 - ENSG00000279210.1 RP4-593C16.4 antisense +chr1 182944402 182944454 - ENSG00000281615.1 AL450304.2 miRNA +chr1 182959485 182959575 - ENSG00000264768.1 AL450304.1 miRNA +chr1 186311825 186311928 - ENSG00000202025.1 RNU6-1240P snRNA +chr1 201464383 201465146 - ENSG00000224818.1 RP11-134G8.10 3prime_overlapping_ncrna +chr1 201520056 201520549 + ENSG00000242150.2 RP11-134G8.6 transcribed_processed_pseudogene +chr1 202873294 202874326 + ENSG00000243113.1 RP11-480I12.9 transcribed_processed_pseudogene +chr1 204131062 204131966 + ENSG00000261065.1 RP11-74C13.4 antisense +chr1 207801845 207801956 - ENSG00000275668.1 AL035209.1 miRNA +chr1 207802440 207802523 - ENSG00000276752.1 MIR29B2 miRNA +chr1 210678315 210681932 + ENSG00000279333.1 RP11-75I2.3 TEC +chr1 211492255 211492917 + ENSG00000223649.1 RP11-359E8.3 lincRNA +chr1 212853280 212853426 + ENSG00000235182.1 RP11-348H3.4 processed_pseudogene +chr1 218442626 218443996 + ENSG00000281453.1 TGFB2-OT1 3prime_overlapping_ncrna +chr1 220571834 220571899 - ENSG00000281158.1 AC096640.1 miRNA +chr1 220825776 220825893 + ENSG00000276642.1 U6atac snRNA +chr1 225922080 225922142 - ENSG00000274674.1 MIR6741 miRNA +chr1 226992140 226993206 + ENSG00000233706.1 RP5-1087E8.3 antisense +chr1 227430526 227430976 + ENSG00000242757.1 CTD-2090I13.3 processed_pseudogene +chr1 228097263 228097341 + ENSG00000264944.1 MIR3620 miRNA +chr1 228394290 228396967 + ENSG00000270094.1 RP11-245P10.8 antisense +chr1 228397048 228397109 - ENSG00000278067.1 MIR6742 miRNA +chr1 228457435 228457572 + ENSG00000281451.1 AL139288.1 miRNA +chr1 228628176 228628234 - ENSG00000281588.1 AL713899.1 miRNA +chr1 229304857 229305504 + ENSG00000213029.3 SPHAR protein_coding +chr1 229440284 229441020 - ENSG00000226920.1 RP5-1068B5.5 3prime_overlapping_ncrna +chr1 230280312 230281893 - ENSG00000224407.1 RP5-956O18.3 antisense +chr1 231019828 231019924 - ENSG00000221290.1 MIR1182 miRNA +chr1 232223059 232223141 + ENSG00000281475.1 BX323014.1 miRNA +chr1 234607008 234609483 + ENSG00000228830.1 RP4-781K5.2 antisense +chr1 236483165 236484468 + ENSG00000244457.2 ENO1P1 transcribed_processed_pseudogene +chr1 237926831 237927605 + ENSG00000243781.1 RP11-193H5.2 transcribed_processed_pseudogene +chr1 245123471 245124450 - ENSG00000223353.2 RP11-290P14.2 processed_pseudogene +chr1 245749563 246355081 - ENSG00000280657.1 SMYD3 protein_coding +chr1 247201967 247202060 - ENSG00000263568.1 MIR3916 miRNA +chr1 247948858 247949796 + ENSG00000196936.3 OR2L8 protein_coding +chr1 247948858 247949796 + ENSG00000279263.1 OR2L8 polymorphic_pseudogene +chr1 248626178 248627128 - ENSG00000183130.3 OR2T11 protein_coding +chr1 248721993 248722201 - ENSG00000242529.1 AHCYP8 processed_pseudogene +chr1 248826377 248826443 + ENSG00000264500.1 MIR3124 miRNA +chr2 10691538 10691831 + ENSG00000277446.1 Metazoa_SRP misc_RNA +chr2 20401650 20401706 - ENSG00000281337.1 AC007041.1 miRNA +chr2 20678254 20678932 - ENSG00000270100.1 RP11-130L8.1 lincRNA +chr2 27581889 27581946 - ENSG00000221531.1 AC074091.1 miRNA +chr2 28308161 28308570 + ENSG00000225991.1 RP11-731I19.1 processed_pseudogene +chr2 31823018 31823106 - ENSG00000265267.1 AL121652.3 miRNA +chr2 44935294 44935368 + ENSG00000276229.1 Six3os1_3 misc_RNA +chr2 44938833 44939028 + ENSG00000274547.1 Six3os1_6 misc_RNA +chr2 51027953 51028097 + ENSG00000281171.1 AC007682.4 miRNA +chr2 54079974 54080280 - ENSG00000241114.1 AC008280.3 processed_pseudogene +chr2 60925909 60931610 + ENSG00000267520.2 RP11-373L24.1 3prime_overlapping_ncrna +chr2 61177554 61177636 + ENSG00000280672.1 AC016747.1 miRNA +chr2 62146413 62147153 + ENSG00000242735.1 AC018462.3 processed_pseudogene +chr2 64817586 64817668 + ENSG00000280945.1 AC007880.2 miRNA +chr2 65667256 65667346 + ENSG00000265899.1 AC007389.4 miRNA +chr2 68179833 68180532 + ENSG00000273275.1 RP11-474G23.2 antisense +chr2 70301451 70302072 + ENSG00000233849.1 AC022201.5 antisense +chr2 71379755 71379858 - ENSG00000200779.1 RNU6-105P snRNA +chr2 82268612 82268706 + ENSG00000252897.1 RNU6-685P snRNA +chr2 85567662 85567737 - ENSG00000280656.1 AC016753.1 miRNA +chr2 88860886 88860922 - ENSG00000211594.2 IGKJ4 IG_J_gene +chr2 88861221 88861258 - ENSG00000211595.2 IGKJ3 IG_J_gene +chr2 88861525 88861563 - ENSG00000211596.3 IGKJ2 IG_J_gene +chr2 88861886 88861923 - ENSG00000211597.2 IGKJ1 IG_J_gene +chr2 95413456 95414296 - ENSG00000248821.1 AC009238.6 unprocessed_pseudogene +chr2 96809473 96809614 + ENSG00000280510.1 AC092636.2 miRNA +chr2 110126732 110126824 - ENSG00000212091.1 AC013268.1 miRNA +chr2 113596000 113596067 + ENSG00000276624.1 AL078621.1 miRNA +chr2 127701508 127705242 + ENSG00000173349.5 SFT2D3 protein_coding +chr2 127845236 127845341 + ENSG00000202532.1 RNU6-395P snRNA +chr2 127846736 127847084 - ENSG00000244563.1 AC006011.4 processed_pseudogene +chr2 130929762 130929883 - ENSG00000281159.1 SCARNA15 scaRNA +chr2 131491160 131491236 - ENSG00000265575.1 MIR4784 miRNA +chr2 132152243 132152349 - ENSG00000239108.1 RNU6-1132P snRNA +chr2 144518447 144518574 + ENSG00000275372.1 ZEB2_AS1_1 misc_RNA +chr2 144520456 144520555 + ENSG00000273537.1 ZEB2_AS1_3 misc_RNA +chr2 144521039 144521116 + ENSG00000277444.1 ZEB2_AS1_4 misc_RNA +chr2 159462417 159463256 - ENSG00000225369.1 AC009506.2 processed_pseudogene +chr2 160407810 160407882 - ENSG00000263948.1 MIR4785 miRNA +chr2 161422659 161423577 - ENSG00000224076.4 AC009487.4 antisense +chr2 175176493 175176586 - ENSG00000200121.2 Y_RNA misc_RNA +chr2 175184215 175184607 + ENSG00000233131.1 AC096649.1 processed_pseudogene +chr2 176188843 176188901 + ENSG00000277284.1 MIR7704 miRNA +chr2 176270241 176270330 - ENSG00000264392.2 AC016739.3 miRNA +chr2 177212726 177212799 + ENSG00000263721.1 MIR4444-1 miRNA +chr2 178831371 178831449 - ENSG00000238542.1 RNU7-104P snRNA +chr2 179934402 179934527 - ENSG00000202216.2 SNORA17 snoRNA +chr2 182314454 182314536 + ENSG00000281257.1 AC012500.1 miRNA +chr2 182788098 182788435 + ENSG00000232430.1 RPL31P15 processed_pseudogene +chr2 188974419 188974555 + ENSG00000281204.1 AC066694.1 miRNA +chr2 189311671 189311761 - ENSG00000266817.1 AC118063.1 miRNA +chr2 190880854 190880942 + ENSG00000280517.1 AC005540.1 miRNA +chr2 192775943 192776073 + ENSG00000278406.1 PCGEM1 misc_RNA +chr2 201166965 201167546 + ENSG00000234431.2 AC007283.5 3prime_overlapping_ncrna +chr2 201621646 201623430 - ENSG00000241790.2 ENO1P4 processed_pseudogene +chr2 202115167 202115260 - ENSG00000274633.1 AC079354.1 miRNA +chr2 202333642 202333724 + ENSG00000281619.1 AC064836.1 miRNA +chr2 202773720 202774360 - ENSG00000240761.1 AC098831.4 processed_pseudogene +chr2 202840949 202841082 + ENSG00000281423.1 AC010900.1 miRNA +chr2 203190780 203191277 + ENSG00000204196.5 AC011737.2 processed_pseudogene +chr2 203764707 203764798 - ENSG00000211573.2 AC125238.1 miRNA +chr2 206115547 206122323 + ENSG00000231955.1 AC007383.4 antisense +chr2 206116110 206116500 - ENSG00000237580.1 GCSHP3 processed_pseudogene +chr2 206160843 206161024 + ENSG00000277502.1 uc_338 misc_RNA +chr2 206162228 206162359 + ENSG00000207406.1 SNORA41 snoRNA +chr2 206259628 206259918 - ENSG00000224070.1 HMGN1P6 processed_pseudogene +chr2 207753872 207754435 - ENSG00000272851.1 RP11-801F7.1 antisense +chr2 207754807 207754881 + ENSG00000264900.1 MIR4775 miRNA +chr2 218280125 218280188 - ENSG00000274203.1 MIR6513 miRNA +chr2 230176665 230221721 - ENSG00000280755.1 SP110 protein_coding +chr2 230908852 230910102 + ENSG00000230385.1 AC012507.4 antisense +chr2 231456444 231456523 - ENSG00000207280.1 SNORD20 snoRNA +chr2 231711525 231711647 + ENSG00000277986.1 U4 snRNA +chr2 231810348 231810844 - ENSG00000260622.1 RP11-690I21.3 processed_pseudogene +chr2 232550474 232550573 - ENSG00000266620.1 MIR5001 miRNA +chr2 233865496 233867359 - ENSG00000279809.1 AC005538.3 TEC +chr2 239091759 239091836 - ENSG00000281838.1 AC017028.12 miRNA +chr3 8931506 8931631 + ENSG00000199815.2 SNORA17 snoRNA +chr3 10278938 10279024 - ENSG00000273665.1 AC022384.2 miRNA +chr3 12071038 12071121 + ENSG00000265870.1 AC026166.1 miRNA +chr3 12840294 12840396 - ENSG00000281117.1 AC034198.1 miRNA +chr3 12840312 12840450 - ENSG00000207496.1 SNORA7A snoRNA +chr3 12850659 12850860 + ENSG00000250939.2 AC034198.7 transcribed_unprocessed_pseudogene +chr3 15738657 15738718 + ENSG00000281814.1 AC090950.1 miRNA +chr3 16933196 16933260 + ENSG00000264818.1 MIR3714 miRNA +chr3 24096512 24097360 - ENSG00000242109.1 NPM1P23 transcribed_processed_pseudogene +chr3 30304321 30304536 - ENSG00000281710.1 U3 snoRNA +chr3 32259728 32259819 + ENSG00000207857.2 AC097639.1 miRNA +chr3 33144104 33147721 - ENSG00000272149.1 RP11-627J17.1 antisense +chr3 38125292 38125394 - ENSG00000201965.1 Y_RNA misc_RNA +chr3 39408389 39408539 + ENSG00000206760.1 SNORA6 snoRNA +chr3 39411054 39411206 + ENSG00000202363.1 SNORA62 snoRNA +chr3 44629284 44629372 + ENSG00000280942.1 AC099669.1 miRNA +chr3 44861888 44861981 + ENSG00000207783.1 MIR564 miRNA +chr3 48094801 48094876 - ENSG00000281068.1 AC124916.1 miRNA +chr3 48094888 48094957 - ENSG00000281238.1 AC124916.2 miRNA +chr3 48465811 48467645 + ENSG00000213689.8 TREX1 protein_coding +chr3 48633636 48633698 - ENSG00000274831.1 MIR6824 miRNA +chr3 48985485 48985963 - ENSG00000273211.1 RP13-131K19.7 lincRNA +chr3 49099854 49099914 - ENSG00000274888.1 MIR6890 miRNA +chr3 49270132 49270239 + ENSG00000199546.1 Y_RNA misc_RNA +chr3 49274120 49274186 + ENSG00000264633.1 MIR4271 miRNA +chr3 49806137 49806245 - ENSG00000263506.1 MIR5193 miRNA +chr3 49863381 49863464 - ENSG00000281278.1 AC139451.2 miRNA +chr3 50273236 50273297 + ENSG00000274596.1 MIR6872 miRNA +chr3 52690744 52690827 + ENSG00000238862.1 SNORD19B snoRNA +chr3 54639681 54639748 + ENSG00000276927.1 AC092057.1 miRNA +chr3 60617805 60617870 - ENSG00000281426.1 MIR548BB miRNA +chr3 64011964 64016246 + ENSG00000243410.1 RP11-245J9.4 antisense +chr3 64099273 64101122 + ENSG00000241572.1 PRICKLE2-AS1 antisense +chr3 75738280 75738363 + ENSG00000266396.1 MIR4273 miRNA +chr3 87323969 87324095 - ENSG00000280503.1 AC130885.1 miRNA +chr3 98264285 98265262 + ENSG00000230301.4 OR5H6 protein_coding +chr3 98264285 98265262 + ENSG00000279922.1 OR5H6 polymorphic_pseudogene +chr3 99691480 99691571 - ENSG00000263810.1 AC055723.1 miRNA +chr3 101823793 101824998 - ENSG00000249474.1 RP11-49I4.3 antisense +chr3 116716460 116716624 + ENSG00000278072.1 AC108713.1 misc_RNA +chr3 123161794 123161879 + ENSG00000275891.1 MIR7110 miRNA +chr3 123283593 123283983 + ENSG00000272678.1 RP11-797D24.4 antisense +chr3 124723788 124726325 + ENSG00000260391.2 RP11-71H17.7 sense_overlapping +chr3 124792319 124792562 - ENSG00000276626.1 7SK misc_RNA +chr3 126571789 126572636 - ENSG00000206483.5 TXNRD3NB protein_coding +chr3 128673691 128673771 - ENSG00000280957.1 AC079945.1 miRNA +chr3 134437827 134437906 + ENSG00000263554.1 MIR4788 miRNA +chr3 138102085 138102222 + ENSG00000281378.1 AC023049.1 miRNA +chr3 139233414 139233520 + ENSG00000276304.1 PISRT1 misc_RNA +chr3 139494618 139494701 + ENSG00000263538.1 AC097103.1 miRNA +chr3 142450102 142452149 + ENSG00000242479.1 RP11-383G6.4 processed_pseudogene +chr3 147386967 147387453 + ENSG00000241202.1 ZIC4-AS1 antisense +chr3 149766814 149766883 + ENSG00000281611.1 AC069216.1 miRNA +chr3 149779009 149779108 - ENSG00000251854.1 RNU6-507P snRNA +chr3 151079506 151079584 + ENSG00000276055.1 CLRN1-AS1 misc_RNA +chr3 157153548 157153640 + ENSG00000201778.1 Y_RNA misc_RNA +chr3 169483709 169483946 + ENSG00000281137.1 AC074033.1 protein_coding +chr3 169764610 169765047 - ENSG00000277925.1 Telomerase-vert misc_RNA +chr3 169793495 169793966 + ENSG00000270135.1 RP11-362K14.7 antisense +chr3 169794962 169796213 + ENSG00000270096.1 RP11-362K14.6 antisense +chr3 169945987 169946754 - ENSG00000244193.1 RP11-379K17.5 transcribed_processed_pseudogene +chr3 170087810 170089590 + ENSG00000268220.1 RP11-379K17.12 antisense +chr3 170496131 170496263 - ENSG00000281375.1 AC008041.1 miRNA +chr3 179396961 179399191 + ENSG00000242539.2 AC007620.3 antisense +chr3 181610498 181610729 + ENSG00000276074.1 SOX2OT_exon1 misc_RNA +chr3 181699608 181699883 + ENSG00000276690.1 SOX2OT_exon3 misc_RNA +chr3 181699705 181699783 + ENSG00000281596.1 AC117415.1 miRNA +chr3 183453814 183453944 + ENSG00000199363.1 SNORA63 snoRNA +chr3 183802475 183802553 - ENSG00000216166.1 AC131160.1 miRNA +chr3 186784796 186784864 + ENSG00000238942.1 SNORD2 snoRNA +chr3 186786323 186786445 + ENSG00000200418.1 SNORA63 snoRNA +chr3 186786672 186786777 + ENSG00000281017.1 MIR1248 miRNA +chr3 186786675 186786852 + ENSG00000221420.2 SNORA81 snoRNA +chr3 186787300 186787431 + ENSG00000200320.1 SNORA63 snoRNA +chr3 186787612 186787749 + ENSG00000263776.1 SNORA4 snoRNA +chr3 190659216 190659750 + ENSG00000273370.1 RP11-268E23.2 lincRNA +chr3 195658096 195685904 + ENSG00000215837.7 SDHAP2 transcribed_unprocessed_pseudogene +chr3 195688008 195688120 + ENSG00000276635.1 AC233280.3 miRNA +chr3 197674496 197674576 - ENSG00000216042.1 MIR922 miRNA +chr4 1986384 1986477 - ENSG00000216105.1 MIR943 miRNA +chr4 2250077 2250156 - ENSG00000265080.1 MIR4800 miRNA +chr4 13627442 13627591 + ENSG00000281620.1 AC006445.1 protein_coding +chr4 16256308 16256555 - ENSG00000242358.1 RPS21P4 processed_pseudogene +chr4 38089944 38090036 - ENSG00000280678.1 AC108933.1 miRNA +chr4 44448005 44448110 + ENSG00000266496.1 AC131951.1 miRNA +chr4 44704405 44704965 + ENSG00000272936.1 RP11-700J17.2 antisense +chr4 56097422 56097481 + ENSG00000280464.1 AC092627.1 miRNA +chr4 56794354 56794438 - ENSG00000281241.1 AC022483.1 miRNA +chr4 69215908 69216635 - ENSG00000268803.1 RP11-704M14.2 unprocessed_pseudogene +chr4 88275205 88275308 - ENSG00000200469.1 RNU6-112P snRNA +chr4 88521573 88521789 - ENSG00000255072.1 PIGY protein_coding +chr4 88710147 88710265 + ENSG00000278151.1 FAM13A-AS1_1 misc_RNA +chr4 98929914 98929993 - ENSG00000238449.2 AC019131.1 miRNA +chr4 104490876 104490954 + ENSG00000272082.1 AC093628.1 miRNA +chr4 105679050 105680094 - ENSG00000248778.1 RP11-311D14.1 processed_pseudogene +chr4 108789200 108789262 - ENSG00000265522.1 AC097473.1 miRNA +chr4 118279190 118279320 + ENSG00000275994.1 SNORA24 snoRNA +chr4 122827014 122827090 + ENSG00000253069.1 AC021205.1 miRNA +chr4 135371590 135371681 - ENSG00000207849.2 AC108867.1 miRNA +chr4 137601899 137602433 - ENSG00000280352.1 RP13-884E18.3 TEC +chr4 143555082 143555583 - ENSG00000248924.2 RP11-481K16.2 transcribed_processed_pseudogene +chr4 144739762 144739941 - ENSG00000273621.1 uc_338 misc_RNA +chr4 146639261 146639343 + ENSG00000264323.1 AC093887.1 miRNA +chr4 151103827 151103891 + ENSG00000208797.1 SNORD73A snoRNA +chr4 152536428 152536516 + ENSG00000277685.1 MIR4453 miRNA +chr4 158199105 158200442 - ENSG00000250604.1 RP11-597D13.8 antisense +chr4 183318194 183320774 - ENSG00000177300.6 CLDN22 protein_coding +chr4 190065233 190065914 + ENSG00000277162.1 DBET processed_pseudogene +chr4 190175141 190175224 + ENSG00000274222.1 AC215524.1 miRNA +chr5 3596211 3600188 - ENSG00000259603.1 CTD-2012M11.3 antisense +chr5 8460925 8460999 + ENSG00000273868.1 MIR4458 miRNA +chr5 10195187 10197622 - ENSG00000271998.1 CTD-2199O4.7 lincRNA +chr5 10652211 10655925 - ENSG00000251196.1 RP11-54F2.1 unprocessed_pseudogene +chr5 18958153 18958237 - ENSG00000281138.1 AC114981.1 miRNA +chr5 31249879 31250200 + ENSG00000250482.2 RP11-152K4.1 processed_pseudogene +chr5 32379407 32379467 - ENSG00000222961.1 AC008949.1 miRNA +chr5 38557502 38557561 - ENSG00000265304.1 MIR3650 miRNA +chr5 42806394 42806997 + ENSG00000272234.1 CTD-2325A15.5 antisense +chr5 52903908 52904478 + ENSG00000241809.1 CTD-2207L17.1 processed_pseudogene +chr5 55936143 55941727 + ENSG00000262211.1 CTD-2031P19.5 antisense +chr5 57481820 57481903 - ENSG00000264748.1 AC025470.1 miRNA +chr5 60487713 60487929 + ENSG00000273701.1 PART1_1 misc_RNA +chr5 60488078 60488327 + ENSG00000275634.1 PART1_2 misc_RNA +chr5 60546219 60546349 + ENSG00000276233.1 PART1_3 misc_RNA +chr5 69160808 69160939 + ENSG00000280894.1 SNORA76 snoRNA +chr5 73446357 73446984 + ENSG00000247993.2 FOXD1-AS1 lincRNA +chr5 74779309 74779413 + ENSG00000199645.1 RNU6-1330P snRNA +chr5 75598482 75599380 - ENSG00000248881.1 CTC-366B18.2 antisense +chr5 77073881 77074520 + ENSG00000250615.1 CTC-564N23.2 antisense +chr5 88666853 88666939 - ENSG00000273878.1 MIR9-2 miRNA +chr5 88692651 88692859 + ENSG00000250555.2 CTC-467M3.2 antisense +chr5 91313057 91314402 - ENSG00000271762.1 RP11-213H15.4 lincRNA +chr5 91844022 91844116 - ENSG00000276426.1 uc_338 misc_RNA +chr5 92405941 92406044 - ENSG00000264489.2 AC120120.1 miRNA +chr5 93620696 93620788 - ENSG00000251725.1 MIR2277 miRNA +chr5 100050365 100050438 + ENSG00000264839.1 AC113407.1 miRNA +chr5 122478662 122478729 + ENSG00000277169.1 AC022101.1 miRNA +chr5 131427266 131635030 - ENSG00000281164.1 RAPGEF6 protein_coding +chr5 132488382 132488702 + ENSG00000277192.1 RP11-89G4.1 antisense +chr5 134928039 134928112 + ENSG00000263963.1 MIR4461 miRNA +chr5 136080497 136080597 - ENSG00000278815.1 VTRNA2-1 misc_RNA +chr5 136129516 136129781 + ENSG00000277859.1 SMAD5-AS1_1 misc_RNA +chr5 136133696 136133826 + ENSG00000275646.1 SMAD5-AS1_2 misc_RNA +chr5 136133912 136134035 + ENSG00000277524.1 SMAD5-AS1_3 misc_RNA +chr5 136134082 136134248 + ENSG00000274934.1 SMAD5-AS1_4 misc_RNA +chr5 138347027 138349641 - ENSG00000249971.1 RP11-256P1.1 antisense +chr5 139364677 139369717 - ENSG00000272742.1 CTB-43P18.1 antisense +chr5 140563671 140563751 - ENSG00000274910.1 MIR6831 miRNA +chr5 140670794 140673586 - ENSG00000256453.1 DND1 protein_coding +chr5 140849105 140849696 - ENSG00000278907.1 AC005609.19 antisense +chr5 140861224 140863521 + ENSG00000249504.3 PCDHA14 transcribed_unprocessed_pseudogene +chr5 140867513 140867959 - ENSG00000278946.1 AC005609.20 antisense +chr5 140875346 140875922 - ENSG00000278915.1 AC005609.18 antisense +chr5 141350109 141350662 - ENSG00000280026.1 AC005618.8 antisense +chr5 141427295 141427752 - ENSG00000279855.1 AC005618.9 antisense +chr5 141479535 141479617 + ENSG00000281646.1 AC008781.1 miRNA +chr5 142317830 142317920 + ENSG00000277968.1 SPRY4-IT1_1 misc_RNA +chr5 142318047 142318167 + ENSG00000274721.1 SPRY4-IT1_2 misc_RNA +chr5 149425771 149428289 - ENSG00000275871.1 RP11-394O4.6 lincRNA +chr5 149430646 149430733 + ENSG00000276365.1 MIR145 miRNA +chr5 150670658 150672390 - ENSG00000250309.2 CTC-345K18.2 antisense +chr5 155845469 155845527 + ENSG00000280546.1 AC140677.1 miRNA +chr5 160485352 160485450 + ENSG00000277727.1 MIR146A miRNA +chr5 164601002 164601452 - ENSG00000253600.1 CTC-340A15.1 processed_pseudogene +chr5 168552277 168553727 - ENSG00000253861.1 SLC2A3P1 processed_pseudogene +chr5 168791498 168791610 + ENSG00000202345.1 Y_RNA misc_RNA +chr5 170767384 170767451 + ENSG00000276554.1 AC008514.1 miRNA +chr5 178884715 178884879 + ENSG00000206624.1 RNU1-39P snRNA +chr5 179082680 179083194 - ENSG00000253144.1 RP11-281O15.7 processed_pseudogene +chr5 181222566 181222633 - ENSG00000264732.1 MIR4638 miRNA +chr5 181224646 181230685 - ENSG00000247049.2 CTC-338M12.7 antisense +chr5 181241814 181241892 - ENSG00000272296.1 SNORD96A snoRNA +chr5 181243312 181243379 - ENSG00000264549.1 SNORD95 snoRNA +chr6 1390314 1390411 - ENSG00000275859.1 MIR6720 miRNA +chr6 3023142 3023772 - ENSG00000271361.1 HTATSF1P2 processed_pseudogene +chr6 3138394 3153062 - ENSG00000228170.1 RP1-40E16.11 antisense +chr6 6347081 6347381 - ENSG00000241216.1 SNAPC5P1 transcribed_processed_pseudogene +chr6 8653558 8653797 + ENSG00000276019.1 HULC misc_RNA +chr6 13614111 13615155 - ENSG00000261071.1 RP1-223E5.4 antisense +chr6 16301693 16301824 - ENSG00000281447.1 AL009031.1 miRNA +chr6 20421686 20421749 - ENSG00000281428.1 AL136303.2 miRNA +chr6 24599052 24599184 - ENSG00000280713.1 AL512385.1 miRNA +chr6 24839967 24840065 - ENSG00000263391.1 AL512428.1 miRNA +chr6 25732635 25732774 - ENSG00000280964.1 AL512384.1 miRNA +chr6 26124436 26124576 - ENSG00000281052.1 U91328.1 miRNA +chr6 26198861 26198997 + ENSG00000281823.1 AL031777.2 miRNA +chr6 26217220 26217357 - ENSG00000280547.1 AL031777.1 miRNA +chr6 27808413 27808553 - ENSG00000281258.1 AL009179.1 miRNA +chr6 27814397 27814537 + ENSG00000280826.1 AL049822.1 miRNA +chr6 27837947 27838339 - ENSG00000275221.1 HIST1H2AK protein_coding +chr6 27837957 27838094 + ENSG00000281435.1 Z98744.1 miRNA +chr6 27865600 27865738 - ENSG00000281512.1 Z98744.2 miRNA +chr6 27892767 27892904 + ENSG00000281851.1 Z98744.3 miRNA +chr6 28977613 28977709 + ENSG00000280628.1 AL662791.1 miRNA +chr6 29396700 29397623 + ENSG00000168787.6 OR12D2 protein_coding +chr6 29440016 29440954 + ENSG00000279941.1 OR10C1 protein_coding +chr6 29726669 29727139 - ENSG00000239257.1 RPL23AP1 transcribed_processed_pseudogene +chr6 30035916 30035983 + ENSG00000278104.1 ZNRD1-AS1_1 misc_RNA +chr6 30058115 30058190 + ENSG00000275856.1 ZNRD1-AS1_2 misc_RNA +chr6 30061080 30061183 + ENSG00000278773.1 ZNRD1-AS1_3 misc_RNA +chr6 30684796 30684892 + ENSG00000277346.1 AL662797.1 miRNA +chr6 30890883 30890972 + ENSG00000264594.1 MIR4640 miRNA +chr6 31532757 31532869 - ENSG00000276877.1 AL662801.1 miRNA +chr6 31541101 31541178 - ENSG00000265236.1 SNORD84 snoRNA +chr6 31658329 31660721 + ENSG00000227198.1 C6orf47-AS1 antisense +chr6 31837076 31837142 + ENSG00000201754.1 SNORD52 snoRNA +chr6 31956839 31956940 - ENSG00000221267.1 MIR1236 miRNA +chr6 32936916 32937010 - ENSG00000212066.1 AL645941.1 miRNA +chr6 32972065 32972853 - ENSG00000263756.1 XXbac-BPG181M17.6 antisense +chr6 33290245 33290325 + ENSG00000275010.1 MIR6834 miRNA +chr6 33698128 33698234 + ENSG00000266509.1 MIR3934 miRNA +chr6 34873831 34873927 + ENSG00000252106.2 RNY3P15 misc_RNA +chr6 40392730 40392874 + ENSG00000280824.1 AL591063.1 miRNA +chr6 41787662 41789898 + ENSG00000214736.6 TOMM6 protein_coding +chr6 41791410 41791477 + ENSG00000268745.1 RP11-298J23.9 antisense +chr6 42155426 42163439 + ENSG00000214732.2 RP1-139D8.6 protein_coding +chr6 43213801 43223860 - ENSG00000245261.1 RP3-330M21.5 antisense +chr6 43770429 43770616 - ENSG00000272114.1 RP1-261G23.7 antisense +chr6 44254206 44254285 - ENSG00000265700.1 MIR4647 miRNA +chr6 53090961 53091257 + ENSG00000242865.3 RN7SL244P misc_RNA +chr6 56432379 56432442 - ENSG00000266793.1 AL137008.1 miRNA +chr6 71585089 71585201 + ENSG00000211530.1 AL354933.1 miRNA +chr6 73263008 73263084 + ENSG00000263378.1 AC019205.1 miRNA +chr6 85677294 85677368 - ENSG00000281147.1 SNORD50A snoRNA +chr6 85677589 85677658 - ENSG00000275072.1 SNORD50B snoRNA +chr6 88276125 88276208 - ENSG00000281199.1 AL139042.1 miRNA +chr6 110440082 110440165 - ENSG00000281088.1 AC002464.1 miRNA +chr6 112361848 112361939 - ENSG00000266485.1 AL365214.1 miRNA +chr6 113428797 113428886 + ENSG00000280723.1 AL021326.1 miRNA +chr6 116244187 116244728 - ENSG00000236326.1 RP3-486I3.5 antisense +chr6 116457732 116457822 - ENSG00000265516.1 Z84488.1 miRNA +chr6 125979812 125979934 - ENSG00000251920.1 RNA5SP216 rRNA +chr6 136034553 136034886 - ENSG00000213111.5 COX5BP2 transcribed_processed_pseudogene +chr6 136343193 136343249 - ENSG00000276943.1 AL023284.1 miRNA +chr6 144007227 144007464 + ENSG00000276680.1 HYMAI misc_RNA +chr6 145736911 145737173 - ENSG00000270828.1 RP3-466P17.2 lincRNA +chr6 158609707 158609790 + ENSG00000278571.1 MIR7161 miRNA +chr6 158764661 158764753 - ENSG00000265558.1 MIR3918 miRNA +chr6 159785594 159785733 - ENSG00000206910.1 SNORA29 snoRNA +chr6 166099853 166099924 + ENSG00000276643.1 SNORD45 snoRNA +chr7 1055360 1059261 - ENSG00000257607.1 RP11-449P15.1 antisense +chr7 2257515 2257577 - ENSG00000277102.1 MIR6836 miRNA +chr7 4788565 4788639 - ENSG00000264474.1 MIR4656 miRNA +chr7 5528103 5528186 - ENSG00000263900.1 AC006483.1 miRNA +chr7 6578565 6588974 - ENSG00000232581.1 AC079742.4 antisense +chr7 6691977 6692059 + ENSG00000265245.1 AC073343.1 miRNA +chr7 7742091 7742535 - ENSG00000269721.1 RPL23AP51 transcribed_processed_pseudogene +chr7 9084022 9084175 + ENSG00000271526.1 RP4-668E10.2 processed_pseudogene +chr7 12654179 12654985 + ENSG00000229233.1 CTD-2320J21.2 sense_overlapping +chr7 19719388 19719451 + ENSG00000221576.2 AC004543.1 miRNA +chr7 27096124 27096248 + ENSG00000276528.1 HOTAIRM1_1 misc_RNA +chr7 27098900 27099114 + ENSG00000276771.1 HOTAIRM1_2 misc_RNA +chr7 27099778 27099836 + ENSG00000274864.1 HOTAIRM1_3 misc_RNA +chr7 27099856 27099957 + ENSG00000274396.1 HOTAIRM1_4 misc_RNA +chr7 27099967 27100111 + ENSG00000277694.1 HOTAIRM1_5 misc_RNA +chr7 27169480 27169564 - ENSG00000207584.1 MIR196B miRNA +chr7 27185433 27185530 + ENSG00000273961.1 HOXA11-AS1_1 misc_RNA +chr7 27185832 27186018 + ENSG00000278334.1 HOXA11-AS1_2 misc_RNA +chr7 27186166 27186263 + ENSG00000276496.1 HOXA11-AS1_3 misc_RNA +chr7 27188816 27188994 + ENSG00000278020.1 HOXA11-AS1_6 misc_RNA +chr7 27200465 27200521 + ENSG00000276609.1 HOTTIP_1 misc_RNA +chr7 27201844 27202219 + ENSG00000278708.1 HOTTIP_2 misc_RNA +chr7 27202302 27202638 + ENSG00000277469.1 HOTTIP_3 misc_RNA +chr7 27206139 27206303 + ENSG00000277553.1 HOTTIP_4 misc_RNA +chr7 30157531 30159534 + ENSG00000251660.1 AC007036.5 sense_overlapping +chr7 30424672 30425412 + ENSG00000272638.1 GS1-114I9.1 antisense +chr7 30550217 30551569 + ENSG00000263683.1 RP4-777O23.1 lincRNA +chr7 38655893 38656025 - ENSG00000281438.1 AC011309.1 miRNA +chr7 39609717 39610280 + ENSG00000106540.4 AC004837.3 processed_pseudogene +chr7 40128121 40128232 - ENSG00000199273.1 Y_RNA misc_RNA +chr7 42918741 42920084 + ENSG00000234983.1 AC010132.11 processed_pseudogene +chr7 44051766 44051829 + ENSG00000274083.1 MIR6837 miRNA +chr7 44062727 44065587 - ENSG00000164708.5 PGAM2 protein_coding +chr7 44064908 44066079 + ENSG00000239775.1 AC017116.11 sense_overlapping +chr7 44110849 44110912 + ENSG00000264652.1 MIR4649 miRNA +chr7 44367176 44367270 + ENSG00000280507.1 AC004453.1 miRNA +chr7 44881748 44881800 - ENSG00000264326.1 MIR4657 miRNA +chr7 44985378 44985510 - ENSG00000277184.1 SNORA9 snoRNA +chr7 45105968 45106099 - ENSG00000200656.1 SNORA5B snoRNA +chr7 63349154 63350059 - ENSG00000227545.1 RP5-905H7.10 processed_pseudogene +chr7 63398046 63398957 + ENSG00000234467.1 SLC25A1P2 processed_pseudogene +chr7 65038372 65038565 + ENSG00000239985.2 RP11-460N20.3 unprocessed_pseudogene +chr7 66980335 66980409 + ENSG00000280772.1 AC079920.1 miRNA +chr7 75237293 75237405 - ENSG00000275121.1 CH17-232I21.1 processed_pseudogene +chr7 75474707 75486108 - ENSG00000242073.2 AC006014.7 transcribed_unprocessed_pseudogene +chr7 75915197 75915269 + ENSG00000265020.1 MIR4651 miRNA +chr7 76968346 76968518 + ENSG00000236280.1 AC114737.3 processed_pseudogene +chr7 84939349 84940245 - ENSG00000232019.1 AC074183.4 lincRNA +chr7 87345082 87345233 + ENSG00000273623.1 TP53TG1_1 misc_RNA +chr7 87345305 87345486 + ENSG00000276185.1 TP53TG1_2 misc_RNA +chr7 90403434 90513391 + ENSG00000273299.1 CTB-13L3.1 processed_transcript +chr7 95156606 95156671 - ENSG00000277296.1 AC002429.1 miRNA +chr7 96965302 96965481 + ENSG00000274409.1 Evf1_1 misc_RNA +chr7 96965489 96965695 + ENSG00000277124.1 Evf1_2 misc_RNA +chr7 100352360 100353692 + ENSG00000235333.3 PVRIG2P transcribed_unprocessed_pseudogene +chr7 100356651 100356721 + ENSG00000278005.1 MIR6840 miRNA +chr7 100868036 100868107 + ENSG00000273985.1 MIR6875 miRNA +chr7 101058299 101058567 + ENSG00000222636.1 RN7SKP54 misc_RNA +chr7 102465742 102465826 + ENSG00000266715.1 MIR5090 miRNA +chr7 102471469 102471531 + ENSG00000264471.1 MIR4467 miRNA +chr7 105014152 105014199 - ENSG00000280574.1 AC007384.1 miRNA +chr7 106781600 106781715 - ENSG00000251978.1 RNA5SP236 rRNA +chr7 112288623 112288952 + ENSG00000202406.1 RN7SKP187 misc_RNA +chr7 114629855 114629956 + ENSG00000266229.1 AC020606.1 miRNA +chr7 116909877 116909964 - ENSG00000252115.1 Y_RNA misc_RNA +chr7 116952698 116952813 + ENSG00000275359.1 ST7-AS1_1 misc_RNA +chr7 116953214 116953324 + ENSG00000277583.1 ST7-AS1_2 misc_RNA +chr7 116954480 116954679 + ENSG00000273596.1 ST7-OT4_1 misc_RNA +chr7 116956431 116956723 + ENSG00000276100.1 ST7-OT4_3 misc_RNA +chr7 116959593 116959805 + ENSG00000274606.1 ST7-OT4_4 misc_RNA +chr7 117020211 117020319 + ENSG00000275870.1 MIR6132 miRNA +chr7 117117912 117117983 + ENSG00000274344.1 ST7-AS2_1 misc_RNA +chr7 117184126 117184199 + ENSG00000275054.1 ST7-OT3_1 misc_RNA +chr7 117191647 117191761 + ENSG00000278482.1 ST7-OT3_3 misc_RNA +chr7 121050927 121051203 + ENSG00000234927.1 HMGN1P18 processed_pseudogene +chr7 128306649 128307678 + ENSG00000242261.1 RP11-62J1.3 processed_pseudogene +chr7 128466563 128469171 + ENSG00000272601.1 RP11-155G14.5 transcribed_unprocessed_pseudogene +chr7 129756266 129756377 + ENSG00000212238.1 RNA5SP244 rRNA +chr7 130487483 130487622 + ENSG00000277269.1 MESTIT1_1 misc_RNA +chr7 130488304 130488538 + ENSG00000278055.1 MESTIT1_2 misc_RNA +chr7 130489868 130489966 + ENSG00000274500.1 MESTIT1_3 misc_RNA +chr7 130496111 130496204 + ENSG00000199043.1 MIR335 miRNA +chr7 130877459 130877539 - ENSG00000274250.1 MIR29B1 miRNA +chr7 135704537 135704841 + ENSG00000273219.1 RP11-644N4.1 antisense +chr7 135927274 135927450 - ENSG00000267697.1 LUZP6 protein_coding +chr7 136903167 136903294 + ENSG00000207597.1 MIR490 miRNA +chr7 138123758 138123821 + ENSG00000266193.1 MIR4468 miRNA +chr7 140645966 140646034 + ENSG00000280499.1 AC006452.2 miRNA +chr7 142797119 142797166 + ENSG00000211769.1 TRBJ2-5 TR_J_gene +chr7 142797239 142797291 + ENSG00000211770.1 TRBJ2-6 TR_J_gene +chr7 143959971 143960924 + ENSG00000279723.1 OR2F1 protein_coding +chr7 151238421 151238538 + ENSG00000211517.1 MIR671 miRNA +chr7 151240399 151240972 + ENSG00000272661.1 RP4-548D19.3 antisense +chr8 8582352 8582427 - ENSG00000281480.1 AC114550.1 miRNA +chr8 9903388 9903472 - ENSG00000275677.1 MIR124-1 miRNA +chr8 17498737 17499157 + ENSG00000280453.1 RP11-349F21.4 TEC +chr8 20290174 20290289 + ENSG00000274467.1 5S_rRNA rRNA +chr8 23225233 23230915 - ENSG00000250714.3 RP11-1149O23.4 antisense +chr8 24956621 24957110 + ENSG00000272157.1 CTD-2168K21.2 antisense +chr8 27610601 27610751 - ENSG00000273705.1 MIR6843 miRNA +chr8 27701673 27701767 - ENSG00000265075.1 MIR3622B miRNA +chr8 29067279 29068454 + ENSG00000259607.1 CTD-2647L4.5 antisense +chr8 33513475 33513578 + ENSG00000239039.1 SNORD13 snoRNA +chr8 37858949 37861333 + ENSG00000280064.1 RP11-205M5.3 TEC +chr8 38970360 38973011 - ENSG00000253645.1 CTD-2544N14.3 antisense +chr8 41609692 41621502 - ENSG00000264578.1 RP11-360L9.8 antisense +chr8 55745232 55745342 + ENSG00000222955.1 RNA5SP265 rRNA +chr8 56073835 56073901 - ENSG00000238650.1 SNORD54 snoRNA +chr8 66922467 66922555 - ENSG00000254341.2 SNORD87 snoRNA +chr8 70480192 70480487 - ENSG00000275128.1 Metazoa_SRP misc_RNA +chr8 73982125 73982467 + ENSG00000244295.2 RPS20P21 processed_pseudogene +chr8 80484589 80484683 - ENSG00000277604.1 Y_RNA misc_RNA +chr8 86098965 86154225 - ENSG00000253675.1 CTD-3118D11.2 antisense +chr8 86657870 86657952 - ENSG00000221137.1 AC013751.1 miRNA +chr8 93733216 93734022 + ENSG00000253722.1 RP11-10N23.4 antisense +chr8 93916022 93916119 - ENSG00000276513.1 MIR378D2 miRNA +chr8 94791643 94793106 - ENSG00000254307.2 KB-1608C10.2 antisense +chr8 98042086 98042217 - ENSG00000207067.1 SNORA72 snoRNA +chr8 98192205 98192313 - ENSG00000252558.1 RNU6-914P snRNA +chr8 100702968 100703024 - ENSG00000277719.1 MIR7705 miRNA +chr8 101686547 101689093 + ENSG00000253629.1 KB-1107E3.1 antisense +chr8 103228425 103229314 - ENSG00000253851.1 RP11-318M2.3 antisense +chr8 109973943 109974781 + ENSG00000255402.1 RP11-696P8.2 antisense +chr8 116874728 116874800 - ENSG00000264875.1 MIR3610 miRNA +chr8 117164179 117164255 + ENSG00000281002.1 AC084114.1 miRNA +chr8 126073046 126073532 - ENSG00000253841.1 RP11-622O11.5 processed_pseudogene +chr8 126556896 126557433 + ENSG00000254010.1 RP11-103H7.5 antisense +chr8 127794541 127794734 + ENSG00000276443.1 PVT1_1 misc_RNA +chr8 127795962 127796028 + ENSG00000275264.1 MIR1204 miRNA +chr8 127890626 127890720 + ENSG00000278324.1 PVT1_3 misc_RNA +chr8 133229056 133229697 + ENSG00000270132.1 WISP1-OT1 sense_intronic +chr8 134598071 134598149 + ENSG00000276140.1 ZFAT-AS1_1 misc_RNA +chr8 134598318 134598518 + ENSG00000277732.1 ZFAT-AS1_2 misc_RNA +chr8 134600257 134600336 + ENSG00000278454.1 ZFAT-AS1_3 misc_RNA +chr8 142727283 142727690 - ENSG00000253806.1 CTD-2292P10.2 antisense +chr8 143542110 143542398 + ENSG00000275558.1 7SK misc_RNA +chr8 143579636 143580670 + ENSG00000254741.1 RP11-661A12.7 antisense +chr8 143837756 143837816 - ENSG00000274094.1 MIR6845 miRNA +chr8 144079874 144079942 + ENSG00000276472.1 MIR6847 miRNA +chr8 144262673 144262737 - ENSG00000277158.1 MIR7112 miRNA +chr8 144314590 144315138 - ENSG00000254690.1 GS1-393G12.12 antisense +chr8 144394149 144394230 - ENSG00000216133.1 MIR939 miRNA +chr8 144400086 144400165 - ENSG00000266624.1 MIR1234 miRNA +chr8 144400277 144400345 - ENSG00000274683.1 MIR6849 miRNA +chr8 144463817 144465101 + ENSG00000254578.1 CTD-2517M22.16 antisense +chr8 144853413 144853522 + ENSG00000263640.1 AF235103.1 miRNA +chr8 144994886 144995540 + ENSG00000254618.1 TMED10P1 processed_pseudogene +chr8 145005561 145005906 - ENSG00000255530.1 RP5-1047A19.6 processed_pseudogene +chr9 30144 30281 + ENSG00000278579.1 MIR1302-2 miRNA +chr9 4834156 4860275 + ENSG00000281007.1 AL158147.2 protein_coding +chr9 4850299 4850373 - ENSG00000228165.1 RP11-125K10.5 antisense +chr9 30774228 30774319 + ENSG00000211510.2 AL590726.1 miRNA +chr9 33042109 33042216 - ENSG00000222169.1 AL162590.1 miRNA +chr9 35449748 35450352 + ENSG00000244213.1 ZFAND6P1 processed_pseudogene +chr9 35657754 35658017 - ENSG00000277027.1 RNase_MRP ribozyme +chr9 35752990 35756613 - ENSG00000215183.4 MSMP protein_coding +chr9 35756712 35757940 - ENSG00000228843.2 RP11-112J3.15 antisense +chr9 35811476 35811550 - ENSG00000263448.1 AL133410.1 miRNA +chr9 35859062 35859983 - ENSG00000236083.1 OR13E1P unitary_pseudogene +chr9 35957139 35958098 - ENSG00000122718.5 OR2S2 protein_coding +chr9 37434177 37434586 + ENSG00000236156.2 CHCHD4P3 processed_pseudogene +chr9 38542314 38542569 - ENSG00000259898.1 CYP4F33P processed_pseudogene +chr9 38542389 38543215 - ENSG00000272934.1 RP11-392E22.10 processed_transcript +chr9 38543104 38543446 - ENSG00000250989.1 RP11-392E22.5 processed_pseudogene +chr9 39173794 39174513 - ENSG00000243695.1 RP11-290L7.3 processed_pseudogene +chr9 41280460 41280787 + ENSG00000278647.1 RP11-4L24.2 transcribed_processed_pseudogene +chr9 69428248 69428721 - ENSG00000243888.1 RP11-548B3.3 3prime_overlapping_ncrna +chr9 70311607 70311701 - ENSG00000239180.1 Y_RNA misc_RNA +chr9 76785782 76786190 + ENSG00000277320.1 PCA3_2 misc_RNA +chr9 79726069 79726321 + ENSG00000240979.1 RP11-79D8.2 processed_pseudogene +chr9 83969748 83969857 - ENSG00000207603.1 MIR7-1 miRNA +chr9 89497938 89498021 + ENSG00000264913.1 AL590233.1 miRNA +chr9 92836826 92837668 - ENSG00000226721.2 EEF1DP2 processed_pseudogene +chr9 95086012 95086096 - ENSG00000207617.3 MIR3074 miRNA +chr9 97700234 97700325 + ENSG00000266608.1 AL445531.1 miRNA +chr9 100732033 100732116 + ENSG00000281312.1 AL390876.1 miRNA +chr9 116398157 116400606 - ENSG00000256040.2 PAPPA-AS1 antisense +chr9 121341347 121348132 + ENSG00000280315.1 AL161784.1 protein_coding +chr9 122628579 122629535 - ENSG00000171484.4 OR1B1 protein_coding +chr9 123111546 123111643 - ENSG00000274325.1 MIR600 miRNA +chr9 127690687 127690795 - ENSG00000264329.1 MIR3911 miRNA +chr9 127785833 127785923 + ENSG00000266070.1 MIR3960 miRNA +chr9 127785836 127785905 + ENSG00000281546.1 AL162586.1 miRNA +chr9 128260749 128260817 - ENSG00000274982.1 AL590708.3 miRNA +chr9 128391461 128392016 + ENSG00000272593.1 RP11-339B21.11 lincRNA +chr9 128392618 128392714 - ENSG00000273685.1 MIR219B miRNA +chr9 129040566 129040674 + ENSG00000280692.1 AL592211.1 miRNA +chr9 129175807 129177575 + ENSG00000268050.2 RP11-247A12.8 antisense +chr9 131497479 131500191 - ENSG00000176868.2 RP11-334J6.7 antisense +chr9 133338990 133339465 + ENSG00000230064.1 RP11-244N20.7 processed_pseudogene +chr9 133349396 133349470 + ENSG00000206611.1 SNORD24 snoRNA +chr9 133350095 133350168 + ENSG00000200831.1 SNORD36B snoRNA +chr9 133350456 133350528 + ENSG00000199744.1 SNORD36A snoRNA +chr9 136249978 136251205 + ENSG00000279813.1 CR392000.1 protein_coding +chr9 136726104 136726239 - ENSG00000280496.1 SNORA43 snoRNA +chr9 136726105 136726234 - ENSG00000276161.1 SNORA17 snoRNA +chr9 136726747 136726879 - ENSG00000274998.1 SNORA17 snoRNA +chr9 136726748 136726879 - ENSG00000281808.1 SNORA17 snoRNA +chr9 137063535 137064581 + ENSG00000231864.2 RP11-229P13.23 antisense +chr9 137450026 137450086 - ENSG00000276682.1 MIR7114 miRNA +chr10 277184 277308 + ENSG00000264248.1 AL603831.1 miRNA +chr10 5524976 5525742 - ENSG00000256462.1 RP11-116G8.5 antisense +chr10 5861805 5862594 - ENSG00000240180.1 RP11-318E3.4 processed_pseudogene +chr10 22332587 22332981 - ENSG00000271981.1 RP11-573G6.8 lincRNA +chr10 29421476 29422012 - ENSG00000274985.1 PTCHD3P1 unprocessed_pseudogene +chr10 32346864 32346946 - ENSG00000222309.1 AL391839.1 miRNA +chr10 35641172 35641252 - ENSG00000264780.1 MIR4683 miRNA +chr10 37831889 37831971 + ENSG00000266800.1 AL135791.1 miRNA +chr10 42470082 42470268 - ENSG00000279239.1 RP11-178A10.3 transcribed_unprocessed_pseudogene +chr10 42832447 42832550 - ENSG00000252416.1 RNU6-885P snRNA +chr10 50393006 50394561 + ENSG00000279291.1 AC069547.1 protein_coding +chr10 50393006 50394561 - ENSG00000279027.1 RP11-521C22.3 TEC +chr10 72274915 72275980 - ENSG00000269926.1 RP11-442H21.2 antisense +chr10 77912280 77912362 - ENSG00000281632.1 AL391421.1 miRNA +chr10 79684494 79684983 - ENSG00000224886.2 RP11-119F19.4 transcribed_processed_pseudogene +chr10 79970963 79973213 - ENSG00000280259.1 RP11-479O17.9 TEC +chr10 80091411 80091867 - ENSG00000279399.1 RP11-369J21.12 TEC +chr10 86751611 86751772 - ENSG00000281735.1 Clostridiales-1 sRNA +chr10 86970237 86970826 - ENSG00000273413.1 RP11-96C23.15 antisense +chr10 87001636 87009905 + ENSG00000261011.1 RP11-96C23.11 transcribed_unprocessed_pseudogene +chr10 89644603 89645223 - ENSG00000249962.1 RP11-80H5.5 processed_pseudogene +chr10 89837612 89839334 - ENSG00000270670.1 RP11-248C1.3 processed_pseudogene +chr10 102409042 102409102 - ENSG00000275957.1 AL121928.1 miRNA +chr10 102483039 102483559 + ENSG00000273262.1 RP11-18I14.11 antisense +chr10 104312141 104313881 + ENSG00000270075.1 RP11-127L20.5 antisense +chr10 110898090 110898155 + ENSG00000265827.1 MIR4680 miRNA +chr10 114174105 114174179 - ENSG00000238742.1 MIR2110 miRNA +chr10 127013501 127026475 - ENSG00000232935.2 RP11-223P11.2 antisense +chr10 129837505 129837794 + ENSG00000275327.1 RP11-234G16.4 antisense +chr11 203623 205470 + ENSG00000254559.1 RP11-304M2.5 antisense +chr11 209336 209406 + ENSG00000274298.1 MIR6743 miRNA +chr11 811681 811814 + ENSG00000199785.1 SNORA52 snoRNA +chr11 1242261 1249676 - ENSG00000255177.2 RP11-532E4.2 antisense +chr11 1996540 1996610 + ENSG00000275266.1 H19_1 misc_RNA +chr11 1996730 1996842 - ENSG00000278648.1 AC051649.1 miRNA +chr11 1997484 1997552 + ENSG00000274866.1 H19_2 misc_RNA +chr11 1997713 1997828 + ENSG00000280586.1 H19_3 misc_RNA +chr11 2129121 2129964 - ENSG00000240801.1 AC132217.4 3prime_overlapping_ncrna +chr11 2404515 2407908 + ENSG00000230483.1 AC124057.5 antisense +chr11 2652099 2652562 + ENSG00000275666.1 KCNQ1OT1_1 misc_RNA +chr11 2674097 2674292 + ENSG00000276105.1 KCNQ1OT1_2 misc_RNA +chr11 2674625 2674740 + ENSG00000276494.1 KCNQ1OT1_3 misc_RNA +chr11 2697851 2698076 + ENSG00000276015.1 KCNQ1OT1_5 misc_RNA +chr11 3856062 3856141 + ENSG00000263421.1 MIR4687 miRNA +chr11 4367351 4368295 - ENSG00000280253.1 OR52B4 protein_coding +chr11 4768979 4769917 - ENSG00000188069.4 OR51F1 protein_coding +chr11 4803433 4804380 - ENSG00000176937.9 OR52R1 protein_coding +chr11 4803433 4804380 - ENSG00000279270.1 OR52R1 polymorphic_pseudogene +chr11 4923374 4924339 - ENSG00000176879.3 OR51G1 protein_coding +chr11 5069572 5070461 + ENSG00000236621.3 OR52E1 pseudogene +chr11 5323359 5324297 - ENSG00000184881.3 OR51B2 protein_coding +chr11 6608667 6610135 - ENSG00000254641.1 RP11-732A19.2 sense_overlapping +chr11 6621451 6622322 + ENSG00000255390.1 RP11-732A19.5 antisense +chr11 6785038 6785988 + ENSG00000170803.5 OR2AG1 protein_coding +chr11 7927718 7928662 - ENSG00000175393.3 OR10A6 protein_coding +chr11 8684204 8684314 + ENSG00000280884.1 AC091053.1 miRNA +chr11 8684227 8684356 + ENSG00000200983.1 SNORA45A snoRNA +chr11 8693357 8696607 + ENSG00000254665.1 RP11-152H18.3 antisense +chr11 9578028 9578131 + ENSG00000238387.1 snoU13 snoRNA +chr11 9958744 9959790 - ENSG00000254765.1 RP11-1H15.1 processed_pseudogene +chr11 10801467 10801608 - ENSG00000238622.1 SNORD97 snoRNA +chr11 11352426 11353307 + ENSG00000255351.1 RP11-567I13.1 antisense +chr11 12261426 12263173 - ENSG00000254680.1 RP11-265D17.2 antisense +chr11 15969533 15969621 - ENSG00000274140.1 MIR6073 miRNA +chr11 17075779 17075868 - ENSG00000201403.1 SNORD14B snoRNA +chr11 20119684 20120632 - ENSG00000254894.1 NAV2-AS1 antisense +chr11 32097143 32105091 - ENSG00000255252.3 RP1-65P5.3 antisense +chr11 32435738 32435846 + ENSG00000278822.1 WT1-AS_1 misc_RNA +chr11 32436797 32437030 + ENSG00000278045.1 WT1-AS_3 misc_RNA +chr11 32439086 32439206 + ENSG00000276530.1 WT1-AS_6 misc_RNA +chr11 32439716 32440009 + ENSG00000273908.1 WT1-AS_7 misc_RNA +chr11 32440109 32440383 + ENSG00000277119.1 WT1-AS_8 misc_RNA +chr11 33190062 33190503 - ENSG00000241950.1 RPL29P23 processed_pseudogene +chr11 33354465 33354545 + ENSG00000223134.1 AL122015.1 miRNA +chr11 35860654 35860744 - ENSG00000266590.1 AC090692.1 miRNA +chr11 45905941 45906461 - ENSG00000255498.1 RP11-618K13.2 antisense +chr11 47577725 47578277 + ENSG00000231880.2 RP11-76I23.7 antisense +chr11 48245104 48246015 + ENSG00000279556.1 OR4X2 protein_coding +chr11 48263861 48264778 + ENSG00000176567.1 OR4X1 protein_coding +chr11 48263861 48264778 + ENSG00000279260.1 OR4X1 polymorphic_pseudogene +chr11 55572128 55573060 + ENSG00000181935.3 OR4C16 protein_coding +chr11 55572128 55573060 + ENSG00000279514.1 OR4C16 polymorphic_pseudogene +chr11 55773438 55774382 + ENSG00000198877.1 OR5D13 protein_coding +chr11 55773438 55774382 + ENSG00000279761.1 OR5D13 polymorphic_pseudogene +chr11 55811467 55812402 + ENSG00000186117.3 OR5L1 protein_coding +chr11 56318307 56319245 + ENSG00000181689.1 OR8K3 protein_coding +chr11 56318307 56319245 + ENSG00000280314.1 OR8K3 polymorphic_pseudogene +chr11 56412744 56413668 + ENSG00000181395.6 OR5AL1 pseudogene +chr11 56417258 56418232 - ENSG00000174942.1 OR5R1 protein_coding +chr11 56417258 56418232 - ENSG00000279961.1 OR5R1 polymorphic_pseudogene +chr11 56663686 56664618 + ENSG00000279911.1 OR5AR1 protein_coding +chr11 57476493 57477534 - ENSG00000255301.1 RP11-624G17.3 antisense +chr11 58030953 58031906 + ENSG00000172381.4 OR6Q1 protein_coding +chr11 58214745 58215722 + ENSG00000172774.7 OR1S1 protein_coding +chr11 61792495 61792561 - ENSG00000207601.1 MIR611 miRNA +chr11 61815161 61815240 - ENSG00000222326.1 MIR1908 miRNA +chr11 62372656 62372719 + ENSG00000265696.1 AP003064.2 miRNA +chr11 62391516 62393372 - ENSG00000255126.1 CTD-2531D15.5 antisense +chr11 62665422 62665570 + ENSG00000206597.1 SNORA57 snoRNA +chr11 62789815 62789885 + ENSG00000274856.1 MIR6748 miRNA +chr11 62841619 62841809 - ENSG00000222328.1 RNU2-2P snRNA +chr11 62852910 62853035 - ENSG00000277194.1 SNORD22 snoRNA +chr11 62854161 62854285 - ENSG00000278527.1 SNORD22 snoRNA +chr11 62854621 62854695 - ENSG00000274544.1 SNORD28 snoRNA +chr11 62855012 62855083 - ENSG00000275996.1 SNORD27 snoRNA +chr11 62855292 62855366 - ENSG00000276788.1 SNORD26 snoRNA +chr11 62855564 62855632 - ENSG00000275043.1 SNORD25 snoRNA +chr11 64313860 64313950 + ENSG00000278148.1 AP001453.1 miRNA +chr11 64891132 64891243 - ENSG00000207648.2 MIR192 miRNA +chr11 64891355 64891439 - ENSG00000277225.1 MIR194-2 miRNA +chr11 65117157 65117458 + ENSG00000255173.1 AP003068.12 antisense +chr11 65129916 65129978 - ENSG00000277547.1 MIR6751 miRNA +chr11 65175035 65175502 - ENSG00000249251.1 PGAM1P8 processed_pseudogene +chr11 65423273 65423392 + ENSG00000278144.1 NEAT1_1 misc_RNA +chr11 65423638 65423742 + ENSG00000278050.1 NEAT1_2 misc_RNA +chr11 65423960 65424118 + ENSG00000277599.1 NEAT1_3 misc_RNA +chr11 65444458 65444557 + ENSG00000273834.1 MIR612 miRNA +chr11 65498010 65498405 - ENSG00000270117.1 AP000769.7 lincRNA +chr11 65502034 65503622 - ENSG00000279576.1 MALAT1 protein_coding +chr11 65502914 65503008 + ENSG00000278217.1 MALAT1 misc_RNA +chr11 65506117 65506173 + ENSG00000274072.1 mascRNA-menRNA sRNA +chr11 65795946 65797219 - ENSG00000255404.1 RP11-770G2.5 antisense +chr11 66276779 66277492 - ENSG00000254452.1 RP11-867G23.4 antisense +chr11 67431367 67435399 - ENSG00000255949.1 AP003419.16 antisense +chr11 67435510 67438067 - ENSG00000213402.2 PTPRCAP protein_coding +chr11 68032864 68032922 + ENSG00000277703.1 MIR7113 miRNA +chr11 68033897 68033981 + ENSG00000266737.1 MIR4691 miRNA +chr11 69671952 69672075 + ENSG00000281781.1 AP001888.1 protein_coding +chr11 70187788 70188509 - ENSG00000254902.1 ANO1-AS1 antisense +chr11 70206291 70207390 - ENSG00000254721.1 RP11-805J14.5 antisense +chr11 73395559 73396436 - ENSG00000256928.1 RP11-809N8.2 antisense +chr11 74455348 74456825 + ENSG00000254928.1 RP11-702H23.6 antisense +chr11 75264289 75265170 + ENSG00000254963.1 CTD-2562J17.9 antisense +chr11 75742270 75742331 + ENSG00000281528.1 AP001922.1 miRNA +chr11 76404140 76404252 - ENSG00000201756.1 Y_RNA misc_RNA +chr11 78015715 78016495 + ENSG00000254829.1 RP11-7I15.3 antisense +chr11 78016971 78079865 - ENSG00000259112.1 NDUFC2-KCTD14 protein_coding +chr11 82957423 82958216 + ENSG00000242279.1 RP11-659G9.1 processed_pseudogene +chr11 83185521 83187036 - ENSG00000269939.1 RP11-727A23.11 lincRNA +chr11 83213005 83213404 + ENSG00000241020.1 RP11-727A23.1 processed_pseudogene +chr11 86278333 86278398 + ENSG00000273630.1 MIR6755 miRNA +chr11 93721542 93721621 + ENSG00000275146.1 snoU2_19 snoRNA +chr11 93730513 93730646 - ENSG00000207112.1 SNORA25 snoRNA +chr11 93730979 93731099 - ENSG00000206799.1 SNORA32 snoRNA +chr11 93732004 93732133 - ENSG00000206834.1 SNORA1 snoRNA +chr11 93732361 93732499 - ENSG00000207304.1 SNORA8 snoRNA +chr11 93732435 93732501 - ENSG00000281293.1 AP001273.1 miRNA +chr11 93733228 93733300 - ENSG00000239195.1 SNORD5 snoRNA +chr11 93733466 93733597 - ENSG00000207145.1 SNORA18 snoRNA +chr11 93733674 93733764 - ENSG00000221170.1 MIR1304 miRNA +chr11 93735111 93735236 - ENSG00000210825.1 SNORA40 snoRNA +chr11 96341427 96341534 + ENSG00000266192.2 MIR1260B miRNA +chr11 102229851 102230922 - ENSG00000254422.1 RP11-864G5.3 antisense +chr11 112218326 112218720 + ENSG00000243930.1 RPS12P21 processed_pseudogene +chr11 113789242 113790027 + ENSG00000255870.1 RP11-667M19.5 processed_pseudogene +chr11 114312063 114312207 + ENSG00000280653.1 AP002518.1 miRNA +chr11 117820163 117876667 - ENSG00000255245.3 FXYD6-FXYD2 protein_coding +chr11 118644000 118644079 + ENSG00000275466.1 MIR6716 miRNA +chr11 118910708 118910787 + ENSG00000264211.1 MIR4492 miRNA +chr11 119018944 119019012 + ENSG00000266398.1 MIR3656 miRNA +chr11 119095051 119095191 + ENSG00000281272.1 AP003391.1 miRNA +chr11 119312950 119313012 - ENSG00000277325.1 MIR6756 miRNA +chr11 119336249 119337309 - ENSG00000245385.2 RP11-334E6.10 antisense +chr11 119338942 119340883 - ENSG00000223953.4 C1QTNF5 protein_coding +chr11 119417951 119419114 + ENSG00000263873.1 RP11-334E6.12 sense_intronic +chr11 119821829 119821927 - ENSG00000276827.1 AP001994.1 miRNA +chr11 120986258 120986353 + ENSG00000281726.1 GRIK4_3p_UTR misc_RNA +chr11 121055207 121055275 - ENSG00000281492.1 AP000646.1 miRNA +chr11 123058909 123058995 - ENSG00000207118.1 SNORD14D snoRNA +chr11 123059335 123059422 - ENSG00000202252.1 SNORD14C snoRNA +chr11 124319262 124320197 - ENSG00000197263.3 OR8D2 protein_coding +chr11 124423942 124424871 - ENSG00000198657.5 OR8B4 protein_coding +chr11 124636459 124636592 + ENSG00000200278.1 RNA5SP352 rRNA +chr11 124636491 124636552 + ENSG00000280773.1 AP001524.1 miRNA +chr11 124883691 124887789 + ENSG00000254568.1 RP11-664I21.5 antisense +chr11 124919244 124920677 + ENSG00000221932.6 HEPN1 protein_coding +chr11 125957900 125958652 + ENSG00000264299.1 RP11-680F20.12 antisense +chr11 130121672 130121780 - ENSG00000277300.1 AP003041.1 miRNA +chr11 133898504 133898581 - ENSG00000264919.1 MIR4697 miRNA +chr12 3726222 3726327 - ENSG00000222338.1 RNU6-174P snRNA +chr12 4809176 4813412 + ENSG00000151079.7 KCNA6 protein_coding +chr12 6510275 6510522 + ENSG00000276232.1 SCARNA10 sense_intronic +chr12 6537794 6538370 - ENSG00000269968.1 RP5-940J5.9 antisense +chr12 6943816 6943878 + ENSG00000238923.1 RNU7-1 snRNA +chr12 7115736 7116486 - ENSG00000276144.1 ABC12-49244600F4.4 lincRNA +chr12 9127871 9127985 + ENSG00000211542.1 AC007436.1 miRNA +chr12 9695384 9696227 + ENSG00000213443.2 RP11-75L1.2 processed_pseudogene +chr12 10214161 10214761 - ENSG00000255958.1 RP11-656E20.5 antisense +chr12 12915829 12915918 + ENSG00000207817.1 MIR614 miRNA +chr12 13540231 13544540 + ENSG00000277935.1 RP11-4N23.4 lincRNA +chr12 14774716 14774860 - ENSG00000281457.1 AC010168.1 miRNA +chr12 22195469 22195629 - ENSG00000212172.1 RNU1-149P snRNA +chr12 27798641 27800708 - ENSG00000256512.1 RP11-860B13.3 antisense +chr12 34027268 34027362 - ENSG00000264446.1 AC046130.1 miRNA +chr12 38321566 38321660 - ENSG00000266333.1 AC117372.1 miRNA +chr12 39443048 39443116 - ENSG00000252974.1 AC121334.1 miRNA +chr12 48487946 48488408 + ENSG00000240443.1 RPS10P20 transcribed_processed_pseudogene +chr12 48766194 48767323 + ENSG00000257653.1 RP11-579D7.2 antisense +chr12 48995150 48996334 + ENSG00000258283.1 RP11-386G11.3 antisense +chr12 49954639 49956125 - ENSG00000257378.1 RP11-469H8.8 antisense +chr12 51809705 51810600 - ENSG00000260122.1 RP11-923I11.3 lincRNA +chr12 52241481 52241613 - ENSG00000281415.1 AC021066.1 miRNA +chr12 52449492 52449620 + ENSG00000280966.1 AC055736.2 miRNA +chr12 52471155 52471283 + ENSG00000281474.1 AC055736.4 miRNA +chr12 52490592 52490720 + ENSG00000281194.1 AC055736.3 miRNA +chr12 52517613 52517741 + ENSG00000280827.1 AC055736.1 miRNA +chr12 52824221 52824358 + ENSG00000281110.1 AC107016.2 miRNA +chr12 52951708 52951795 + ENSG00000265039.1 AC107016.1 miRNA +chr12 53464720 53464901 + ENSG00000273658.1 uc_338 misc_RNA +chr12 53506690 53507638 - ENSG00000139574.8 NPFF protein_coding +chr12 53963629 53963697 + ENSG00000275589.1 HOTAIR_2 misc_RNA +chr12 53965965 53966061 + ENSG00000277994.1 HOTAIR_3 misc_RNA +chr12 54231397 54231476 - ENSG00000265371.1 MIR3198-2 miRNA +chr12 54543111 54544105 - ENSG00000257824.1 RP11-1049A21.2 antisense +chr12 55870941 55871219 - ENSG00000265119.2 RN7SL676P misc_RNA +chr12 55966838 55967474 - ENSG00000258554.1 RP11-973D8.4 antisense +chr12 56104614 56113905 - ENSG00000257553.1 RP11-603J24.17 antisense +chr12 57512688 57512750 + ENSG00000275657.1 MIR6758 miRNA +chr12 57694132 57721510 - ENSG00000257342.1 RP11-571M6.7 antisense +chr12 57806154 57806260 - ENSG00000206749.1 RNU6-1083P snRNA +chr12 62260359 62260454 + ENSG00000276811.1 MIR6125 miRNA +chr12 62934507 62934607 - ENSG00000275729.1 AC078814.1 miRNA +chr12 63004338 63006541 - ENSG00000257235.1 RP11-848D3.5 lincRNA +chr12 64146388 64147857 - ENSG00000255629.1 RP11-196H14.3 antisense +chr12 64266413 64266766 + ENSG00000256192.1 RP11-290I21.2 processed_pseudogene +chr12 64696191 64696550 - ENSG00000280320.1 RP11-629N8.5 TEC +chr12 65858013 65858132 + ENSG00000211577.1 AC090673.1 miRNA +chr12 66251082 66251157 + ENSG00000275058.1 MIR6502 miRNA +chr12 68841288 68843237 - ENSG00000257181.1 RP11-611O2.5 antisense +chr12 68841946 68842384 + ENSG00000256664.1 RP11-611O2.3 processed_pseudogene +chr12 69353493 69354225 - ENSG00000257764.2 RP11-1143G9.4 antisense +chr12 71793855 71799627 - ENSG00000257410.1 RP11-2H8.2 lincRNA +chr12 74538145 74538633 - ENSG00000257386.1 RP11-56G10.2 antisense +chr12 76032658 76033897 + ENSG00000257839.1 RP11-290L1.2 antisense +chr12 85958686 85960946 + ENSG00000258178.1 RP11-18J9.3 lincRNA +chr12 89544203 89544488 - ENSG00000279939.1 RP11-734K2.3 TEC +chr12 91986626 91993403 - ENSG00000279037.1 C12orf79 protein_coding +chr12 91986682 91993403 - ENSG00000280112.1 C12orf79 protein_coding +chr12 93509487 93509768 + ENSG00000243015.2 RN7SL737P misc_RNA +chr12 94571231 94571352 - ENSG00000277302.1 MIR7844 miRNA +chr12 94834398 94834513 + ENSG00000208038.1 MIR492 miRNA +chr12 97492462 97492597 + ENSG00000273942.1 RMST_2 misc_RNA +chr12 97530656 97530858 + ENSG00000275971.1 RMST_6 misc_RNA +chr12 97532691 97532958 + ENSG00000274819.1 RMST_7 misc_RNA +chr12 97563812 97563911 + ENSG00000207586.1 MIR135A2 miRNA +chr12 97564174 97564327 + ENSG00000277081.1 RMST_10 misc_RNA +chr12 100157256 100157338 - ENSG00000221770.1 AC010203.1 miRNA +chr12 100158502 100158765 - ENSG00000266610.2 RN7SL176P misc_RNA +chr12 101779814 101779929 + ENSG00000201168.1 RNA5SP368 rRNA +chr12 102217318 102217613 - ENSG00000264554.2 RN7SL793P misc_RNA +chr12 102230027 102230533 - ENSG00000258142.2 RP11-18O15.1 processed_pseudogene +chr12 103930425 103930555 + ENSG00000265072.1 MIR3652 miRNA +chr12 104125268 104125329 + ENSG00000280646.1 AC089983.1 miRNA +chr12 107650789 107650892 + ENSG00000222160.1 Y_RNA misc_RNA +chr12 108778912 108779166 + ENSG00000280110.1 RP11-423G4.8 TEC +chr12 109567975 109568115 - ENSG00000200274.1 RNU4-32P snRNA +chr12 110360456 110360538 - ENSG00000281030.1 AC006088.1 miRNA +chr12 110496352 110496421 - ENSG00000202335.1 SNORD50 snoRNA +chr12 111598951 111599031 - ENSG00000281280.1 AC137055.1 miRNA +chr12 111899263 111901391 + ENSG00000229186.4 ADAM1A unitary_pseudogene +chr12 113159113 113159177 - ENSG00000276908.1 MIR7106 miRNA +chr12 113185624 113192161 - ENSG00000257286.1 RP11-545P7.4 antisense +chr12 117453012 117456986 + ENSG00000255686.1 RP11-227B21.2 lincRNA +chr12 119713634 119713724 - ENSG00000221323.1 MIR1178 miRNA +chr12 120697124 120699541 - ENSG00000256364.1 RP11-173P15.3 antisense +chr12 120721507 120723639 - ENSG00000256569.1 RP11-173P15.5 antisense +chr12 120723193 120723266 + ENSG00000265455.1 MIR4700 miRNA +chr12 122865335 122867021 + ENSG00000256152.2 RP11-463O12.3 lincRNA +chr12 123364764 123364843 - ENSG00000277700.1 MIR8072 miRNA +chr12 125025434 125027410 - ENSG00000280634.1 THRIL antisense +chr12 130144954 130145691 + ENSG00000280405.1 RP11-143E21.4 TEC +chr12 130977562 130978768 + ENSG00000256204.1 RP11-243M5.1 lincRNA +chr12 131296110 131297972 - ENSG00000248703.2 RP11-495K9.3 lincRNA +chr12 132077803 132080460 - ENSG00000257000.1 RP13-820C6.2 antisense +chr12 132126461 132126764 - ENSG00000256804.1 RP13-977J11.5 processed_pseudogene +chr12 132279256 132280900 - ENSG00000278872.1 RP13-895J2.4 TEC +chr12 132835374 132835500 - ENSG00000252079.1 RNU6-327P snRNA +chr13 21287634 21287828 - ENSG00000277077.1 RP11-101P17.15 unprocessed_pseudogene +chr13 24321126 24321428 - ENSG00000281899.1 C1QTNF9B-AS1 protein_coding +chr13 25246531 25246615 + ENSG00000221324.1 AL590787.1 miRNA +chr13 25944606 25944673 + ENSG00000281497.1 AL138815.1 miRNA +chr13 27255064 27255135 + ENSG00000207500.1 SNORD102 snoRNA +chr13 27255401 27255526 + ENSG00000207051.1 SNORA27 snoRNA +chr13 30154066 30154586 + ENSG00000232643.1 LINC00385 lincRNA +chr13 30206616 30206699 - ENSG00000266816.1 AL356750.1 miRNA +chr13 44196129 44196200 - ENSG00000276319.1 MIR8079 miRNA +chr13 44432144 44432678 + ENSG00000280357.1 RP11-269C23.4 TEC +chr13 45336314 45336447 - ENSG00000253051.1 SNORA31 snoRNA +chr13 45340039 45341183 + ENSG00000273149.1 RP11-290D2.6 antisense +chr13 45732089 45732172 - ENSG00000280848.1 AL139320.1 miRNA +chr13 46437394 46437988 - ENSG00000241353.3 PPP1R2P4 processed_pseudogene +chr13 50044649 50044768 + ENSG00000277913.1 DLEU2_1 misc_RNA +chr13 50045143 50045232 + ENSG00000277066.1 DLEU2_2 misc_RNA +chr13 50049591 50049663 + ENSG00000274878.1 DLEU2_3 misc_RNA +chr13 50075570 50075653 + ENSG00000277752.1 DLEU2_5 misc_RNA +chr13 50081843 50081978 + ENSG00000275559.1 DLEU2_6 misc_RNA +chr13 50082295 50082484 + ENSG00000276089.1 DLEU1_1 misc_RNA +chr13 50104833 50105174 + ENSG00000273541.1 DLEU1_2 misc_RNA +chr13 51586424 51586532 - ENSG00000206920.1 RNY1P6 misc_RNA +chr13 57632759 57633575 - ENSG00000278722.1 RP11-95F22.1 antisense +chr13 77698012 77698116 - ENSG00000266325.1 MIR3665 miRNA +chr13 90231182 90231277 + ENSG00000207858.1 MIR622 miRNA +chr13 91350605 91350688 + ENSG00000275042.1 MIR17 miRNA +chr13 91350743 91350834 + ENSG00000274160.1 AL162375.1 miRNA +chr13 91350891 91350972 + ENSG00000277328.1 MIR19A miRNA +chr13 91351065 91351135 + ENSG00000275534.1 MIR20A miRNA +chr13 91351192 91351278 + ENSG00000275802.1 MIR19B1 miRNA +chr13 91351314 91351393 + ENSG00000276018.1 MIR92A1 miRNA +chr13 96949249 96949533 - ENSG00000222472.1 RN7SKP7 misc_RNA +chr13 97363007 97363069 - ENSG00000281389.1 AL442067.1 miRNA +chr13 102742990 102745224 + ENSG00000231633.1 LINC00283 antisense +chr13 105459815 105460015 + ENSG00000275968.1 DAOA-AS1_1 misc_RNA +chr13 105462302 105462505 + ENSG00000275502.1 DAOA-AS1_2 misc_RNA +chr13 106567662 106567799 + ENSG00000278371.2 AL442127.1 miRNA +chr14 20343075 20343407 - ENSG00000277209.1 RNaseP_nuc ribozyme +chr14 20474789 20477089 - ENSG00000258908.1 RP11-203M5.8 lincRNA +chr14 21023314 21023386 - ENSG00000278629.1 MIR6717 miRNA +chr14 21521083 21522660 + ENSG00000257096.1 AE000658.22 antisense +chr14 22281105 22281748 + ENSG00000211817.2 TRAV38-2DV8 TR_V_gene +chr14 22450089 22450139 + ENSG00000211825.1 TRDJ1 TR_J_gene +chr14 22509341 22509406 + ENSG00000211857.1 TRAJ32 TR_J_gene +chr14 22956950 22957029 - ENSG00000265037.1 MIR4707 miRNA +chr14 23033530 23033638 - ENSG00000207765.1 AL132780.1 miRNA +chr14 23356406 23357003 + ENSG00000259018.1 RP11-124D2.3 antisense +chr14 24143489 24143565 - ENSG00000276511.1 MIR7703 miRNA +chr14 35809212 35809300 - ENSG00000266264.1 AL162311.1 miRNA +chr14 49577392 49577794 - ENSG00000244270.1 RPL32P29 processed_pseudogene +chr14 49586580 49586878 + ENSG00000276168.1 RN7SL1 misc_RNA +chr14 49586722 49586791 + ENSG00000281893.1 AL139099.3 miRNA +chr14 49620815 49623480 - ENSG00000258377.1 RP11-649E7.5 antisense +chr14 49635000 49635077 + ENSG00000275425.1 AL139099.1 miRNA +chr14 49853703 49853772 - ENSG00000279868.2 AL627171.1 miRNA +chr14 49862638 49862707 - ENSG00000280602.1 AL627171.3 miRNA +chr14 50326526 50327909 - ENSG00000259071.1 RP11-247L20.4 lincRNA +chr14 51967003 51969800 - ENSG00000259007.1 RP11-463J10.3 antisense +chr14 52640839 52641566 + ENSG00000258757.1 RP11-841O20.2 antisense +chr14 52775237 52777740 + ENSG00000259049.1 RP11-589M4.1 antisense +chr14 53036755 53038251 + ENSG00000258985.1 RP11-368P15.3 antisense +chr14 53153049 53153115 - ENSG00000266552.1 AL356020.1 miRNA +chr14 55413556 55414059 - ENSG00000239199.1 RPL21P6 processed_pseudogene +chr14 60972272 60972466 - ENSG00000258656.1 RP11-193F5.4 processed_pseudogene +chr14 60974327 60974435 + ENSG00000206870.1 RNU6-398P snRNA +chr14 63598874 63599248 + ENSG00000258800.1 CTD-2302E22.2 lincRNA +chr14 68887785 68888084 - ENSG00000258967.1 HMGN1P3 processed_pseudogene +chr14 70610086 70610379 + ENSG00000240837.3 RN7SL77P misc_RNA +chr14 73698103 73700351 - ENSG00000258660.1 RP4-693M11.3 antisense +chr14 73885392 73885555 - ENSG00000273711.1 RP5-1021I20.8 antisense +chr14 74480133 74480204 - ENSG00000265649.1 MIR4709 miRNA +chr14 76778952 76782249 + ENSG00000258610.1 RP11-488C13.7 lincRNA +chr14 77266218 77266290 + ENSG00000221754.1 MIR1260A miRNA +chr14 88820297 88820432 + ENSG00000200653.1 RNU4-92P snRNA +chr14 89156743 89157574 + ENSG00000277801.1 RP11-681H18.2 lincRNA +chr14 95185117 95185854 - ENSG00000259143.1 CTD-2240H23.2 sense_overlapping +chr14 95662480 95662598 + ENSG00000275033.1 TCL6_2 misc_RNA +chr14 95670441 95670577 + ENSG00000277468.1 TCL6_3 misc_RNA +chr14 99512501 99513576 + ENSG00000258749.1 RP11-688G15.3 antisense +chr14 100291117 100294656 + ENSG00000258504.2 RP11-638I2.6 lincRNA +chr14 100333790 100354061 + ENSG00000258666.1 RP11-638I2.8 antisense +chr14 100829350 100829454 + ENSG00000276919.1 MEG3_2 misc_RNA +chr14 100834432 100861026 - ENSG00000258663.1 RP11-123M6.2 antisense +chr14 100881007 100881120 + ENSG00000208001.1 MIR431 miRNA +chr14 100881883 100882006 + ENSG00000207569.1 MIR433 miRNA +chr14 100882965 100883075 + ENSG00000207608.2 MIR127 miRNA +chr14 100884483 100884576 + ENSG00000272458.1 MIR432 miRNA +chr14 100884697 100884788 + ENSG00000207942.1 MIR136 miRNA +chr14 100894817 100894913 + ENSG00000276225.1 MEG8_1 misc_RNA +chr14 100898958 100899079 + ENSG00000275134.1 MEG8_2 misc_RNA +chr14 100987046 100987117 + ENSG00000200413.1 SNORD114-26 snoRNA +chr14 101560287 101560422 - ENSG00000277601.1 MIR1247 miRNA +chr14 102501676 102501779 + ENSG00000212330.1 RNU6-244P snRNA +chr14 103725728 103725825 - ENSG00000253096.1 Y_RNA misc_RNA +chr14 104589021 104589847 - ENSG00000259037.1 RP11-614O9.1 antisense +chr14 104769349 104770271 + ENSG00000258430.1 RP11-982M15.2 antisense +chr14 105384360 105384461 - ENSG00000281275.1 AL928654.1 miRNA +chr14 105736956 105737020 + ENSG00000278556.1 AL122127.3 miRNA +chr14 105863198 105863258 - ENSG00000211900.2 IGHJ6 IG_J_gene +chr14 105863814 105863862 - ENSG00000242472.1 IGHJ5 IG_J_gene +chr14 105864215 105864260 - ENSG00000240041.1 IGHJ4 IG_J_gene +chr14 106636704 106636763 + ENSG00000280494.1 AC245369.3 miRNA +chr15 20759311 20774794 - ENSG00000259383.1 RP11-403B2.6 lincRNA +chr15 23565857 23566366 - ENSG00000281873.1 AC126407.1 protein_coding +chr15 24981994 24982068 + ENSG00000276314.1 SNORD107 snoRNA +chr15 24985100 24985166 + ENSG00000276610.1 SNORD64 snoRNA +chr15 24986925 24986995 + ENSG00000239014.1 SNORD108 snoRNA +chr15 25041974 25042040 + ENSG00000274640.1 SNORD109B snoRNA +chr15 25087662 25087753 + ENSG00000278715.1 SNORD116-20 snoRNA +chr15 25088804 25088895 + ENSG00000277785.1 SNORD116-21 snoRNA +chr15 25104642 25104732 + ENSG00000278123.1 SNORD116-28 snoRNA +chr15 25182385 25182466 + ENSG00000278089.1 SNORD115-7 snoRNA +chr15 25193321 25193402 + ENSG00000273835.1 SNORD115-13 snoRNA +chr15 25218617 25218698 + ENSG00000275524.1 SNORD115-26 snoRNA +chr15 28857882 28858398 - ENSG00000270301.1 WI2-2334D6.1 processed_pseudogene +chr15 29233868 29233979 + ENSG00000252868.1 snoZ278 snoRNA +chr15 30380353 30386987 - ENSG00000263070.1 RP11-382B18.3 transcribed_unprocessed_pseudogene +chr15 34373789 34373871 - ENSG00000266205.1 AC025678.1 miRNA +chr15 34978351 34980084 + ENSG00000279364.1 RP11-463I20.1 TEC +chr15 39593580 39594231 - ENSG00000259279.1 CTD-2033D15.1 antisense +chr15 39922782 39922886 - ENSG00000200305.1 Y_RNA misc_RNA +chr15 40088832 40089386 + ENSG00000259409.1 RP11-521C20.3 antisense +chr15 40331537 40331648 - ENSG00000252714.1 RNA5SP392 rRNA +chr15 40368925 40369640 - ENSG00000259368.1 RP11-64K12.4 antisense +chr15 41770756 41772732 - ENSG00000260814.2 RP11-107F6.3 lincRNA +chr15 42531867 42532840 - ENSG00000261684.1 RP11-265N6.1 antisense +chr15 42567031 42569994 - ENSG00000261822.1 RP11-265N6.2 antisense +chr15 42724102 42724922 + ENSG00000278769.1 CTD-2036P10.5 antisense +chr15 42739118 42743202 + ENSG00000246283.2 CTD-2036P10.3 lincRNA +chr15 43793659 43793759 - ENSG00000221792.1 MIR1282 miRNA +chr15 44826540 44827094 + ENSG00000259187.1 CTD-2008A1.1 lincRNA +chr15 45073492 45074048 - ENSG00000259352.1 RP11-109D20.2 antisense +chr15 45214906 45215033 - ENSG00000261709.3 SNORA11 snoRNA +chr15 45433050 45433129 + ENSG00000211519.1 MIR147B miRNA +chr15 48972595 48972727 - ENSG00000280771.1 AC091073.1 miRNA +chr15 50359450 50360194 - ENSG00000259715.1 CTD-3110H11.1 lincRNA +chr15 50360329 50360410 + ENSG00000264109.1 MIR4712 miRNA +chr15 50557601 50560500 + ENSG00000259684.1 RP11-120K9.2 antisense +chr15 51908902 51909642 - ENSG00000259185.1 RP11-56B16.4 antisense +chr15 52116574 52122131 + ENSG00000259327.1 CTD-2184D3.6 lincRNA +chr15 62246284 62246349 - ENSG00000277779.1 AC126323.2 miRNA +chr15 63070025 63071911 - ENSG00000259627.1 RP11-244F12.2 antisense +chr15 64695041 64695594 + ENSG00000265967.1 AC100830.4 antisense +chr15 65077894 65078008 - ENSG00000281328.1 AC013553.1 miRNA +chr15 65655620 65656085 - ENSG00000275638.1 RP11-16E23.5 antisense +chr15 66379337 66379915 - ENSG00000240821.1 RPL9P25 processed_pseudogene +chr15 66501250 66501318 - ENSG00000199574.1 SNORD18C snoRNA +chr15 66502019 66502089 - ENSG00000280554.1 snoU18 snoRNA +chr15 66502020 66502091 - ENSG00000202529.1 SNORD18B snoRNA +chr15 66502812 66502910 - ENSG00000199673.1 SNORD16 snoRNA +chr15 66503243 66503314 - ENSG00000200623.1 SNORD18A snoRNA +chr15 69160651 69160724 + ENSG00000266374.1 AC026512.1 miRNA +chr15 69406441 69406552 + ENSG00000207395.1 Y_RNA misc_RNA +chr15 72587217 72587313 + ENSG00000207690.1 MIR630 miRNA +chr15 72589691 72591845 + ENSG00000260534.1 RP11-1006G14.4 sense_overlapping +chr15 74303005 74304343 + ENSG00000261384.1 RP11-60L3.2 sense_intronic +chr15 74598919 74599397 - ENSG00000275527.1 CTD-3154N5.2 lincRNA +chr15 75211301 75212167 - ENSG00000261779.1 RP11-69H7.3 antisense +chr15 75353611 75353685 - ENSG00000207636.1 MIR631 miRNA +chr15 75355210 75355746 - ENSG00000280564.1 MAN2C1 processed_transcript +chr15 75676227 75677162 + ENSG00000260892.1 CTD-2026K11.1 antisense +chr15 75762215 75762315 - ENSG00000274496.1 MIR4313 miRNA +chr15 77043680 77045160 + ENSG00000259652.1 RP11-797A18.3 lincRNA +chr15 77484275 77485606 - ENSG00000279033.1 RP11-500C12.1 TEC +chr15 78280950 78282190 - ENSG00000272418.1 RP11-762H8.4 sense_intronic +chr15 82044294 82044376 + ENSG00000222521.1 AC026956.1 miRNA +chr15 82477123 82477206 - ENSG00000221095.1 AC245033.1 miRNA +chr15 82726550 82726633 - ENSG00000266697.1 AC105339.2 miRNA +chr15 82755945 82756071 + ENSG00000277864.1 SCARNA15 scaRNA +chr15 82756006 82756069 + ENSG00000280933.1 AC105339.3 miRNA +chr15 83113617 83114566 - ENSG00000260579.1 RP11-382A20.2 antisense +chr15 84204516 84204599 - ENSG00000221008.1 AC136698.1 miRNA +chr15 84622015 84623237 - ENSG00000276278.1 RP11-182J1.3 antisense +chr15 84633874 84634635 + ENSG00000254779.4 EGLN1P1 transcribed_processed_pseudogene +chr15 84642487 84642763 - ENSG00000277578.1 Metazoa_SRP misc_RNA +chr15 85209115 85209198 - ENSG00000221266.1 AC044860.1 miRNA +chr15 85210053 85210299 - ENSG00000277582.1 Metazoa_SRP misc_RNA +chr15 85380596 85380662 + ENSG00000276648.1 MIR7706 miRNA +chr15 85579046 85580178 - ENSG00000259375.1 RP11-815J21.2 antisense +chr15 89201091 89201768 - ENSG00000259948.2 RP11-326A19.5 processed_pseudogene +chr15 89897576 89897637 + ENSG00000252645.1 RNU7-111P snRNA +chr15 90076424 90076486 + ENSG00000276376.1 U7 snRNA +chr15 90275129 90275716 + ENSG00000228998.4 RP11-697E2.7 transcribed_processed_pseudogene +chr15 90294059 90294142 + ENSG00000280965.1 AC091167.2 miRNA +chr15 90348844 90349197 - ENSG00000238244.3 GABARAPL3 processed_pseudogene +chr15 90920218 90921186 - ENSG00000259661.1 AC068831.15 antisense +chr15 91029888 91029996 + ENSG00000258542.1 AC068831.11 transcribed_processed_pseudogene +chr15 96333261 96333307 + ENSG00000222651.1 MIR1469 miRNA +chr15 99791127 99792847 + ENSG00000259655.1 CTD-2054N24.1 unprocessed_pseudogene +chr15 99791209 99791410 + ENSG00000241588.3 RN7SL484P misc_RNA +chr15 99792297 99792379 + ENSG00000221511.1 AC090825.1 miRNA +chr15 101772300 101772381 - ENSG00000277814.1 AC107977.2 miRNA +chr16 547185 553847 - ENSG00000261691.1 LA16c-366D1.3 antisense +chr16 678645 679061 + ENSG00000279441.1 LA16c-313D11.13 TEC +chr16 770183 770277 + ENSG00000207579.1 MIR662 miRNA +chr16 1065240 1066502 + ENSG00000261720.1 RP11-161M6.5 lincRNA +chr16 1445343 1446519 + ENSG00000261641.2 LA16c-390E6.5 antisense +chr16 1962334 1962466 - ENSG00000206811.1 SNORA10 snoRNA +chr16 1962973 1963106 - ENSG00000207405.1 SNORA64 snoRNA +chr16 1963745 1964095 - ENSG00000255513.1 AC005363.9 transcribed_processed_pseudogene +chr16 1965184 1965310 + ENSG00000273587.1 SNORA78 snoRNA +chr16 1997654 1998374 + ENSG00000260107.1 AC005606.15 lincRNA +chr16 2155025 2155104 - ENSG00000281010.1 snoR1 snoRNA +chr16 2211997 2212863 + ENSG00000261532.1 RP11-304L19.8 lincRNA +chr16 2253737 2262342 + ENSG00000279473.1 AC009065.4 protein_coding +chr16 2271737 2271846 + ENSG00000274753.1 MIR940 miRNA +chr16 2530035 2531417 - ENSG00000205923.3 CEMP1 protein_coding +chr16 2597881 2599718 - ENSG00000261093.1 CTD-3126B10.1 antisense +chr16 2769872 2769949 + ENSG00000265864.1 AC092117.2 miRNA +chr16 3069523 3069651 + ENSG00000252561.1 RNU1-125P snRNA +chr16 3307573 3308393 - ENSG00000262899.1 LA16c-360H6.3 antisense +chr16 3308609 3308816 + ENSG00000262554.1 LA16c-360H6.2 transcribed_processed_pseudogene +chr16 3485381 3485469 - ENSG00000273776.1 MIR6126 miRNA +chr16 3533429 3534258 - ENSG00000278942.1 LA16c-390H2.1 TEC +chr16 3581181 3583266 + ENSG00000261938.1 RP11-461A8.1 lincRNA +chr16 8683461 8683543 + ENSG00000281170.1 AC007224.1 miRNA +chr16 8853312 8854347 + ENSG00000259939.1 RP11-77H9.5 antisense +chr16 9104848 9113181 + ENSG00000263244.2 RP11-473I1.9 3prime_overlapping_ncrna +chr16 9105834 9107174 - ENSG00000260349.1 RP11-473I1.5 antisense +chr16 10529440 10532082 + ENSG00000256013.1 RP11-27M24.1 antisense +chr16 10934258 10934887 - ENSG00000275673.1 RP11-876N24.7 sense_intronic +chr16 11345483 11345560 - ENSG00000280717.1 AC009121.2 protein_coding +chr16 11348727 11348796 + ENSG00000238774.1 AC009121.1 miRNA +chr16 11915661 11915738 - ENSG00000266163.1 AC007216.1 miRNA +chr16 14901508 14901591 + ENSG00000274301.1 MIR3179-3 miRNA +chr16 14911220 14911313 + ENSG00000265537.1 MIR3180-3 miRNA +chr16 15611030 15611095 - ENSG00000275184.1 MIR6506 miRNA +chr16 15643281 15643390 + ENSG00000272213.2 AC026401.1 miRNA +chr16 16309875 16309968 + ENSG00000265373.1 MIR3180-1 miRNA +chr16 18402178 18402271 - ENSG00000266291.1 MIR3180-2 miRNA +chr16 19119976 19121629 - ENSG00000261759.1 RP11-626G11.3 antisense +chr16 19498610 19498747 + ENSG00000222750.1 RNU4-46P snRNA +chr16 19501689 19502286 + ENSG00000260934.1 CTA-363E6.7 antisense +chr16 19503861 19504625 + ENSG00000279747.1 CTA-363E6.8 TEC +chr16 21519830 21520365 - ENSG00000258186.2 SLC7A5P2 transcribed_processed_pseudogene +chr16 23061406 23064173 - ENSG00000260566.2 RP11-20G6.3 3prime_overlapping_ncrna +chr16 23061767 23062232 + ENSG00000280400.1 RP11-20G6.1 TEC +chr16 23571854 23572278 - ENSG00000279618.1 CTD-2196E14.7 TEC +chr16 23670011 23675499 + ENSG00000260482.3 CTD-2196E14.9 3prime_overlapping_ncrna +chr16 25238318 25239287 + ENSG00000259955.1 CTD-2547G23.2 antisense +chr16 27066928 27067858 - ENSG00000261482.1 RP11-673P17.2 antisense +chr16 28958583 28958661 + ENSG00000266868.1 MIR4517 miRNA +chr16 28982014 28982130 + ENSG00000281146.1 AC109460.1 miRNA +chr16 28989140 28990778 - ENSG00000261552.1 RP11-264B17.5 antisense +chr16 29804430 29804990 - ENSG00000275857.1 AC009133.21 antisense +chr16 29862760 29863417 + ENSG00000278713.1 CTD-2574D22.7 antisense +chr16 30064306 30064825 - ENSG00000274904.1 CTD-2515O10.5 antisense +chr16 30670160 30670297 + ENSG00000280843.1 AC093249.1 miRNA +chr16 30875266 30875323 - ENSG00000265991.1 MIR4519 miRNA +chr16 30875766 30895216 - ENSG00000262721.1 AC106782.20 sense_overlapping +chr16 30893903 30893985 + ENSG00000211591.1 MIR762 miRNA +chr16 31109211 31109318 + ENSG00000252809.3 AC135050.1 miRNA +chr16 31131433 31131877 + ENSG00000261385.1 RP11-388M20.2 antisense +chr16 31709113 31711984 - ENSG00000261731.2 CTD-2358C21.4 antisense +chr16 34159185 34159299 + ENSG00000207986.1 AC136932.1 miRNA +chr16 35023339 35023765 + ENSG00000262885.1 CTD-2144E22.11 processed_pseudogene +chr16 35149457 35149790 - ENSG00000261510.1 RP11-244B22.13 processed_pseudogene +chr16 35193335 35193734 + ENSG00000260590.1 RP11-244B22.7 processed_pseudogene +chr16 48447904 48448398 - ENSG00000261802.1 RP11-44I10.6 sense_overlapping +chr16 54114697 54114878 - ENSG00000280454.1 AC007347.1 pseudogene +chr16 58559796 58559929 - ENSG00000206952.3 SNORA76A snoRNA +chr16 66509437 66510048 + ENSG00000260755.1 RP11-403P17.3 lincRNA +chr16 66550457 66550567 + ENSG00000275745.1 Y_RNA misc_RNA +chr16 66720897 66731785 + ENSG00000260465.1 RP11-63M22.2 antisense +chr16 66944660 66945096 - ENSG00000280416.1 RP11-361L15.3 TEC +chr16 67019727 67019811 + ENSG00000281589.1 AC009084.1 miRNA +chr16 67390691 67390850 - ENSG00000239194.1 RNU1-123P snRNA +chr16 67542123 67542963 - ENSG00000259945.1 CTD-2012K14.3 antisense +chr16 67542304 67542572 - ENSG00000260894.1 CTD-2012K14.4 antisense +chr16 67877657 67877740 + ENSG00000221526.1 AC040162.1 miRNA +chr16 68199841 68200981 - ENSG00000279621.1 RP11-67A1.4 TEC +chr16 68233426 68233499 - ENSG00000276151.1 MIR6773 miRNA +chr16 68742495 68742551 + ENSG00000281454.1 AC099314.1 miRNA +chr16 69328644 69334871 - ENSG00000272617.1 RP11-343C2.12 protein_coding +chr16 69463844 69466264 + ENSG00000260108.1 RP11-140H17.1 3prime_overlapping_ncrna +chr16 69565808 69565868 - ENSG00000223109.1 MIR1538 miRNA +chr16 69703065 69704652 + ENSG00000260772.1 RP11-311C24.1 3prime_overlapping_ncrna +chr16 69709874 69710583 + ENSG00000261602.1 CTD-2033A16.1 antisense +chr16 70379457 70399502 + ENSG00000260111.1 RP11-529K1.4 antisense +chr16 70768967 70770221 - ENSG00000279122.1 RP11-394B2.3 TEC +chr16 72787693 72787773 - ENSG00000265573.1 AC004943.1 miRNA +chr16 75108601 75110712 - ENSG00000247033.1 RP11-252E2.1 antisense +chr16 81170740 81181213 - ENSG00000279362.1 PKD1L2 protein_coding +chr16 81385018 81385093 + ENSG00000273048.1 MIR4720 miRNA +chr16 81385463 81387560 + ENSG00000272923.1 RP11-391L3.1 lincRNA +chr16 81961926 81962243 + ENSG00000260682.3 7SK misc_RNA +chr16 86510780 86510877 - ENSG00000277360.1 AC009108.2 miRNA +chr16 87326987 87327584 + ENSG00000270082.1 RP11-178L8.8 antisense +chr16 88686544 88687053 - ENSG00000280603.1 AC138028.1 protein_coding +chr16 89226807 89228692 - ENSG00000260659.1 RP11-46C24.6 antisense +chr16 89561434 89561517 + ENSG00000200084.1 SNORD68 snoRNA +chr17 1713895 1714005 - ENSG00000275595.1 AC130343.2 miRNA +chr17 1725748 1738585 - ENSG00000262791.1 RP11-961A15.1 antisense +chr17 2041936 2043430 + ENSG00000262664.2 OVCA2 protein_coding +chr17 2042900 2043425 - ENSG00000262533.1 RP11-667K14.4 antisense +chr17 2329119 2329213 - ENSG00000212552.3 SNORD91B snoRNA +chr17 2330276 2330370 - ENSG00000274802.1 SNORD91A snoRNA +chr17 2366589 2366791 - ENSG00000274758.1 RP1-59D14.10 antisense +chr17 2384847 2386664 + ENSG00000262456.1 RP1-59D14.1 antisense +chr17 2683305 2685088 - ENSG00000272770.1 RP11-74E22.5 antisense +chr17 2748078 2748182 - ENSG00000221200.1 MIR1253 miRNA +chr17 2748078 2748182 + ENSG00000272920.1 MIR1253 lincRNA +chr17 3310312 3311189 + ENSG00000180068.8 OR3A4P transcribed_unprocessed_pseudogene +chr17 4163910 4164713 + ENSG00000263165.1 RP11-810M2.2 antisense +chr17 5514209 5514270 - ENSG00000280489.1 U7 snRNA +chr17 6651914 6652270 + ENSG00000279257.1 C17orf100 protein_coding +chr17 7017615 7017701 - ENSG00000275739.1 MIR195 miRNA +chr17 7017911 7018022 - ENSG00000273895.1 MIR497 miRNA +chr17 7352687 7354944 - ENSG00000263171.1 RP11-542C16.1 antisense +chr17 7436557 7437523 - ENSG00000262624.1 RP11-104H15.9 antisense +chr17 7439159 7443327 - ENSG00000263301.1 RP11-104H15.8 antisense +chr17 7574713 7574847 + ENSG00000209582.1 SNORA48 snoRNA +chr17 7576811 7576952 + ENSG00000238917.1 SNORD10 snoRNA +chr17 7577955 7578091 + ENSG00000277985.1 SNORA67 snoRNA +chr17 8144994 8145071 - ENSG00000278027.1 MIR6883 miRNA +chr17 8173454 8173587 - ENSG00000200463.1 SNORD118 snoRNA +chr17 8188933 8189688 + ENSG00000279152.1 AC129492.1 protein_coding +chr17 12990149 12990610 - ENSG00000263707.1 RP11-597M12.1 antisense +chr17 15588852 15589084 + ENSG00000223544.1 AC005838.2 unprocessed_pseudogene +chr17 16044621 16044961 + ENSG00000243686.2 RPLP1P11 processed_pseudogene +chr17 16382152 16382669 - ENSG00000265401.1 RP11-138I1.4 antisense +chr17 16439505 16439576 + ENSG00000277108.1 SNORD49 snoRNA +chr17 16440036 16440106 + ENSG00000277370.1 SNORD49A snoRNA +chr17 16441226 16441298 + ENSG00000277512.1 SNORD65 snoRNA +chr17 16812447 16812651 + ENSG00000264892.1 NOS2P4 processed_pseudogene +chr17 17242564 17242647 + ENSG00000265109.1 AC055811.1 miRNA +chr17 17675366 17675522 + ENSG00000273948.1 SMCR2_1 misc_RNA +chr17 17676211 17676371 + ENSG00000274836.1 SMCR2_2 misc_RNA +chr17 17777781 17779094 + ENSG00000264167.1 RP1-253P7.1 sense_intronic +chr17 18340814 18340886 - ENSG00000275820.1 MIR6778 miRNA +chr17 18388871 18389459 + ENSG00000267441.1 RP1-37N7.5 processed_pseudogene +chr17 19061912 19062128 + ENSG00000280523.1 SNORD3B-2 snoRNA +chr17 19061912 19062129 + ENSG00000276271.1 SNORD3B-2 snoRNA +chr17 19063919 19064136 - ENSG00000274088.1 SNORD3B-1 snoRNA +chr17 19063920 19064136 - ENSG00000281187.1 SNORD3B-2 snoRNA +chr17 19112419 19112636 - ENSG00000277947.1 SNORD3D snoRNA +chr17 19112420 19112636 - ENSG00000281000.1 SNORD3D snoRNA +chr17 19188016 19188232 + ENSG00000281298.1 SNORD3A snoRNA +chr17 19188016 19188233 + ENSG00000277813.1 SNORD3A snoRNA +chr17 19190028 19190245 - ENSG00000275303.1 SNORD3C snoRNA +chr17 19190029 19190245 - ENSG00000280847.1 SNORD3C snoRNA +chr17 19334308 19336127 - ENSG00000265263.1 RP11-135L13.4 antisense +chr17 19557560 19557711 + ENSG00000276660.1 SNORA59A snoRNA +chr17 19649494 19649587 - ENSG00000275982.1 Y_RNA misc_RNA +chr17 20981489 20981654 + ENSG00000266009.1 RP11-746M1.2 transcribed_processed_pseudogene +chr17 20999747 21000323 + ENSG00000263986.1 RP11-746M1.1 antisense +chr17 21457434 21458989 + ENSG00000264023.1 RP11-728E14.2 lincRNA +chr17 22411893 22412229 - ENSG00000266746.1 RP11-1109M24.7 processed_pseudogene +chr17 22435629 22436064 + ENSG00000265705.1 RP11-744K17.8 transcribed_processed_pseudogene +chr17 22528853 22528921 - ENSG00000241225.2 NMTRS-TGA3-1 unprocessed_pseudogene +chr17 27625484 27626438 - ENSG00000266872.1 RP11-19P22.8 antisense +chr17 28276463 28276553 - ENSG00000207844.1 AC061975.1 miRNA +chr17 28360654 28360734 + ENSG00000264302.1 MIR4723 miRNA +chr17 28361601 28362859 - ENSG00000265618.1 CTB-96E2.7 antisense +chr17 28655557 28655983 + ENSG00000240494.2 RPS12P28 processed_pseudogene +chr17 28722582 28722653 + ENSG00000238578.1 SNORD4A snoRNA +chr17 28723429 28723492 + ENSG00000238649.1 SNORD42A snoRNA +chr17 28723682 28723753 + ENSG00000238597.1 SNORD4B snoRNA +chr17 28749731 28750079 - ENSG00000265840.1 AC010761.10 antisense +chr17 28861369 28861440 - ENSG00000273915.1 MIR451A miRNA +chr17 28861514 28861624 - ENSG00000277441.1 AC024267.1 miRNA +chr17 28861655 28861730 - ENSG00000278521.1 MIR4732 miRNA +chr17 29390662 29390730 + ENSG00000263719.1 MIR4523 miRNA +chr17 30059054 30059147 - ENSG00000267482.1 RNY4P13 unprocessed_pseudogene +chr17 30117079 30117172 + ENSG00000199071.2 MIR423 miRNA +chr17 30117079 30117172 - ENSG00000266919.1 MIR3184 sense_intronic +chr17 30557732 30558502 - ENSG00000266775.1 RP11-218M11.6 antisense +chr17 30702506 30702586 - ENSG00000281673.1 AC005562.2 miRNA +chr17 30899110 30899651 + ENSG00000275185.1 RP13-753N3.3 antisense +chr17 31533171 31533938 - ENSG00000278977.1 RP1-41C23.2 TEC +chr17 31534883 31534971 + ENSG00000266459.1 MIR4724 miRNA +chr17 35097560 35097657 - ENSG00000252328.1 Vault misc_RNA +chr17 36491199 36491322 - ENSG00000274164.1 5S_rRNA rRNA +chr17 37609739 37613841 + ENSG00000277688.1 RP11-697E22.1 antisense +chr17 38727833 38728198 - ENSG00000279119.1 AC006449.2 protein_coding +chr17 38851524 38851659 - ENSG00000252699.1 SNORA21 snoRNA +chr17 38852863 38852994 - ENSG00000199293.1 SNORA21 snoRNA +chr17 38918801 38921769 - ENSG00000265784.1 RP1-56K13.3 antisense +chr17 39081065 39081187 + ENSG00000222494.1 AC091178.1 miRNA +chr17 40026332 40026409 - ENSG00000275267.1 MIR6884 miRNA +chr17 41500983 41502409 + ENSG00000229732.1 AC019349.5 antisense +chr17 41867581 41867736 + ENSG00000274630.1 RP11-229E13.4 antisense +chr17 43387226 43387417 - ENSG00000277084.1 U2 snRNA +chr17 43444806 43444885 + ENSG00000278547.1 MIR2117 miRNA +chr17 44123539 44123649 - ENSG00000274433.1 AC023855.1 miRNA +chr17 44303965 44304203 + ENSG00000221496.2 U3 snoRNA +chr17 44899712 44905390 + ENSG00000214447.4 FAM187A protein_coding +chr17 44903161 44904546 - ENSG00000224911.1 AC015936.3 antisense +chr17 45637110 45637206 + ENSG00000273917.1 AC126544.1 miRNA +chr17 46537734 46537813 + ENSG00000280583.1 AC138645.1 miRNA +chr17 46939155 46939860 - ENSG00000280158.1 RP11-63A1.4 TEC +chr17 47042025 47042104 + ENSG00000281864.1 AC068152.1 miRNA +chr17 47118502 47118591 + ENSG00000221016.1 AC002558.1 miRNA +chr17 47682417 47682683 - ENSG00000264558.1 RP11-138C9.1 antisense +chr17 47946802 47948275 - ENSG00000264019.1 RP11-6N17.6 antisense +chr17 48048365 48048430 + ENSG00000273862.1 AC004477.1 miRNA +chr17 48060383 48060669 - ENSG00000266341.1 RP5-890E16.4 antisense +chr17 48382371 48382586 - ENSG00000200538.2 U3 snoRNA +chr17 48579838 48579947 - ENSG00000274592.1 MIR10A miRNA +chr17 48724408 48724475 - ENSG00000263602.1 MIR3185 miRNA +chr17 48931791 48937100 + ENSG00000230532.1 AC091133.1 antisense +chr17 49049540 49049624 + ENSG00000264552.1 AC105030.1 miRNA +chr17 49404081 49405197 + ENSG00000250186.3 RP11-1079K10.4 antisense +chr17 50693448 50695449 + ENSG00000262967.1 RP11-294J22.6 antisense +chr17 50840057 50841626 - ENSG00000261976.2 RP11-506D12.5 antisense +chr17 51166831 51171507 + ENSG00000280803.1 NME1-NME2 protein_coding +chr17 53106069 53106157 - ENSG00000276078.1 AC091154.1 miRNA +chr17 56888880 56891841 + ENSG00000262112.1 RP11-670E13.5 antisense +chr17 56891270 56891355 - ENSG00000265238.1 MIR3614 miRNA +chr17 58331215 58331325 - ENSG00000273667.1 AC004687.1 miRNA +chr17 59841266 59841337 + ENSG00000199004.1 MIR21 miRNA +chr17 60810957 60811052 + ENSG00000211515.1 AC079005.1 miRNA +chr17 62005737 62006016 - ENSG00000242398.3 RN7SL800P misc_RNA +chr17 64146337 64146471 + ENSG00000281311.1 SNORA76C snoRNA +chr17 64146339 64146471 + ENSG00000277887.1 SNORA76C snoRNA +chr17 64500773 64500839 - ENSG00000265695.1 MIR3064 miRNA +chr17 64501214 64501313 - ENSG00000266241.1 MIR5047 miRNA +chr17 64749918 64758603 - ENSG00000266820.1 RP13-104F24.1 transcribed_unprocessed_pseudogene +chr17 64780759 64780824 + ENSG00000278581.1 MIR6080 miRNA +chr17 64940606 64940717 + ENSG00000272346.2 RP11-927P21.11 transcribed_unprocessed_pseudogene +chr17 67032409 67033290 - ENSG00000265664.1 RP11-74H8.1 antisense +chr17 68134675 68135604 - ENSG00000267352.1 SH3GL1P3 processed_pseudogene +chr17 74748613 74748699 + ENSG00000264624.1 MIR3615 miRNA +chr17 75041740 75042015 + ENSG00000239607.3 RN7SL573P misc_RNA +chr17 75145670 75145762 + ENSG00000252042.1 Y_RNA misc_RNA +chr17 75498548 75498628 + ENSG00000276372.1 MIR6785 miRNA +chr17 75784521 75784607 - ENSG00000263565.1 MIR4738 miRNA +chr17 75910723 75938149 - ENSG00000281844.1 FBF1 protein_coding +chr17 75943832 75945142 + ENSG00000267615.1 RP11-552F3.13 antisense +chr17 76558791 76558868 + ENSG00000274091.1 SNORD1C snoRNA +chr17 76561634 76561705 + ENSG00000278261.1 SNORD1A snoRNA +chr17 76736450 76736548 - ENSG00000207556.1 MIR636 miRNA +chr17 77089307 77089493 + ENSG00000275143.1 SCARNA16 scaRNA +chr17 77089417 77089497 + ENSG00000281678.1 MIR6516 miRNA +chr17 78855478 78855844 + ENSG00000267601.1 RP11-323N12.5 antisense +chr17 80999509 81000130 - ENSG00000263218.2 CTD-2561B21.7 antisense +chr17 81251194 81251803 + ENSG00000276101.1 RP11-455O6.8 antisense +chr17 81461013 81461937 - ENSG00000263271.1 RP11-1055B8.8 antisense +chr17 81511026 81511109 - ENSG00000266077.1 AC139149.1 miRNA +chr17 81697025 81697714 - ENSG00000275902.1 RP13-1032I1.11 antisense +chr17 81843165 81843958 + ENSG00000262831.1 RP11-498C9.2 antisense +chr17 81867721 81868552 + ENSG00000262413.1 RP11-498C9.3 antisense +chr17 81878667 81879557 + ENSG00000263859.1 RP11-498C9.16 lincRNA +chr17 81932398 81933058 + ENSG00000263585.1 RP11-498C9.13 antisense +chr17 82236668 82236728 + ENSG00000275505.1 MIR6787 miRNA +chr17 82362349 82363196 - ENSG00000278964.1 RP13-20L14.2 TEC +chr17 82602989 82604178 - ENSG00000261845.2 RP13-638C3.4 antisense +chr18 738058 739444 + ENSG00000264339.1 RP11-769O8.2 antisense +chr18 3246401 3247086 - ENSG00000272688.1 RP13-270P17.3 lincRNA +chr18 5240255 5241167 - ENSG00000265188.1 RP11-835E18.4 processed_pseudogene +chr18 11851414 11852751 - ENSG00000267165.1 RP11-78A19.3 antisense +chr18 11908712 11909223 + ENSG00000273141.1 RP11-820I16.4 antisense +chr18 14074912 14075741 - ENSG00000267756.1 RP11-411B10.4 unprocessed_pseudogene +chr18 14104542 14105226 + ENSG00000267356.1 RP11-411B10.3 antisense +chr18 21712017 21712119 - ENSG00000281568.1 AC106037.1 miRNA +chr18 21825698 21825785 - ENSG00000276792.1 MIR133A1 miRNA +chr18 21828996 21829106 - ENSG00000278753.1 AC103987.1 miRNA +chr18 22933349 22933438 + ENSG00000264817.1 MIR4741 miRNA +chr18 23136435 23136512 - ENSG00000222999.1 AC105247.1 miRNA +chr18 26688111 26689668 + ENSG00000263677.1 RP11-17A19.2 lincRNA +chr18 26689316 26689529 - ENSG00000275900.1 U3 snoRNA +chr18 27452623 27452712 - ENSG00000280492.1 AC068408.1 miRNA +chr18 31726043 31726397 - ENSG00000263772.1 RP11-549B18.3 processed_pseudogene +chr18 35466938 35466991 - ENSG00000277489.1 AC007998.1 miRNA +chr18 49487373 49487422 + ENSG00000278544.1 MIR1539 miRNA +chr18 49489245 49489308 - ENSG00000202093.1 SNORD58C snoRNA +chr18 49491283 49491347 - ENSG00000206602.1 SNORD58A snoRNA +chr18 49491664 49491729 - ENSG00000271982.1 SNORD58B snoRNA +chr18 49814133 49814276 + ENSG00000251992.1 SCARNA17 scaRNA +chr18 49814361 49814443 + ENSG00000252139.1 SCARNA18 scaRNA +chr18 57435821 57435880 + ENSG00000266636.1 AC090340.1 miRNA +chr18 58398663 58400082 - ENSG00000267396.1 RP11-845C23.3 antisense +chr18 58451068 58451176 + ENSG00000207778.2 MIR122 miRNA +chr18 58752179 58753898 - ENSG00000267705.1 RP11-108P20.3 lincRNA +chr18 67506589 67514030 + ENSG00000263424.1 CTD-2541J13.2 antisense +chr18 79253577 79254856 - ENSG00000267628.1 RP11-1136J12.1 antisense +chr19 305573 306467 + ENSG00000267124.2 CTD-3113P16.5 antisense +chr19 804940 805001 + ENSG00000265767.1 MIR4745 miRNA +chr19 813584 813653 + ENSG00000263414.1 MIR3187 miRNA +chr19 1010221 1010907 + ENSG00000274177.1 LLNLR-284B4.1 antisense +chr19 1038727 1039064 - ENSG00000279753.1 AC011558.5 TEC +chr19 1376773 1377520 - ENSG00000267755.1 AC004623.2 antisense +chr19 1556605 1556686 + ENSG00000222720.1 AC027307.1 miRNA +chr19 1576939 1577086 + ENSG00000279009.1 AC005943.6 TEC +chr19 1815249 1815873 + ENSG00000267007.1 CTB-31O20.3 antisense +chr19 1816159 1816238 - ENSG00000223244.1 MIR1909 miRNA +chr19 1875016 1875992 + ENSG00000267232.1 CTB-31O20.9 lincRNA +chr19 2235829 2235926 - ENSG00000276587.1 MIR6789 miRNA +chr19 2250639 2250718 + ENSG00000267021.1 MIR4321 miRNA +chr19 3052910 3053724 + ENSG00000267469.1 AC005944.2 antisense +chr19 3118665 3119304 - ENSG00000267139.1 AC005262.3 antisense +chr19 3121116 3122128 - ENSG00000267688.1 AC005262.2 antisense +chr19 3544199 3557569 + ENSG00000267436.1 AC005786.7 antisense +chr19 3961414 3961512 - ENSG00000207733.1 MIR637 miRNA +chr19 4445978 4446048 + ENSG00000266437.1 MIR4746 miRNA +chr19 4447304 4448217 + ENSG00000267030.1 CTB-50L17.7 antisense +chr19 4652171 4652283 - ENSG00000280849.1 AC005339.1 miRNA +chr19 4654964 4655524 - ENSG00000268565.1 AC005339.2 antisense +chr19 4791745 4795559 - ENSG00000269604.1 AC005523.2 antisense +chr19 6176256 6176442 - ENSG00000267415.1 CTC-503J8.2 transcribed_processed_pseudogene +chr19 6494320 6494805 + ENSG00000268203.1 CTD-2396E7.9 antisense +chr19 6494320 6495025 + ENSG00000268191.1 CTD-2396E7.10 antisense +chr19 6736712 6736778 - ENSG00000277714.1 MIR6791 miRNA +chr19 7519916 7520460 - ENSG00000269371.1 CTD-2207O23.11 antisense +chr19 7870561 7871296 + ENSG00000268120.1 CTD-3193O13.11 lincRNA +chr19 7912648 7913518 - ENSG00000268149.1 CTD-3193O13.13 antisense +chr19 7959123 7960012 + ENSG00000269813.1 CTD-3193O13.14 antisense +chr19 10286967 10288522 + ENSG00000105371.8 ICAM4 protein_coding +chr19 10403458 10403538 - ENSG00000221566.1 MIR1181 miRNA +chr19 11322156 11324195 + ENSG00000267576.1 CTC-510F12.6 sense_intronic +chr19 12379746 12383687 - ENSG00000248406.1 CTD-3105H18.4 transcribed_unprocessed_pseudogene +chr19 12688922 12689238 + ENSG00000267791.1 CTD-2659N19.2 antisense +chr19 12796823 12801849 + ENSG00000267062.1 CTD-2659N19.10 antisense +chr19 12944118 12944487 - ENSG00000267458.1 CTC-425F1.4 antisense +chr19 13153071 13154193 - ENSG00000267598.1 CTC-250I14.6 antisense +chr19 14073361 14073479 + ENSG00000277805.1 MIR1199 miRNA +chr19 14163039 14163183 + ENSG00000281044.1 AC022098.2 miRNA +chr19 14213241 14213321 + ENSG00000280955.1 AC011509.1 miRNA +chr19 14402717 14408723 - ENSG00000267379.1 CTC-548K16.5 antisense +chr19 14529543 14529640 + ENSG00000207707.1 MIR639 miRNA +chr19 15449548 15449608 + ENSG00000269782.1 MIR1470 miRNA +chr19 15834730 15834804 + ENSG00000273782.1 UCA1 misc_RNA +chr19 16551773 16552328 + ENSG00000268309.1 CTD-3222D19.11 antisense +chr19 16565551 16566330 + ENSG00000269085.1 CTD-3222D19.10 antisense +chr19 16586905 16587985 - ENSG00000269578.1 CTD-3222D19.5 sense_intronic +chr19 16910496 16910579 - ENSG00000280536.1 AC008737.1 miRNA +chr19 17419305 17419774 - ENSG00000269053.1 CTD-2521M24.8 antisense +chr19 17727840 17734513 - ENSG00000268112.1 CTD-3149D2.4 antisense +chr19 17862588 17862720 + ENSG00000207166.1 SNORA68 snoRNA +chr19 18009440 18009881 - ENSG00000279172.1 CTB-52I2.7 TEC +chr19 18144522 18151691 - ENSG00000269145.2 AC007192.6 antisense +chr19 18448275 18448802 + ENSG00000279262.1 CTD-3137H5.5 TEC +chr19 18568506 18569375 - ENSG00000268983.1 AC005253.4 antisense +chr19 18868545 18896096 - ENSG00000130283.8 GDF1 protein_coding +chr19 19255638 19256141 + ENSG00000280282.1 LLNLR-259H9.1 TEC +chr19 20125044 20125484 + ENSG00000224864.4 CTC-260E6.2 transcribed_processed_pseudogene +chr19 21188598 21188953 + ENSG00000268995.1 VN1R82P unprocessed_pseudogene +chr19 21592727 21593041 + ENSG00000274503.1 RP11-678G14.6 unprocessed_pseudogene +chr19 21753011 21753083 + ENSG00000265084.1 AC092364.1 miRNA +chr19 22601485 22601707 + ENSG00000240713.3 RN7SL860P misc_RNA +chr19 33207129 33207639 + ENSG00000273420.1 CTD-2540B15.13 3prime_overlapping_ncrna +chr19 33299934 33301168 + ENSG00000267580.1 CTD-2540B15.11 antisense +chr19 33301279 33301940 + ENSG00000267727.1 CTD-2540B15.7 antisense +chr19 34645662 34646070 + ENSG00000269811.2 SCGB2B3P processed_pseudogene +chr19 35122700 35122764 + ENSG00000278663.1 MIR6887 miRNA +chr19 36114362 36115146 + ENSG00000279504.1 AD001527.4 TEC +chr19 38385522 38386759 + ENSG00000267090.1 AC005789.9 antisense +chr19 41425359 41426237 + ENSG00000268475.1 CTC-435M10.6 antisense +chr19 41605341 41605671 - ENSG00000269266.1 DNAJC19P2 processed_pseudogene +chr19 42078588 42080107 - ENSG00000268525.1 CTB-59C6.3 antisense +chr19 42424384 42425071 - ENSG00000268605.1 CTB-50E14.4 sense_intronic +chr19 44758657 44758721 + ENSG00000277736.1 MIR8085 miRNA +chr19 45149750 45150605 - ENSG00000267037.1 AC005757.7 lincRNA +chr19 45638994 45639087 - ENSG00000199066.1 MIR330 miRNA +chr19 45938139 45938282 - ENSG00000280818.1 AC008623.1 miRNA +chr19 46382492 46383169 - ENSG00000268810.1 AC007193.9 antisense +chr19 46390515 46390852 - ENSG00000269151.1 AC007193.8 antisense +chr19 46609277 46610779 - ENSG00000269292.1 CTB-12A17.3 antisense +chr19 47226942 47227021 + ENSG00000265134.1 MIR3190 miRNA +chr19 47581231 47581313 + ENSG00000281476.1 AC010331.1 miRNA +chr19 47755853 47755962 + ENSG00000221803.1 SNORD23 snoRNA +chr19 48966694 48966775 - ENSG00000281206.1 AC026803.1 miRNA +chr19 49489965 49490048 + ENSG00000201675.1 SNORD32A snoRNA +chr19 49490615 49490699 + ENSG00000199631.1 SNORD33 snoRNA +chr19 49490904 49490974 + ENSG00000202503.1 SNORD34 snoRNA +chr19 49491175 49491260 + ENSG00000200259.1 SNORD35A snoRNA +chr19 49497720 49497806 + ENSG00000200530.1 SNORD35B snoRNA +chr19 49625994 49626439 - ENSG00000268636.1 CTB-33G10.11 antisense +chr19 49688853 49690573 - ENSG00000268677.1 CTB-33G10.6 antisense +chr19 49832018 49832099 + ENSG00000277609.1 MIR6800 miRNA +chr19 49888175 49888230 + ENSG00000263462.1 MIR4750 miRNA +chr19 49933064 49933137 + ENSG00000265438.1 MIR4751 miRNA +chr19 49949316 49949527 - ENSG00000221125.2 U3 snoRNA +chr19 50310022 50310539 - ENSG00000267815.1 CTB-191K22.5 antisense +chr19 50480119 50483351 - ENSG00000268854.1 CTD-2545M3.2 antisense +chr19 50486810 50487638 - ENSG00000268518.1 CTD-2545M3.8 lincRNA +chr19 50799032 50799122 - ENSG00000221381.1 SNORD88B snoRNA +chr19 50802328 50802418 - ENSG00000220988.1 SNORD88C snoRNA +chr19 51014374 51014734 + ENSG00000268739.1 CTC-518B2.12 antisense +chr19 51692773 51692881 + ENSG00000198972.2 MIRLET7E miRNA +chr19 51693254 51693339 + ENSG00000208008.1 MIR125A miRNA +chr19 52564076 52564231 + ENSG00000242255.1 RPL39P34 transcribed_unprocessed_pseudogene +chr19 53162428 53163563 + ENSG00000268842.1 CTD-2245F17.2 antisense +chr19 53386233 53386388 + ENSG00000241069.1 CTD-3141N22.1 transcribed_processed_pseudogene +chr19 53426019 53426499 - ENSG00000249435.1 CTD-2224J9.7 processed_pseudogene +chr19 53495887 53496037 + ENSG00000241434.1 CTD-2224J9.4 transcribed_processed_pseudogene +chr19 53762335 53762445 + ENSG00000280835.1 AC011453.2 miRNA +chr19 53787675 53787741 + ENSG00000199031.1 MIR371A miRNA +chr19 53787890 53787956 + ENSG00000199095.1 MIR372 miRNA +chr19 53874626 53876049 - ENSG00000232220.2 AC008440.5 antisense +chr19 53982307 53982397 + ENSG00000215998.1 MIR935 miRNA +chr19 54589441 54590287 + ENSG00000269271.1 CTB-83J4.2 lincRNA +chr19 55312029 55312495 - ENSG00000268729.1 CTD-2105E13.14 antisense +chr19 55388181 55388242 + ENSG00000277326.1 MIR6805 miRNA +chr19 55705978 55706172 - ENSG00000267689.1 AC010525.5 processed_pseudogene +chr19 55707550 55707855 + ENSG00000268593.3 CTD-2611O12.6 processed_pseudogene +chr19 56316524 56316636 - ENSG00000200646.1 Y_RNA misc_RNA +chr19 56377037 56377792 - ENSG00000267459.1 AC006116.27 transcribed_processed_pseudogene +chr19 56547105 56547241 + ENSG00000281545.1 AC005498.1 miRNA +chr19 56840905 56840992 + ENSG00000281440.1 MIMT1_1 sRNA +chr19 56848068 56848204 + ENSG00000274777.1 MIMT1_2 misc_RNA +chr19 58310917 58311002 - ENSG00000264333.1 AC020915.1 miRNA +chr19 58475355 58475763 - ENSG00000269106.1 CTD-2619J13.23 antisense +chr19 58582024 58582609 + ENSG00000268784.1 MGC2752 transcribed_unprocessed_pseudogene +chr19 58586158 58586356 + ENSG00000269032.1 AC016629.7 transcribed_processed_pseudogene +chr20 1392900 1392961 - ENSG00000276741.1 MIR6869 miRNA +chr20 2652777 2652842 + ENSG00000221062.1 MIR1292 miRNA +chr20 2654212 2654286 + ENSG00000221116.1 SNORD110 snoRNA +chr20 2656097 2656182 + ENSG00000212498.1 SNORD86 snoRNA +chr20 2656624 2656694 + ENSG00000229686.1 SNORD56 snoRNA +chr20 2656939 2657010 + ENSG00000226572.1 SNORD57 snoRNA +chr20 10025917 10026168 + ENSG00000276525.1 Metazoa_SRP misc_RNA +chr20 21501395 21501968 + ENSG00000227693.1 GSTM3P1 processed_pseudogene +chr20 21511447 21512309 + ENSG00000258197.1 NKX2-2-AS1 antisense +chr20 22733210 22733301 - ENSG00000265151.1 AL158175.1 miRNA +chr20 31581089 31581192 + ENSG00000201770.1 RNU6-384P snRNA +chr20 32237795 32237847 + ENSG00000221667.1 MIR1825 miRNA +chr20 35544430 35544747 - ENSG00000224497.1 RPL36P4 processed_pseudogene +chr20 36255716 36255820 + ENSG00000281193.1 AL121895.1 miRNA +chr20 38421647 38421774 - ENSG00000277034.1 SNORA71 snoRNA +chr20 38425198 38425331 - ENSG00000273718.1 SNORA71 snoRNA +chr20 38448084 38448215 + ENSG00000274309.1 SNORA71E snoRNA +chr20 43549389 43550949 - ENSG00000226143.1 RP1-138B7.5 antisense +chr20 47651067 47651156 + ENSG00000280970.1 AL034418.1 miRNA +chr20 49278427 49278624 + ENSG00000277830.1 ZNFX1-AS1_1 misc_RNA +chr20 49279116 49279208 + ENSG00000274760.1 ZNFX1-AS1_2 misc_RNA +chr20 49280485 49280571 + ENSG00000277967.1 ZNFX1-AS1_3 misc_RNA +chr20 49280683 49280772 + ENSG00000212304.1 SNORD12 snoRNA +chr20 50840615 50840749 - ENSG00000230043.1 TMSB4XP6 processed_pseudogene +chr20 56459428 56459583 - ENSG00000228601.1 RPL39P processed_pseudogene +chr20 56460266 56460357 - ENSG00000212084.2 AL121914.1 miRNA +chr20 58817615 58817694 - ENSG00000276373.1 MIR296 miRNA +chr20 58842030 58842132 + ENSG00000276859.1 GNAS-AS1_1 misc_RNA +chr20 58850530 58850641 + ENSG00000274491.1 GNAS-AS1_4 misc_RNA +chr20 58850783 58850903 + ENSG00000275069.1 GNAS-AS1_5 misc_RNA +chr20 61953546 61953662 - ENSG00000221417.1 MIR1257 miRNA +chr20 62064802 62064885 + ENSG00000265306.1 MIR3195 miRNA +chr20 62134680 62135089 - ENSG00000280448.1 AL078633.1 pseudogene +chr20 62845664 62845912 + ENSG00000233838.5 DPH3P1 processed_pseudogene +chr20 63102142 63102259 + ENSG00000274915.1 HAR1A misc_RNA +chr20 63696668 63698684 + ENSG00000243509.4 TNFRSF6B protein_coding +chr20 63744689 63745958 + ENSG00000229299.2 RP4-583P15.10 antisense +chr20 63861213 63863306 + ENSG00000183260.6 ABHD16B protein_coding +chr20 63941465 63941544 - ENSG00000272045.1 MIR1914 miRNA +chr21 6994374 6997737 - ENSG00000279313.1 CH507-145C22.4 lincRNA +chr21 14143581 14144158 + ENSG00000240755.1 ERLEC1P1 processed_pseudogene +chr21 14961309 14964233 + ENSG00000229047.1 AF127577.10 antisense +chr21 25573980 25574044 + ENSG00000275402.1 MIR155 miRNA +chr21 33550662 33550728 + ENSG00000275224.1 MIR6501 miRNA +chr21 36132450 36133032 + ENSG00000214889.3 RPS9P1 processed_pseudogene +chr21 36485983 36487411 - ENSG00000223741.1 PSMD4P1 processed_pseudogene +chr21 39171462 39171560 - ENSG00000276873.1 uc_338 misc_RNA +chr21 39184469 39184899 + ENSG00000272991.1 AF129408.17 antisense +chr21 41180097 41180626 + ENSG00000224388.1 BACE2-IT1 antisense +chr21 41739373 41741308 + ENSG00000236883.1 AP001615.9 antisense +chr21 44328944 44330221 - ENSG00000241728.4 AP001062.8 sense_overlapping +chr22 15826566 15827187 + ENSG00000271672.1 DUXAP8 transcribed_processed_pseudogene +chr22 16961936 17008222 - ENSG00000215568.6 GAB4 protein_coding +chr22 17012404 17012932 + ENSG00000270226.1 AC006548.26 processed_pseudogene +chr22 17021398 17022570 - ENSG00000276400.1 VN1R9P processed_pseudogene +chr22 18101612 18101888 + ENSG00000235617.1 XXbac-B476C20.10 unprocessed_pseudogene +chr22 18102457 18103649 - ENSG00000225225.1 ARL2BPP10 processed_pseudogene +chr22 19018043 19018916 - ENSG00000270393.1 AC000095.9 processed_pseudogene +chr22 19130808 19132623 + ENSG00000206203.4 TSSK2 protein_coding +chr22 19454179 19454605 + ENSG00000273300.1 AC000068.9 antisense +chr22 19722945 19724771 + ENSG00000203618.5 GP1BB protein_coding +chr22 20064552 20065705 - ENSG00000268292.1 AC006547.15 antisense +chr22 20085746 20085833 + ENSG00000266567.1 MIR3618 miRNA +chr22 20086042 20086150 + ENSG00000221366.2 MIR1306 miRNA +chr22 20110821 20111875 - ENSG00000243762.1 AC006547.8 antisense +chr22 20126402 20126526 + ENSG00000264346.1 SNORA77 snoRNA +chr22 20483225 20483316 - ENSG00000265300.1 AC007731.1 miRNA +chr22 20889206 20891214 - ENSG00000272600.1 AC007308.7 antisense +chr22 22895375 22895834 + ENSG00000211675.2 IGLC1 IG_C_gene +chr22 23782283 23783958 - ENSG00000280178.1 AP000349.2 protein_coding +chr22 23903381 23903455 + ENSG00000277002.1 AP000350.1 miRNA +chr22 26671402 26671550 + ENSG00000277941.1 MIAT_exon5_1 misc_RNA +chr22 26672164 26672248 + ENSG00000275942.1 MIAT_exon5_2 misc_RNA +chr22 26673254 26673630 + ENSG00000276991.1 MIAT_exon5_3 misc_RNA +chr22 27919384 27919545 + ENSG00000277460.1 TTC28-AS1_1 misc_RNA +chr22 27922022 27922178 + ENSG00000276150.1 TTC28-AS1_2 misc_RNA +chr22 28002484 28002595 + ENSG00000276675.1 TTC28-AS1_4 misc_RNA +chr22 28794555 28800597 - ENSG00000100219.15 XBP1 protein_coding +chr22 28798628 28798725 - ENSG00000280977.1 Z93930.1 miRNA +chr22 28992721 29018620 + ENSG00000235786.1 ZNRF3-IT1 sense_intronic +chr22 29024999 29031476 - ENSG00000177993.3 ZNRF3-AS1 antisense +chr22 29058672 29061844 - ENSG00000100249.4 C22orf31 protein_coding +chr22 29073078 29168333 + ENSG00000183762.11 KREMEN1 protein_coding +chr22 29099041 29111683 - ENSG00000226772.1 CTA-747E2.10 antisense +chr22 29126261 29126404 - ENSG00000281592.1 Z95116.1 miRNA +chr22 29134014 29134120 + ENSG00000200871.1 RNU6-810P snRNA +chr22 29191697 29191808 - ENSG00000251952.1 RNU6-1219P snRNA +chr22 29333163 29333258 - ENSG00000239127.1 SNORD125 snoRNA +chr22 29437583 29437733 + ENSG00000274457.1 AC000041.10 unprocessed_pseudogene +chr22 29711820 29719714 - ENSG00000239446.1 RP1-76B20.12 antisense +chr22 30007049 30007113 + ENSG00000275818.1 MIR6818 miRNA +chr22 30971005 30971149 + ENSG00000276664.1 TUG1_1 misc_RNA +chr22 30971296 30971382 + ENSG00000276057.1 TUG1_2 misc_RNA +chr22 30972857 30973093 + ENSG00000276965.1 TUG1_3 misc_RNA +chr22 30973417 30973597 + ENSG00000275307.1 TUG1_4 misc_RNA +chr22 30976515 30978848 - ENSG00000269987.1 RP3-430N8.11 lincRNA +chr22 30977516 30977858 - ENSG00000269972.1 RP3-430N8.10 lincRNA +chr22 31059989 31060285 + ENSG00000240186.3 RN7SL633P misc_RNA +chr22 31205264 31205616 - ENSG00000254835.1 RNF185-AS1 antisense +chr22 31621467 31621531 - ENSG00000275382.1 MIR7109 miRNA +chr22 31837238 31837298 + ENSG00000252909.1 RNU6-201P snRNA +chr22 32362972 32363059 + ENSG00000274617.1 RFPL3-AS1_1 misc_RNA +chr22 32368497 32368567 + ENSG00000274170.1 RFPL3-AS1_2 misc_RNA +chr22 33164063 33166439 + ENSG00000232073.1 RP1-302D9.3 antisense +chr22 33704786 33704920 - ENSG00000253007.2 SNORA76 snoRNA +chr22 35164304 35165347 + ENSG00000238153.1 CTA-714B7.4 processed_pseudogene +chr22 35194699 35194942 - ENSG00000243453.1 COX7BP1 processed_pseudogene +chr22 37371684 37372858 + ENSG00000272694.1 RP1-63G5.8 antisense +chr22 37844272 37844371 - ENSG00000207945.1 MIR658 miRNA +chr22 37891347 37891448 + ENSG00000207227.1 RNU6-900P snRNA +chr22 37950965 37951778 + ENSG00000272582.1 RP5-1039K5.17 antisense +chr22 37967563 37967624 + ENSG00000277321.1 MIR6820 miRNA +chr22 37970686 37987422 - ENSG00000100146.15 SOX10 protein_coding +chr22 37988794 37988853 + ENSG00000264505.1 MIR4534 miRNA +chr22 39120293 39120566 - ENSG00000226024.1 COX5BP7 processed_pseudogene +chr22 39313819 39313911 - ENSG00000209480.1 SNORD83B snoRNA +chr22 39319050 39319113 - ENSG00000263764.1 SNORD43 snoRNA +chr22 41092513 41092566 + ENSG00000221160.1 MIR1281 miRNA +chr22 41923222 41923297 - ENSG00000263463.1 MIR378I miRNA +chr22 42569147 42569250 - ENSG00000251913.1 RNU6-513P snRNA +chr22 42615244 42615393 + ENSG00000276027.1 RNU12 snRNA +chr22 45976878 45976954 - ENSG00000265610.1 CR536603.1 miRNA +chr22 46112732 46112840 + ENSG00000198986.2 MIRLET7A3 miRNA +chr22 46113566 46113657 + ENSG00000264147.1 MIR4763 miRNA +chr22 46113686 46113768 + ENSG00000207875.1 MIRLET7B miRNA +chr22 50275674 50275921 + ENSG00000279216.1 AL022328.1 protein_coding +chrX 2904904 2906081 + ENSG00000229851.1 ARSD-AS1 antisense +chrX 3607258 3607365 - ENSG00000207332.1 RNU6-146P snRNA +chrX 15785716 15787589 - ENSG00000281371.1 INE2 antisense +chrX 21872707 21872808 + ENSG00000206639.1 Y_RNA misc_RNA +chrX 30834623 30835300 + ENSG00000231542.1 TAB3-AS1 antisense +chrX 30854321 30854707 + ENSG00000235512.1 TAB3-AS2 antisense +chrX 37441523 37442068 + ENSG00000241607.1 RP11-357K9.2 unprocessed_pseudogene +chrX 39837561 39837613 + ENSG00000263972.1 MIR1587 miRNA +chrX 41233633 41234283 + ENSG00000269941.1 RP5-1172N10.4 sense_intronic +chrX 52063347 52063474 - ENSG00000221705.1 SNORA11E snoRNA +chrX 52190621 52190748 + ENSG00000221475.1 SNORA11D snoRNA +chrX 53143034 53143117 - ENSG00000266700.1 AL139396.1 miRNA +chrX 54927305 54927433 + ENSG00000221750.1 SNORA11 snoRNA +chrX 66018870 66018979 + ENSG00000207939.1 MIR223 miRNA +chrX 67545277 67545422 + ENSG00000280956.1 AL049564.1 miRNA +chrX 70846080 70846295 - ENSG00000280704.1 U3 snoRNA +chrX 73821657 73821724 - ENSG00000274655.1 XIST_intron misc_RNA +chrX 73831145 73831270 - ENSG00000277577.1 Xist_exon4 misc_RNA +chrX 73850487 73850571 + ENSG00000278039.1 Xist_exon1 misc_RNA +chrX 73944332 73944466 + ENSG00000274430.1 JPX_1 misc_RNA +chrX 73944595 73944663 + ENSG00000276784.1 JPX_2 misc_RNA +chrX 74280936 74281082 + ENSG00000275254.1 FTX_3 misc_RNA +chrX 74293357 74293574 + ENSG00000277922.1 FTX_5 misc_RNA +chrX 80024067 80031111 + ENSG00000281700.1 TBX22 protein_coding +chrX 85244095 85244171 + ENSG00000264517.1 AC003001.1 miRNA +chrX 92460452 92460545 + ENSG00000211526.1 AL121869.1 miRNA +chrX 107428989 107429079 + ENSG00000207846.1 AL035088.1 miRNA +chrX 112780718 112780788 - ENSG00000263351.1 MIR4329 miRNA +chrX 115622308 115649561 + ENSG00000281638.1 AL589842.1 protein_coding +chrX 115703812 115703867 + ENSG00000264759.1 AC005000.1 miRNA +chrX 120877496 120878924 - ENSG00000278646.1 RP1-321E8.5 protein_coding +chrX 126472809 126472882 - ENSG00000264338.1 AL359973.1 miRNA +chrX 136879199 136879271 - ENSG00000206979.1 SNORD61 snoRNA +chrX 138627077 138627343 + ENSG00000232183.1 RP6-27P15.2 antisense +chrX 140086058 140086145 + ENSG00000280833.1 AL589987.1 miRNA +chrX 140783176 140784660 + ENSG00000281508.1 CDR1-AS antisense +chrX 148501098 148991332 + ENSG00000281817.1 AFF2 protein_coding +chrX 151956683 151956778 - ENSG00000264120.1 AF274855.1 miRNA +chrX 151958578 151958658 - ENSG00000207621.1 MIR224 miRNA +chrX 151959607 151959719 - ENSG00000207753.2 MIR452 miRNA +chrX 154400281 154400415 + ENSG00000207165.1 SNORA70 snoRNA +chrX 154768596 154768656 + ENSG00000281135.1 MIR664B miRNA +chrX 154774998 154775126 + ENSG00000206693.1 SNORA56 snoRNA +chrX 154887360 154887458 - ENSG00000221533.1 MIR1184-1 miRNA +chrX 155383100 155383198 - ENSG00000221190.1 MIR1184-1 miRNA +chrX 155457517 155457615 + ENSG00000221603.1 MIR1184-3 miRNA +chrX 156022631 156022698 + ENSG00000276543.3 AJ271736.1 miRNA +chrY 5573928 5574019 + ENSG00000252059.2 AC012667.1 miRNA +chrY 7378672 7378779 + ENSG00000252155.1 RNU6-941P snRNA +chrY 57209151 57209218 + ENSGR0000276543.3 AJ271736.1 miRNA diff --git a/docs/Data/Data_Security/Data_Security.md b/docs/Data/Data_Security/Data_Security.md index 62cc8b9d1..1c009d80c 100644 --- a/docs/Data/Data_Security/Data_Security.md +++ b/docs/Data/Data_Security/Data_Security.md @@ -31,10 +31,66 @@ The GDC Data Transfer Tool and the GDC API use tokens for authentication. GDC au ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTOKEN-01234567890+AlPhAnUmErIcToKeN=0123456789-ALPHANUMERICTO +## Logging into the GDC + +To login to the GDC, users must click on the `Login` button on the top right of the GDC Website. + +![Login](images/v2_image_login.jpg) + +After clicking Login, users authenticate themselves using their eRA Commons login and password. If authentication is successful, the eRA Commons username will be displayed in the upper right corner of the screen, in place of the "Login" button. + +Upon successful authentication, GDC Data Portal users can: + +- See which controlled-access files they can access. +- Download controlled-access files directly from the GDC Data Portal. +- Download an authentication token for use with the GDC Data Transfer Tool or the GDC API. +- See controlled-access mutation data they can access. + +Controlled-access files are identified via their status in the Access Column: + +[![GDC Data Portal Main Page](images/gdc-file-status-controlled-v2_3.png)](images/gdc-file-status-controlled-v2_3.png "Click to see the full image.") + +The rest of this section describes controlled data access features of the GDC Data Portal available to authorized users. For more information about open and controlled-access data, and about obtaining access to controlled data, see [Data Access Processes and Tools](https://gdc.cancer.gov/access-data/data-access-processes-and-tools). + +## User Profile + +After logging into the GDC Portal, users can view which projects they have access to by clicking the `User Profile` section in the dropdown menu in the top corner of the screen. + +[![User Profile Drop Down](images/gdc-user-profile-v2_small.png)](images/gdc-user-profile-v2_small.png "Click to see the full image.") + +Clicking this button shows the list of projects. + +[![User Profile](images/Profile_Access_List.png)](images/Profile_Access_List.png "Click to see the full image.") + +## GDC Authentication Tokens + +The GDC Data Portal provides authentication tokens for use with the GDC Data Transfer Tool or the GDC API. To download a token: + +1. Log into the GDC using your eRA Commons credentials. +2. Click the username in the top right corner of the screen. +3. Select the "Download token" option. + +![Token Download Button](images/Token_Download_v2_small.jpg) + +A new token is generated each time the `Download Token` button is clicked. + +For more information about authentication tokens, see [Data Security](../../Data/Data_Security/Data_Security.md#authentication-tokens). + +>__Note:__ The authentication token should be kept in a secure location, as it allows access to all data accessible by the associated user account. + +## Logging Out + +To log out of the GDC, click the username in the top right corner of the screen, and select the Logout option. + +![Logout link](images/gdc-user-portal-logout-v2_3.jpg) + + + + #### Obtaining A Token -Users can obtain authentication tokens from the [GDC Data Portal](https://portal.gdc.cancer.gov) and the [GDC Data Submission Portal](https://portal.gdc.cancer.gov/submission). See the [GDC Data Portal User's Guide](../../Data_Portal/Users_Guide/Authentication.md#gdc-authentication-tokens) and the [GDC Data Submission Portal User's Guide](../../Data_Submission_Portal/Users_Guide/Authentication.md#gdc-authentication-tokens) for instructions. +Users can obtain authentication tokens from the [GDC Data Portal](https://portal.gdc.cancer.gov) and the [GDC Data Submission Portal](https://portal.gdc.cancer.gov/submission). See the [GDC Data Submission Portal User's Guide](../../Data_Submission_Portal/Users_Guide/Data_Submission_Process.md#authentication) for instructions. #### Token Expiration diff --git a/docs/Data/Data_Security/images/Profile_Access_List.png b/docs/Data/Data_Security/images/Profile_Access_List.png new file mode 100644 index 000000000..fcf5c15a4 Binary files /dev/null and b/docs/Data/Data_Security/images/Profile_Access_List.png differ diff --git a/docs/Data/Data_Security/images/Token_Download_v2_small.jpg b/docs/Data/Data_Security/images/Token_Download_v2_small.jpg new file mode 100644 index 000000000..d0eaf9460 Binary files /dev/null and b/docs/Data/Data_Security/images/Token_Download_v2_small.jpg differ diff --git a/docs/Data/Data_Security/images/gdc-file-status-controlled-v2.png b/docs/Data/Data_Security/images/gdc-file-status-controlled-v2.png new file mode 100644 index 000000000..4a978a583 Binary files /dev/null and b/docs/Data/Data_Security/images/gdc-file-status-controlled-v2.png differ diff --git a/docs/Data/Data_Security/images/gdc-file-status-controlled-v2_3.png b/docs/Data/Data_Security/images/gdc-file-status-controlled-v2_3.png new file mode 100644 index 000000000..deec09159 Binary files /dev/null and b/docs/Data/Data_Security/images/gdc-file-status-controlled-v2_3.png differ diff --git a/docs/Data/Data_Security/images/gdc-user-portal-logout-v2_3.jpg b/docs/Data/Data_Security/images/gdc-user-portal-logout-v2_3.jpg new file mode 100644 index 000000000..5d5c7a922 Binary files /dev/null and b/docs/Data/Data_Security/images/gdc-user-portal-logout-v2_3.jpg differ diff --git a/docs/Data/Data_Security/images/gdc-user-profile-v2_small.png b/docs/Data/Data_Security/images/gdc-user-profile-v2_small.png new file mode 100644 index 000000000..28d63a9ae Binary files /dev/null and b/docs/Data/Data_Security/images/gdc-user-profile-v2_small.png differ diff --git a/docs/Data/Data_Security/images/v2_image_login.jpg b/docs/Data/Data_Security/images/v2_image_login.jpg new file mode 100644 index 000000000..01602c596 Binary files /dev/null and b/docs/Data/Data_Security/images/v2_image_login.jpg differ diff --git a/docs/Data/File_Formats/MAF_Format.md b/docs/Data/File_Formats/MAF_Format.md index 966d7c2de..5732e0f81 100644 --- a/docs/Data/File_Formats/MAF_Format.md +++ b/docs/Data/File_Formats/MAF_Format.md @@ -2,11 +2,11 @@ ## Introduction -Mutation Annotation Format (MAF) is a tab-delimited text file with aggregated mutation information from [VCF Files](VCF_Format.md) and are generated on a project-level. MAF files are produced through the [Somatic Aggregation Workflow](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=somatic_aggregation_workflow&_top=1) The GDC produces MAF files at two permission levels: __protected__ and __somatic__ (or open-access). One MAF files is produced per variant calling pipeline per GDC project. MAFs are produced by aggregating the GDC annotated VCF files generated from one pipeline for one project. +Mutation Annotation Format (MAF) is a tab-delimited text file with aggregated mutation information from [VCF Files](VCF_Format.md) and are generated on a project-level. MAF files are produced through the [Somatic Aggregation Workflow](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=somatic_aggregation_workflow&_top=1). The GDC produces MAF files at two permission levels: __protected__ and __somatic__ (or open-access). One MAF file is produced per variant calling pipeline per GDC project. MAFs are produced by aggregating the GDC annotated VCF files generated from one pipeline for one project. Annotated VCF files often have variants reported on multiple transcripts whereas the MAF files generated from the VCFs (\*protected.maf) only report the most critically affected one. Somatic MAFs (\*somatic.maf), which are also known as [Masked Somatic Mutation](https://docs.gdc.cancer.gov/Data_Dictionary/viewer/#?view=table-definition-view&id=masked_somatic_mutation) files, are further processed to remove lower quality and potential germline variants. For tumor samples that contain variants from multiple combinations of tumor-normal aliquot pairs, only one pair is selected in the Somatic MAF based on their sample type. Somatic MAFs are publicly available and can be freely distributed within the boundaries of the [GDC Data Access Policies](https://gdc.cancer.gov/access-data/data-access-policies). -The GDC MAF file format is based on the [TCGA Mutation Annotation Format](https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+(MAF)+Specification) specifications, with additional columns included. +The GDC MAF file format is based on the TCGA Mutation Annotation Format specifications, with additional columns included. __Note:__ The criteria for allowing mutations into open-access are purposefully implemented to overcompensate and filter out germline variants. If omission of true-positive somatic mutations is a concern, the GDC recommends using protected MAFs. @@ -16,13 +16,13 @@ The process for modifying a protected MAF into a somatic MAF is as follows: * Aliquot Selection: only one tumor-normal pair are selected for each tumor sample based on the plate number, sample type, analyte type and other features extracted from tumor TCGA aliquot barcode. * Low quality variant filtering and germline masking: - 1. Variants with __Mutation_Status != 'Somatic'__ or __GDC_FILTER = 'Gapfiller', 'ContEst', 'multiallelic', 'nonselectedaliquot', 'BCR_Duplicate' or 'BadSeq'__ are __removed__. - 2. Remaining variants with __GDC_Valid_Somatic = True__ are __included__ in the Somatic MAF. - 3. Remaining variants with __FILTER != 'panel_of_normals' or PASS__ are __removed__. Note that the `FILTER != panel_of_normals` value is only relevant for the variants generated from the MuTect2 pipeline. - 4. Remaining variants with __MC3_Overlap = True__ are __included__ in the Somatic MAF. - 5. Remaining variants with __GDC_FILTER = 'ndp', 'NonExonic', 'bitgt', 'gdc_pon'__ are __removed__. - 6. Remaining variants with __SOMATIC != null__ are __included__ in the Somatic MAF. - 7. Remaining variants with __dbSNP_RS = 'novel' or null__ are __included__ in the Somatic MAF. + 1. Variants with ```Mutation_Status != 'Somatic'``` or ```GDC_FILTER = 'Gapfiller'```, ```'ContEst'```, ```'multiallelic'```, ```'nonselectedaliquot'```, ```'BCR_Duplicate'``` or ```'BadSeq'``` are __removed__. + 2. Remaining variants with ```GDC_Valid_Somatic = True``` are __included__ in the Somatic MAF. + 3. Remaining variants with ```FILTER != 'panel_of_normals'``` or ```PASS``` are __removed__. Note that the `FILTER != panel_of_normals` value is only relevant for the variants generated from the MuTect2 pipeline. + 4. Remaining variants with ```MC3_Overlap = True``` are __included__ in the Somatic MAF. + 5. Remaining variants with ```GDC_FILTER = 'ndp'```, ```'NonExonic'```, ```'bitgt'```, ```'gdc_pon'``` are __removed__. + 6. Remaining variants with ```SOMATIC != null``` are __included__ in the Somatic MAF. + 7. Remaining variants with ```dbSNP_RS = 'novel'``` or ```null``` are __included__ in the Somatic MAF. 8. Remaining variants are __removed__. * Removal of the following columns: * vcf_region @@ -135,9 +135,9 @@ The table below describes the columns in a protected MAF and their definitions. |82 - EAS_MAF | Non-reference allele and frequency of existing variant in 1000 Genomes combined East Asian population | |83 - EUR_MAF | Non-reference allele and frequency of existing variant in 1000 Genomes combined European population | |84 - SAS_MAF | Non-reference allele and frequency of existing variant in 1000 Genomes combined South Asian population | -|85 - AA_MAF | Non-reference allele and frequency of existing variant in [NHLBI-ESP](http://evs.gs.washington.edu/EVS/) African American population | +|85 - AA_MAF | Non-reference allele and frequency of existing variant in [NHLBI-ESP](https://esp.gs.washington.edu/drupal/) African American population | |86 - EA_MAF | Non-reference allele and frequency of existing variant in NHLBI-ESP European American population| -|87 - CLIN_SIG | Clinical significance of variant from dbSNP | +|87 - CLIN_SIG | Clinical significance of variant from dbSNP as annotated in ClinVar | |88 - SOMATIC |Somatic status of each ID reported under Existing_variation (0, 1, or null) | |89 - PUBMED | Pubmed ID(s) of publications that cite existing variant | |90 - MOTIF_NAME |The source and identifier of a transcription factor binding profile aligned at this position | @@ -180,21 +180,21 @@ The table below describes the columns in a protected MAF and their definitions. ### Notes About GDC MAF Implementation -1. Column #4 __NCBI_Build__ is GRCh38 by default -2. Column #32 __Sequencer__ includes the sequencers used. If different sequencers were used to generate normal and tumor data, the normal sequencer is listed first. -3. Column #61 VEP name "STRAND" is changed to __TRANSCRIPT_STRAND__ to avoid confusion with Column#8 "Strand" -4. Column #94 __IMPACT__ categories are defined by the VEP software and do not necessarily reflect the relative biological influence of each mutation. -4. Column #122-125 __vcf_info, vcf_format, vcf_tumor_gt, and vcf_normal_gt__ are the corresponding columns from the VCF files. Including them facilitates parsing specific variant information. -5. Column #120 __GDC_Validation_Status__: GDC also collects TCGA validation sequences. It compares these with variants derived from Next-Generation Sequencing data from the same sample and populates the comparison result in "GDC_Validation_Status". +1. Column #4: __NCBI_Build__ is GRCh38 by default +2. Column #32: __Sequencer__ includes the sequencers used. If different sequencers were used to generate normal and tumor data, the normal sequencer is listed first. +3. Column #61: VEP name "STRAND" is changed to __TRANSCRIPT_STRAND__ to avoid confusion with Column#8 "Strand" +4. Column #94: __IMPACT__ categories are defined by the VEP software and do not necessarily reflect the relative biological influence of each mutation. +4. Column #122-125: __vcf_info, vcf_format, vcf_tumor_gt, and vcf_normal_gt__ are the corresponding columns from the VCF files. Including them facilitates parsing specific variant information. +5. Column #120: __GDC_Validation_Status__: GDC also collects TCGA validation sequences. It compares these with variants derived from Next-Generation Sequencing data from the same sample and populates the comparison result in "GDC_Validation_Status". * "Valid", if the alternative allele(s) in the tumor validation sequence is(are) the same as GDC variant call * "Invalid", if none of the alternative allele(s) in the tumor validation sequence is the same as GDC variant call * "Inconclusive" if two alternative allele exists, and one matches while the other does not * "Unknown" if no validation sequence exists -6. Column #121 __GDC_Valid_Somatic__ is TRUE if GDC_Validation_Status is "Valid" and the variant is "Somatic" in validation calls. It is FALSE if these criteria are not met +6. Column #121: __GDC_Valid_Somatic__ is TRUE if GDC_Validation_Status is "Valid" and the variant is "Somatic" in validation calls. It is FALSE if these criteria are not met ### FILTER Value Definitions (column 111) -* __oxog :__ Signifies that this variant was determined to be an OxoG artifact. This was calculated with [D-ToxoG](http://archive.broadinstitute.org/cancer/cga/dtoxog) +* __oxog :__ Signifies that this variant was determined to be an OxoG artifact. This was calculated with [D-ToxoG](https://software.broadinstitute.org/cancer/cga/dtoxog) * __bPcr :__ Signifies that this variant was determined to be an artifact of bias on the PCR template strand. This was calculated with the [DKFZ Bias Filter](https://github.com/eilslabs/DKFZBiasFilter). * __bSeq :__ Signifies that this variant was determined to be an artifact of bias on the forward/reverse strand. This was also calculated with the [DKFZ Bias Filter](https://github.com/eilslabs/DKFZBiasFilter). diff --git a/docs/Data/Release_Notes/CPTAC-3_7Cases-WXS-MAFs_GDC-Manifest.txt b/docs/Data/Release_Notes/CPTAC-3_7Cases-WXS-MAFs_GDC-Manifest.txt new file mode 100644 index 000000000..3fa3fc0a1 --- /dev/null +++ b/docs/Data/Release_Notes/CPTAC-3_7Cases-WXS-MAFs_GDC-Manifest.txt @@ -0,0 +1,15 @@ +id file_name file_size md5sum case.submitter_id +21762c82-a87e-4119-b087-40620a2bbe5c 4191375a-bb45-4939-94fe-ea4e24384d9a.wxs.aliquot_ensemble_raw.maf.gz 157552 9828d9b43165faa665889f8edaf14417 C3N-03839 +3bc87d89-1cc5-4b00-a2ed-bd26eabb1245 fb39440b-fff0-456e-a5f9-77b8808f5b1b.wxs.aliquot_ensemble_masked.maf.gz 13263 77609c30faab4b495453e7e195622bbf C3L-04080 +56d1ff72-dd53-422c-9ea5-7664081f6eb2 19fbb6ef-8a29-4c7a-a625-94ce85d5f08f.wxs.aliquot_ensemble_raw.maf.gz 134555 c719416ab33bb0b0476e44f9481205ea C3N-02971 +650494a4-4028-4a6f-bedd-5fc292d38da2 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b/docs/Data/Release_Notes/Data_Release_Notes.md index 4b7eee745..d0f858b34 100644 --- a/docs/Data/Release_Notes/Data_Release_Notes.md +++ b/docs/Data/Release_Notes/Data_Release_Notes.md @@ -2,6 +2,37 @@ | Version | Date | |---|---| +| [v40.0](Data_Release_Notes.md#data-release-400) | March 29, 2024 | +| [v39.0](Data_Release_Notes.md#data-release-390) | December 4, 2023 | +| [v38.0](Data_Release_Notes.md#data-release-380) | August 31, 2023 | +| [v37.0](Data_Release_Notes.md#data-release-370) | March 29, 2023 | +| [v36.0](Data_Release_Notes.md#data-release-360) | December 12, 2022 | +| [v35.0](Data_Release_Notes.md#data-release-350) | September 28, 2022 | +| [v34.0](Data_Release_Notes.md#data-release-340) | July 27, 2022 | +| [v33.1](Data_Release_Notes.md#data-release-331) | May 31, 2022 | +| [v33.0](Data_Release_Notes.md#data-release-330) | May 3, 2022 | +| [v32.0](Data_Release_Notes.md#data-release-320) | March 29, 2022 | +| [v31.0](Data_Release_Notes.md#data-release-310) | October 29, 2021 | +| [v30.0](Data_Release_Notes.md#data-release-300) | September 23, 2021 | +| [v29.0](Data_Release_Notes.md#data-release-290) | March 31, 2021 | +| [v28.0](Data_Release_Notes.md#data-release-280) | February 2, 2021 | +| [v27.0-fix](Data_Release_Notes.md#data-release-270-bug-fix) | November 9, 2020 | +| [v27.0](Data_Release_Notes.md#data-release-270) | October 29, 2020 | +| [v26.0](Data_Release_Notes.md#data-release-260) | September 8, 2020 | +| [v25.0](Data_Release_Notes.md#data-release-250) | July 22, 2020 | +| [v24.0](Data_Release_Notes.md#data-release-240) | May 7, 2020 | +| [v23.0](Data_Release_Notes.md#data-release-230) | April 7, 2020 | +| [v22.0](Data_Release_Notes.md#data-release-220) | January 16, 2020 | +| [v21.0](Data_Release_Notes.md#data-release-210) | December 10, 2019 | +| [v20.0](Data_Release_Notes.md#data-release-200) | November 11, 2019 | +| [v19.1](Data_Release_Notes.md#data-release-191) | November 6, 2019 | +| [v19.0](Data_Release_Notes.md#data-release-190) | September 17, 2019 | +| [v18.0](Data_Release_Notes.md#data-release-180) | July 8, 2019 | +| [v17.1](Data_Release_Notes.md#data-release-171) | June 12, 2019 | +| [v17.0](Data_Release_Notes.md#data-release-170) | June 5, 2019 | +| [v16.0](Data_Release_Notes.md#data-release-160) | March 26, 2019 | +| [v15.0](Data_Release_Notes.md#data-release-150) | February 20, 2019 | +| [v14.0](Data_Release_Notes.md#data-release-140) | December 18, 2018 | | [v13.0](Data_Release_Notes.md#data-release-130) | September 27, 2018 | | [v12.0](Data_Release_Notes.md#data-release-120) | June 13, 2018 | | [v11.0](Data_Release_Notes.md#data-release-110) | May 21, 2018 | @@ -17,6 +48,2548 @@ | [v2.0](Data_Release_Notes.md#data-release-20) | August 9, 2016 | | [v1.0](Data_Release_Notes.md#initial-data-release-10) | June 6, 2016 | +## Data Release 40.0 + +* __GDC Product__: Data +* __Release Date__: March 29, 2024 + +### New Updates + +* New Projects + * MATCH-R - Genomic Characterization CS-MATCH-0007 Arm R - phs002029 + * 28 cases + * WXS, RNA-Seq + * MATCH-S1 - Genomic Characterization CS-MATCH-0007 Arm S1 - phs002153 + * 41 cases + * WXS, RNA-Seq + * MATCH-S2 - Genomic Characterization CS-MATCH-0007 Arm S2 - phs002178 + * 3 cases + * WXS, RNA-Seq + * MATCH-Z1I - Genomic Characterization CS-MATCH-0007 Arm Z1I - phs002058 + * 26 cases + * WXS, RNA-Seq + +* New Cases from Existing Projects + * CPTAC-3 - 79 cases + * REBC-THYR - 9 cases + +* New Data Sets + * Targeted Sequencing + * TARGET-AML - 1,596 aliquot BAMs, 769 variant calls + * TARGET-NBL - 998 aliquot BAMs, 476 variant calls + * TARGET-OS - 233 aliquot BAMs, 65 variant calls + * TCGA WGS + * 57 alignments + * 486 variant call aliquot pairs + * REBC-THYR + * WGS - 90 aliquot BAMs, 69 variant calls + * miRNA-Seq - 177 aliquots + * RNA-Seq - 78 aliquots + * RNA-Seq - Addition of STAR-Fusion data to existing aliquots + * HCMI-CMDC + * Slide images for released cases + * Updated clinical supplements + * TCGA-GBM + * miRNA-Seq - 8 aliquots + * RNA-Seq - 1 aliquot + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_27Mar2024_data_release_40.0_active.tsv.gz](https://api.gdc.cancer.gov/data/ddc77ead-d6d5-4732-80f9-2b4f7f76534d) +* [DR40 Project Level Manifests](https://api.gdc.cancer.gov/data/63826234-fd63-403e-aaeb-e68cc284fb8a) +* [DR40 New Files Manifest](https://api.gdc.cancer.gov/data/eecc9c5b-0fa0-4815-9f43-4bc0d885cf3d) + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* The slide image viewer does not display for any non-TCGA slides. At this time, these slides will need to be downloaded and viewed locally. Additionally, the slide image viewer does not display properly for 14 TCGA slides, which are identified [here](missing_tiling.txt). +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](Contaminated_Alignments.dr32.tsv)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* No data from TARGET-MDLS is available. +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). + * Tumor_grade property is not populated + * Progression_or_recurrence property is not populated + + +## Data Release 39.0 + +* __GDC Product__: Data +* __Release Date__: December 4, 2023 + +### New Updates + +* New Projects + * MATCH-H - Genomic Characterization CS-MATCH-0007 Arm H - phs001888 + * 21 cases + * WXS, RNA-Seq + * MATCH-I - Genomic Characterization CS-MATCH-0007 Arm I - phs002181 + * 60 cases + * WXS, RNA-Seq + * MATCH-U - Genomic Characterization CS-MATCH-0007 Arm U - phs002179 + * 23 cases + * WXS, RNA-Seq + * MATCH-W - Genomic Characterization CS-MATCH-0007 Arm W - phs001948 + * 45 cases + * WXS, RNA-Seq + * MATCH-Z1A - Genomic Characterization CS-MATCH-0007 Arm Z1A - phs001973 + * 45 cases + * WXS, RNA-Seq + +* New Cases from Existing Projects + * HCMI-CMDC - 19 cases + +* New Data Sets + * 6,957 WGS alignments from the TCGA program + * 1,002 sets of WGS variants from TCGA + * MP2PRT-ALL: WXS and RNA-Seq data + * Tumor-only data produced with a new pipeline. This includes raw and annotated VCFs and MAFs for the following projects. Note that all tumor-only variants are controlled-access: + * BEATAML1.0-COHORT + * BEATAML1.0-CRENOLANIB + * CGCI-BLGSP + * CPTAC-3 + * HCMI-CMDC + * MATCH-B + * MATCH-H + * MATCH-I + * MATCH-N + * MATCH-Q + * MATCH-U + * MATCH-W + * MATCH-Y + * MATCH-Z1A + * MATCH-Z1D + * OHSU-CNL + * ORGANOID-PANCREATIC + * TARGET-ALL-P3 + * TARGET-WT + * VAREPOP-APOLLO + + +* New Metadata + * Sample type refactoring: + * Four fields (tissue_type, specimen_type, preservation_method, tumor_descriptor) have been populated to contain the information that was previously populated in the sample_type field + * The new field, specimen_type, is now available in the API to accommodate information about the biological makeup of the sample + * The follow up data for CPTAC-3 has been updated + +* Other Updates + * CNV mutations are now available on the exploration page for projects that only had ASCAT CNV data from WGS files. This includes CNV mutations for the following projects: + * APOLLO-LUAD + * CDDP_EAGLE-1 + * CGCI-BLGSP + * CGCI-HTMCP-CC + * CGCI-HTMCP-DLBCL + * CGCI-HTMCP-LC + * CPTAC-3 + * HCMI-CMDC + * MP2PRT-ALL + * REBC-THYR + * The GENIE program was removed from the GDC Portal because it was not representative of the latest version of GENIE + * GENIE data can be accessed from the [AACR Repositories](https://www.aacr.org/professionals/research/aacr-project-genie/aacr-project-genie-data/) + + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_20231204_data_release_39.0_active.tsv.gz](https://api.gdc.cancer.gov/data/c5171766-a5b4-4347-9db2-645bc4c91659) +* [DR39 Project Level Manifests](https://api.gdc.cancer.gov/data/55e541f8-dde1-4d02-bd4b-c09aa4d36740) + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* The slide image viewer does not display for any non-TCGA slides. At this time, these slides will need to be downloaded and viewed locally. Additionally, the slide image viewer does not display properly for 14 TCGA slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the NCI's webpage on [Using TARGET Data](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. + +## Data Release 38.0 + +* __GDC Product__: Data +* __Release Date__: August 31, 2023 + +### New Updates + +* New Projects + * MP2PRT-ALL - Molecular Profiling to Predict Response to Treatment for Acute Lymphoblastic Leukemia - phs002005 + * 1,507 cases + * WGS + * CGCI-HTMCP-DLBCL - HIV+ Tumor Molecular Characterization Project - Diffuse Large B-Cell Lymphoma - phs000235 + * 70 cases + * WGS, RNA-Seq, miRNA-Seq, Tissue Slide Images + * MATCH-B - Genomic Characterization CS-MATCH-0007 Arm B - phs002028 + * 33 cases + * WXS, RNA-Seq + * MATCH-N - Genomic Characterization CS-MATCH-0007 Arm N - phs002151 + * 21 cases + * WXS, RNA-Seq + +* New Cases from Existing Projects + * CPTAC-3 - GBM and Kidney cohorts - 50 cases + * HCMI-CMDC - 31 cases + * CGCI-BLGSP - 204 cases + * TCGA-TGCT - 113 cases + +* New Data Sets + * 9,368 WGS alignments from the TCGA program + * 4,676 Cases + * 9,368 Aliquots + * All methylation files that were produced with the SeSAMe pipeline was replaced with a new version. + * TCGA SNP6 data processed with the ASCAT3 and ABSOLUTE pipelines + * 172 CEL and birdseed files from TCGA SNP6 + * Release of remaining data for CGCI projects CGCI-BGLSP and CGCI-HTMCP-CC + +* New Metadata + * The `wgs_coverage` field is now populated for most BAMs and will allow for WGS BAMs to be queried by coverage range category. + * The QC metrics for applicable BAMs are now queryable through the GDC Data Portal and API. + * The `msi_status` and `msi_score` fields, which were produced using MSISensor2, are now queryable through the GDC Data Portal and API + + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_20230830_data_release_38.0_active.tsv.gz](https://api.gdc.cancer.gov/data/14573c1f-5dd2-4e00-b4d8-5da6af6e4baa) +* [DR38 Project Level Manifests](https://api.gdc.cancer.gov/data/6e85885d-a3f2-4bcc-a16f-9a34cfef4a67) + +### Bugs Fixed Since Last Release + +* The files produced with the SeSAMe pipeline had unfiltered methylation beta values that should be set as N/A for quality reasons. These files were replaced. +* A bug in which certain files were shown to be associated with more aliquots than usual has been fixed. + +### Known Issues and Workarounds + +* The slide image viewer does not display for any non-TCGA slides. At this time, these slides will need to be downloaded and viewed locally. Additionally, the slide image viewer does not display properly for 14 TCGA slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the NCI's webpage on [Using TARGET Data](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. + +## Data Release 37.0 + +* __GDC Product__: Data +* __Release Date__: March 29, 2023 + +### New Updates + +* New Projects + * APOLLO-LUAD - Proteogenomic characterization of lung adenocarcinoma - phs003011 + * 87 cases + * WGS, RNA-Seq + * CGCI-HTMCP-LC - HIV+ Tumor Molecular Characterization Project - Lung Cancer - phs000530 + * 39 cases + * WGS, RNA-Seq, miRNA-Seq, Slide Images + * MATCH-Q - Genomic Characterization CS-MATCH-0007 Arm Q - phs001926 + * 35 cases + * WXS, RNA-Seq + * MATCH-Y - Genomic Characterization CS-MATCH-0007 Arm Y - phs001904 + * 31 cases + * WXS, RNA-Seq + +* New Data from Existing Projects + * CPTAC-3 - 139 new cases and two new snRNA-Seq samples + * HCMI-CMDC - 118 new cases + * TCGA-THCA - 941 new WGS alignments + * TARGET-OS and TARGET-ALL-P2 - Masked Somatic Mutation MAFs are now open access and their mutations now appear in the exploration portal. + +* Data Migrated from the Legacy Archive to Active Portal + * Birdseed files that were generated from Affymetrix SNP6 arrays + * Additional WGS Alignments are now available for TCGA projects + * Additional samples from RNA-Seq and WXS are now available for TCGA projects + + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_20230329_data_release_37.0_active.tsv.gz](https://api.gdc.cancer.gov/data/838d2fe9-6540-441e-a666-2fd8af47ebf0) +* [DR37 Project Level Manifests](https://api.gdc.cancer.gov/data/27fe396d-c40f-4d6a-b3c4-bb9dea0f2148) + +### Unavailable Files + +* 56 CPTAC-3 snRNA-Seq files are currently unavailable for download. A list of the affected files can be found [here](https://api.gdc.cancer.gov/data/e89608f1-bc1a-405e-a0d2-7da563183f67). These files will be restored for download by the next data release. + + +### Bugs Fixed Since Last Release + +* Outcome data for the CPTAC program has been updated. +* The `age_at_index` field was incorrectly reported in days in the GENIE program. These values have been removed as it contained the same information as the `days_to_birth` field. + + +### Known Issues and Workarounds + +* The current files produced with the SeSAMe pipeline have unfiltered methylation beta values that should be set as N/A for quality reasons. These files will be replaced in a future release. +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The clinical supplement for TARGET-ALL-P1 is not currently available. It will be made available in a future release. +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 36.0 + +* __GDC Product__: Data +* __Release Date__: December 12, 2022 + +### New Updates + +* New Projects + * MATCH-Z1D - Genomic Characterization CS-MATCH-0007 Arm Z1D - phs001859 + * 36 cases + * WXS, RNA-Seq + * CDDP_EAGLE-1 - CDDP Integrative Analysis of Lung Adenocarcinoma (Phase 2) - phs001239 + * 50 cases + * WXS, WGS, RNA-Seq + +* New Data from Existing Projects + * CMI-MPC - new RNA-Seq and WXS data + +* Data Migrated from the Legacy Archive to Active Portal + * WGS Alignments are now available for 25 TCGA Projects + * Pathology reports from TCGA + * Affymetrix SNP6 Genotyping Array CEL files + * A set of WXS and RNA-Seq samples from TCGA and TARGET that failed harmonization at launch have been rerun and are now available in the active portal. + * TCGA Bisulfite-Seq files can be downloaded using the following manifests: + * [TARGET-RT](https://api.gdc.cancer.gov/data/ec12eb66-2b44-40e7-9cde-9598e6839a44) + * [TCGA-BLCA](https://api.gdc.cancer.gov/data/3482eb71-130c-4cf9-b187-5feea0a0c6f9) + * [TCGA-BRCA](https://api.gdc.cancer.gov/data/78dd8adc-af9b-4d32-ac9b-9ab12c4f633c) + * [TCGA-COAD](https://api.gdc.cancer.gov/data/8416eb46-11e3-4936-a7e5-61cb549a6bf8) + * [TCGA-GBM](https://api.gdc.cancer.gov/data/2827b5aa-842c-4511-b639-e5b31f096858) + * [TCGA-LUAD](https://api.gdc.cancer.gov/data/244ec7d5-3f2b-4157-8259-1de7c6c717c6) + * [TCGA-LUSC](https://api.gdc.cancer.gov/data/a9612080-3ced-4d66-9469-afe291a1cb59) + * [TCGA-READ](https://api.gdc.cancer.gov/data/ec423eac-a8e1-4bdf-a19a-01b920386864) + * [TCGA-STAD](https://api.gdc.cancer.gov/data/147b3449-6f4b-4189-b5e3-1e2fc0b8491e) + * [TCGA-UCEC](https://api.gdc.cancer.gov/data/005b4d7d-a5bb-49ad-b072-c8194e6260ff) + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_20221212_data_release_36.0_active.tsv.gz](https://api.gdc.cancer.gov/data/27a4fae0bb-f1fc-4e6f-b8cc-05aa9c28f8bc) + +### Unavailable Files + +* None + + +### Bugs Fixed Since Last Release + +* The copy number variation data is now available on the GDC Exploration portal. +* The mutations on GDC Exploration were re-built with the correct gene model. + + +### Known Issues and Workarounds + +* Outcome data for the CPTAC program is not up-to-date. Please visit the [Proteomic Data Commons](https://proteomic.datacommons.cancer.gov/pdc/) for updated outcome data for CPTAC. +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The clinical supplement for TARGET-ALL-P1 is not currently available. It will be made available in a future release. +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 35.0 + +* __GDC Product__: Data +* __Release Date__: September 28, 2022 + +### New Updates + +* The SomaticSniper variant calling pipeline was deprecated. To support this, the following changes were made: + * All SomaticSniper files no longer appear in the portal, but still can be downloaded using the Data Transfer Tool or API using the original UUID. + * The aggregated somatic mutation and masked somatic mutation files (multi-caller MAFs) have been replaced to reflect the absence of variants from the SomaticSniper pipeline. + * The mutations on the exploration portal reflect the above-mentioned masked somatic mutation files. +* 10 snRNA-Seq samples were released from the CPTAC-3 project. +* Additional RNA-Seq samples from 2,082 additional cases are now available for the TARGET-AML project. +* Demographic data has been added for 94 cases in TARGET-ALL-P2 and TARGET-ALL-P3 projects. A list of the updated cases can be found +[here](https://api.gdc.cancer.gov/data/ce79d116-f397-4cfa-8636-8e482fce8631). + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_20220928_data_release_35.0_active.tsv.gz](https://api.gdc.cancer.gov/data/e7808c04-d03f-48f4-afb6-916073cbac98) + +### Unavailable Files + +* None + + +### Bugs Fixed Since Last Release + +* Data from two HCMI-CMDC aliquots (HCM-BROD-0100-C15-85A-01D-A786-36 and HCM-BROD-0679-C43-85M-01D-A80U-36) were incorrectly selected for inclusion into the Exploration Page in Data Release 32 and has been replaced with the correct aliquots (HCM-BROD-0100-C15-01A-11D-A786-36 and HCM-BROD-0679-C43-06A-11D-A80U-36). + +### Known Issues and Workarounds + +* The mutations on GDC Exploration were built with an incorrect gene model. + * The mutations are still correct in terms of the gene affected, coordinates, DNA changes, amino acid changes, and impact. + * Mutations associated with genes that were present in GENCODE v36 and not GENCODE v22 are not displayed. This affects less than 1% of mutations. + * Files downloaded from the the GDC Repository are not affected by this issue. This only affects mutations that are downloaded from GDC Exploration. +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The clinical supplement for TARGET-ALL-P1 is not currently available. It will be made available in a future release. +* Copy number variations currently do not appear in the Exploration page. This will be restored in a future release. +* Mutations from SomaticSniper were erroneously labelled as LOH (loss of heterozygosity). This affects the VCF files, MAF files, and may cause SomaticSniper mutations to be absent from ensemble MAFs. +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 34.0 + +* __GDC Product__: Data +* __Release Date__: July 27, 2022 + +### New updates + +* 251 cases from the CPTAC-3 project were added to the portal. This includes all files associated with these cases. +* 243 cases from the BEATAML1.0-COHORT project were added to the portal. This includes most of the files associated with these cases. + * The raw tumor-only VCFs from BEATAML1.0-COHORT are downloadable from the BEATAML1.0-COHORT (2022) publication page [here](https://gdc.cancer.gov/about-data/publications/BEATAML1-0-COHORT-2022) and will be added to the Data Portal in a future release. +* WXS mutations from the BEATAML1.0-COHORT project are now available in the Exploration portal. +* Transcript fusion files are now available for the following projects: + * BEATAML1.0-COHORT + * CMI-ASC + * CMI-MBC + * CPTAC-2 + * CTSP-DLBCL1 + * MMRF-COMMPASS + * NCICCR-DLBCL + * OHSU-CNL + * ORGANOID-PANCREATIC + * WCDT-MCRPC + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_20220727_data_release_34.0_active.tsv.gz](https://api.gdc.cancer.gov/data/f0f04445-c20a-43ea-8c55-9ff1e51aff96) + +### Unavailable Files + +* None + + +### Bugs Fixed Since Last Release + +* Data from two HCMI-CMDC aliquots (HCM-BROD-0100-C15-85A-01D-A786-36 and HCM-BROD-0679-C43-85M-01D-A80U-36) were incorrectly selected for inclusion into the Exploration Page in Data Release 32 and has been replaced with the correct aliquots (HCM-BROD-0100-C15-01A-11D-A786-36 and HCM-BROD-0679-C43-06A-11D-A80U-36). + +### Known Issues and Workarounds + +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The clinical supplement for TARGET-ALL-P1 is not currently available. It will be made available in a future release. +* Copy number variations currently do not appear in the Exploration page. This will be restored in a future release. +* Mutations from SomaticSniper were erroneously labelled as LOH (loss of heterozygosity). This affects the VCF files, MAF files, and may cause SomaticSniper mutations to be absent from ensemble MAFs. +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 33.1 + +* __GDC Product__: Data +* __Release Date__: May 31, 2022 + +### New updates + +* None, see "Bugs Fixed Since Last Release" section below. + +A complete list of files included in the GDC Data Portal can be found below: + +* [gdc_manifest_20220531_data_release_33.1_active.tsv.gz](https://api.gdc.cancer.gov/data/0e16d92d-9627-4ed5-b7d2-80b6d78e1d35) + +### Unavailable Files + +* None + + +### Bugs Fixed Since Last Release + +* 32 cases from the EXCEPTIONAL_RESPONDERS-ER project were released as they were missing from the previous release. +* All mutations from EXCEPTIONAL_RESPONDERS-ER in the exploration portal come from WXS data, whereas they were previously a mixture of WXS and Targeted Sequencing. + +### Known Issues and Workarounds + +* Pathology reports do not have any associated case/biospecimen information in the portal. This information can be found in the reports themselves. +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The clinical supplement for TARGET-ALL-P1 is not currently available. It will be made available in a future release. +* Copy number variations currently do not appear in the Exploration page. This will be restored in a future release. +* Mutations from SomaticSniper were erroneously labelled as LOH (loss of heterozygosity). This affects the VCF files, MAF files, and may cause SomaticSniper mutations to be absent from ensemble MAFs. +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 33.0 + +* __GDC Product__: Data +* __Release Date__: May 3, 2022 + +### New updates + +1. New Project: NCI Exceptional Responders Initiative (EXCEPTIONAL_RESPONDERS-ER, phs001145) + * RNA-Seq - 45 Cases + * WXS - 50 Cases + * Targeted Sequencing - 41 Cases + * Mutations from WXS and Targeted Sequencing are present in the exploration page. +2. New Project: Molecular Profiling to Predict Response to Treatment - Wilms Tumor (MP2PRT-WT, phs001965) + * WGS - 52 Cases + * RNA-Seq - 52 Cases + * miRNA-Seq - 52 Cases +3. Methylation files from the SeSAMe pipeline are now available for CGCI-HTMCP-CC and the TARGET projects. + +A complete list of files for this release are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20220503_data_release_33.0_active.tsv.gz](https://api.gdc.cancer.gov/data/684e304b-02e6-47e9-99e6-30ecdb4fe644) +* [gdc_manifest_20220503_data_release_33.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/0dadd9da-d96c-454e-9d4a-65a64730637c) + +### Unavailable Files + +* The Arriba pipeline failed for one aliquot from EXCEPTIONAL-RESPONDERS-ER and is documented [here](https://api.gdc.cancer.gov/data/80cf3148-1dbb-4fda-834d-118d3f8bedb7). + + +### Bugs Fixed Since Last Release + +* Gene-level copy number files from TCGA-THCA and TCGA-UCEC were set as controlled-access files. These have been corrected to be available as open-access files. +* Due to a problem with the columns generated by the pipeline, all scRNA-Seq files have been replaced with a new version. + +### Known Issues and Workarounds + +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The clinical supplement for TARGET-ALL-P1 is not currently available. It will be made available in a future release. +* Copy number variations currently do not appear in the Exploration page. This will be restored in a future release. +* Mutations from SomaticSniper were erroneously labelled as LOH (loss of heterozygosity). This affects the VCF files, MAF files, and may cause SomaticSniper mutations to be absent from ensemble MAFs. +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 32.0 + +* __GDC Product__: Data - GENCODE v36 Release +* __Release Date__: March 29, 2022 + +### New updates + +#### New data files +1. The following data types have been replaced with new GENCODE v36 versions + * RNA-Seq: all files, including alignments, gene expression files, and transcript fusion files. + * WXS and Targeted Sequencing: annotated VCFs, single-caller MAFs, Ensemble MAFs. + * WGS: BEDPE-format structural variants and gene-level copy number variants. + * GENIE Targeted Sequencing files. + * FM-AD Targeted Sequencing files. + * The primary-site-level FM-AD MAF files have been replaced with aliquot-level MAF files. +1. RNA-Seq STAR-Counts files now contain additional normalized counts such as FPKM, FPKM-UQ, and TPM. +1. All WXS files for TCGA have been replaced with new versions. Alignments will contain QC metrics and variants were produced using the same pipelines as all other GDC projects. +1. TCGA RNA-Seq has been changed to contain three alignments (genomic, transcriptome, and chimeric), STAR-counts files, and transcript fusion files for each aliquot. +1. The project-level MAFs in TCGA and FM-AD have been replaced with aliquot-level MAFs. +1. GENCODE v22 derived files (not BAM) that no longer appear in the portal will be downloadable as previous versions of v36 files. +1. Methylation data produced from the SeSAMe pipeline is now available for all TCGA projects. +1. Note that miRNA-Seq data remains unchanged. The miRNA-Seq pipeline uses the miRBase database, which is not affected by the GENCODE version change. +1. A set of manifests were generated at the project-level that map each v22 file to its corresponding v36 file. These can be used to help users transition from v22 to v36 and can be downloaded [here](https://github.com/NCI-GDC/gdc-docs/tree/develop/docs/Data/Release_Notes/GCv36_Manifests). + +#### Removed data files and pipelines +1. Files from the HTSeq pipeline are no longer supported and will no longer appear in the portal. Normalized counts can now be found in the STAR-Counts files. +1. Files that originated from the methylation liftover pipeline are no longer supported and will no longer appear in the portal. +1. GENCODE v22 BAM files that no longer appear in the portal will be available for six months past this release. They may not be available after that. +1. New variant calling tumor-normal pairing was implemented in TCGA, which results in certain aliquots no longer being available as a v36 version (see the aliquots labeled "Unpaired Aliquots" [here](https://api.gdc.cancer.gov/data/80cf3148-1dbb-4fda-834d-118d3f8bedb7)). +1. Some aliquots failed harmonization when the new v36 gene model was used, which results in some new versions no longer being available (see the aliquots labeled "Failed Harmonization" [here](https://api.gdc.cancer.gov/data/80cf3148-1dbb-4fda-834d-118d3f8bedb7)). +1. Some aliquots were found to contain a cross-patient contamination level of over 0.04 as measured by GATK4 CalculateContamination (see the aliquots labeled "Contamination" [here](https://api.gdc.cancer.gov/data/80cf3148-1dbb-4fda-834d-118d3f8bedb7)). + +#### Data Portal Exploration Data +1. The Data Portal Exploration Page is now populated based on open-access mutations from analyses that used GENCODE v36. +1. Mutations from SomaticSniper will not appear on the Exploration page. +1. Due to the copy number variation pipeline transition from GISTIC to ASCAT, the CNV data was not included in the GDC Exploration page. This will be replaced in a future release once visualization of the new pipeline is fully assessed. +1. The TCGA program mutations have been processed using the same pipeline as all other projects, which resulted in a 26% reduction in the number of open-access mutations. Some points on this change are listed below with TCGA-BRCA as the benchmark project: + * 97% of the previously released open-access mutations are still discoverable in the new GDC controlled-access MAFs. This number increases to 99.95% when focusing only on mutations that were also called by [MC3](https://gdc.cancer.gov/about-data/publications/pancanatlas). + * Somatic mutations will now be removed from the Data Portal Exploration Page unless they are detected by more than one variant calling software. This accounts for 40% of the total reduction. + * Somatic mutations will now be removed from the Data Portal Exploration Page if they are detected outside of the target capture region, while previously out-of-target mutations detected from the TCGA Gene Annotation File (GAF) regions were allowed. This accounts for 36% of the total reduction. + * Some TCGA-specific variant-rescue steps have been removed in favor of a more robust and uniform filtering pipeline. + * Some other minor changes due to updates in the gene model or other databases (e.g., the ExAC germline variant database was replaced with gnomAD in DR32). + + +A complete list of files for this release are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20220316_data_release_32.0_active.tsv.gz](https://api.gdc.cancer.gov/data/a79c578c-d601-4113-8afd-3b36b410133c) +* [gdc_manifest_20220316_data_release_32.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/65788d0e-b415-431e-b53e-5e59dc6198a5) + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* 397 alignments from the TCGA program were found to have contamination values over 0.04 ([alignment list](https://api.gdc.cancer.gov/data/a206b677-8396-4178-8ee2-36df4538aaf5)). The ensemble MAFs produced by these alignments were removed from the Data Portal. +* One methylation aliquot from the TCGA-COAD project, TCGA-D5-6930-01A-11D-1926-05, was not added to the portal and will be added in a future release. +* The clinical supplement for TARGET-ALL-P1 is not currently available. It will be made available in a future release. +* Copy number variations currently do not appear in the Exploration page. This will be restored in a future release. +* Mutations from SomaticSniper were erroneously labelled as LOH (loss of heterozygosity). This affects the VCF files, MAF files, and may cause SomaticSniper mutations to be absent from ensemble MAFs. +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release. +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + + + +## Data Release 31.0 + +* __GDC Product__: Data +* __Release Date__: October 29, 2021 + +### New updates + +1. TCGA Slide Images: + * All TCGA slide images that were removed earlier this year have been restored. + * Note that the UUIDs for most TCGA slide images have changed. Older manifest files may not work when downloading slide images. +2. CPTAC-3 clinical data has been refreshed and includes new follow up entities. +3. REBC-THYR + * The clinical and biospecimen XML files were removed as they were not intended for release in DR 30. + * The case REBC-ADL5 was added, which includes one WGS pair. + +A complete list of files for this release are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20211029_data_release_31.0_active.tsv.gz](https://api.gdc.cancer.gov/data/4a5ba7bc-b53f-40ee-b536-7a4c4ad30eaa) +* [gdc_manifest_20211029_data_release_31.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/036c711f-77f5-4c6a-9426-00f7f4fe39ef) + +### Bugs Fixed Since Last Release + +* One file from a previous version of the methylation pipeline appeared in the data portal (bd2f864a-3f00-47b5-815d-bd01ca21ef61; CPTAC-3). This file should no longer appear in the data portal. + +### Known Issues and Workarounds + +* The slide image viewer does not display properly for 14 slides, which are identified [here](https://api.gdc.cancer.gov/data/3363f51f-2250-491c-a1ec-6a563a9527ad). The full slide image can be downloaded as an SVS file. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 30.0 + +* __GDC Product__: Data +* __Release Date__: September 23, 2021 + +### New updates + +1. New Projects: + * TRIO-CRU (phs001163) - Ukrainian National Research Center for Radiation Medicine Trio Study + * WGS Alignments + * REBC-THYR (phs001134) - Comprehensive genomic characterization of radiation-related papillary thyroid cancer in the Ukraine + * miRNA-Seq + * RNA-Seq + * WGS +2. CPTAC Program + * CPTAC-3 methylation data produced from the SeSAMe pipeline is now available. + * CPTAC-2 miRNA-Seq files have been replaced with better quality data. +3. HCMI-CMDC + * 31 New cases have been released to the GDC Data Portal. + * Methylation data produced from the SeSAMe pipeline is now available. +4. TCGA + * Protein expression data (RPPA) is now available for 32 projects. + * RNA-Seq data for TCGA-TGCT was replaced with files from an updated pipeline. +5. TARGET-AML - New RNA-Seq and miRNA-Seq aliquots have been released. + +A complete list of files for this release are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20210923_data_release_30.0_active.tsv.gz](https://api.gdc.cancer.gov/data/74597c3a-d048-4f5a-8e41-fa95c00f667a) +* [gdc_manifest_20210923_data_release_30.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/362bbf4b-a4a8-4591-a796-cbf4930322bc) + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* One file from a previous version of the methylation pipeline appears in the data portal (bd2f864a-3f00-47b5-815d-bd01ca21ef61; CPTAC-3). This file cannot be downloaded, but may cause bulk downloads to fail. Remove this file from any manifest or cart you plan on downloading. +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 29.0 + +* __GDC Product__: Data +* __Release Date__: March 31, 2021 + +### New updates + +1. Count Me In Program + * Aliquot-level MAFs are now available for projects CMI-ASC, CMI-MBC, and CMI-MPC. + * Somatic mutation are now explorable for projects CMI-ASC, CMI-MBC, and CMI-MPC +2. CPTAC Program + * CPTAC-2 open-access somatic mutations are now browsable through the GDC Exploration Portal. + * MSI data is now browsable through the faceted search for CPTAC-2 and CPTAC-3. +3. HCMI-CMDC - Data files and explorable mutations for 18 new cases are now available. + +A complete list of files for this release are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20210331_data_release_29.0_active.tsv.gz](https://api.gdc.cancer.gov/data/d14fe1c9-a30d-40f6-87c5-71e678e57a57) +* [gdc_manifest_20210331_data_release_29.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/501cb79d-ea36-48c8-a790-ebb5c6f73fcb) + +### Bugs Fixed Since Last Release + +* The aggregated and masked MAF files that were missing for seven pancreatic cases in CPTAC-3 have been restored to the data portal. +* The missing RNA-Seq data files for the seven normal pancreatic cases in CPTAC-3 have been restored to the data portal. + +### Known Issues and Workarounds + +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + ## Data Release 28.0 + + * __GDC Product__: Data + * __Release Date__: February 2, 2021 + + ### New updates + + 1. New Project: CMI-MPC - Count Me In - The Metastatic Prostate Cancer Project + * WXS alignments and variant calls (VCFs) are available. + 2. New Data Type: Single nuclei (snRNA-Seq) data is now available for 18 CPTAC-3 cases. See the [RNA-Seq](https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/#scrna-seq-pipeline) documentation for details. + 3. CPTAC-3 + * Data files for 147 new cases from the pancreatic cohort are now available. + * CPTAC-3 open-access somatic mutations are now browsable through the GDC Exploration Portal. + * RNA-Seq transcript fusion files are now available. + * Targeted Sequencing alignments and raw tumor-only variant calls (VCF) are now available. + 4. HCMI-CMDC + * Data files for 22 new cases are now available. + * The HCMI-CMDC open-access somatic mutations have been refreshed on the GDC Exploration Portal to reflect all newly released cases. + + A complete list of files for this release are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + + * [gdc_manifest_20210202_data_release_28.0_active.tsv.gz](https://api.gdc.cancer.gov/data/f554526d-6a0d-448e-ad56-1f757d651820) + * [gdc_manifest_20210202_data_release_28.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/fca3d58a-09d7-4f91-a2d0-9ce98e2f32ea) + + ### Bugs Fixed Since Last Release + + * None + + ### Known Issues and Workarounds + + * The aggregated and masked MAF files for seven pancreatic cases in CPTAC-3 do not appear in the Data Portal. See below for download instructions. + - [This manifest](https://api.gdc.cancer.gov/data/1a229f9a-1492-43c7-9cf4-20e52b72626e) can be used to download the files. + - To download the raw aggregated MAF files, dbGaP access to CPTAC-3 (phs001287) is required. The masked MAF files are open-access. + - The seven cases are as follows: C3L-04027, C3L-04080, C3N-02585, C3N-02768, C3N-02971, C3N-03754, and C3N-03839. The case the each file is associated with is denoted in the manifest. + * The RNA-Seq data files for the seven normal pancreatic cases in CPTAC-3 do not appear in the Data Portal. See below for download instructions. + - [This manifest](https://api.gdc.cancer.gov/data/322db59a-50b2-4903-8a94-6b7280ea6954) can be used to download the files. + - To download the alignments or splice-junction files, dbGaP access to CPTAC-3 (phs001287) is required. The other gene expression files are open-access. + - The seven cases are as follows: C3L-03513, C3L-07032, C3L-07033, C3L-07034, C3L-07035, C3L-07036, C3L-07037. The case the each file is associated with is denoted in the manifest. + * The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. + * Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. + * Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release + * Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. + * Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. + * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. + * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. + * Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg + * TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated + * TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. + * Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + + +## Data Release 27.0 Bug Fix + +* __GDC Product__: Data +* __Release Date__: November 9, 2020 + +### New updates + +1. None, see bug fix section below. + +A complete list of files for this release are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20201109_data_release_27.0_active.tsv.gz](https://api.gdc.cancer.gov/data/6bbf882a-a24f-420f-8f6b-d526c47af488) +* [gdc_manifest_20201109_data_release_27.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/765000d4-3592-4b4d-8f1e-422a46dcd448) + +### Bugs Fixed Since Last Release + +* Some files in projects CGCI-BLGSP, CGCI-HTMCP-CC, and HCMI-CMDC were marked on the portal as controlled-access, when they were supposed to be open-access. These are now downloadable as open-access files. + +### Known Issues and Workarounds + +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 27.0 + +* __GDC Product__: Data +* __Release Date__: October 29, 2020 + +### New updates + +1. Initial release for the WGS variant calling pipeline. See the [documentation](https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline/#whole-genome-sequencing-variant-calling) on WGS variant calling for more details on the available files. This includes data from the following projects: + * CGCI-BLGSP + * CGCI-HTMCP-CC + * HCMI-CMDC +2. RNA-Seq transcript fusion files are available for the following projects: + * CGCI-BLGSP + * CGCI-HTMCP-CC + * HCMI-CMDC +3. Aliquot level MAFs were released for CGCI-HTMCP-CC Targeted Sequencing variants. Open access MAFs are included. +4. 17 new cases were released for the HCMI-CMDC project. This includes WGS, WXS, and RNA-Seq data. +5. WGS alignments were released for 99 TCGA-LUAD cases (196 files). +6. Therapeutic agents (treatment) and tumor stage (diagnosis) properties were migrated to remove deprecated values and better adhere to a standardized set of values. + +A complete list of files for DR27.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20201029_data_release_27.0_active.tsv.gz](https://api.gdc.cancer.gov/data/6bbf882a-a24f-420f-8f6b-d526c47af488) +* [gdc_manifest_20201029_data_release_27.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/765000d4-3592-4b4d-8f1e-422a46dcd448) + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Some files in projects CGCI-BLGSP, CGCI-HTMCP-CC, and HCMI-CMDC are marked on the portal as controlled-access. These files are publicly downloadable using the Data Transfer Tool or API. All files from the following data types should be open-access within the previously specified projects: Biospecimen Supplement, Clinical Supplement, Gene Expression Quantification, Masked Somatic Mutation +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 26.0 + +* __GDC Product__: Data +* __Release Date__: September 8, 2020 + +### New updates + +1. New program released: + * Count Me In (CMI) + * CMI-ASC - The Angiosarcoma Project + * RNA-Seq + * WXS + * CMI-MBC - The Metastatic Breast Cancer Project + * RNA-Seq + * WXS +2. Somatic mutations are now available on the exploration portal for the following projects: + * MMRF-COMMPASS + * TARGET-ALL-P3 + * TARGET-AML + * TARGET-NBL + * TARGET-WT +3. Primary sites and disease types were updated for multiple projects to correspond to GDC Dictionary updates. + +A complete list of files for DR26.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20200908_data_release_26.0_active.tsv.gz](https://api.gdc.cancer.gov/data/9d66bc89-7f99-480e-9a6a-e4114d4c58a3) +* [gdc_manifest_20200908_data_release_26.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/8f44d8bb-09e0-43d5-bf12-6133e27c2e86) + +### Bugs Fixed Since Last Release + +* The CPTAC-3 head and neck cohort can now be queried by choosing the head and neck anatomic site on the GDC home page. + +### Known Issues and Workarounds + +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + ## Data Release 25.0 + + * __GDC Product__: Data + * __Release Date__: July 22, 2020 + + ### New updates + + 1. New data types released: + * RNA-Seq Transcript Fusion files were released for the following projects: + * TARGET-ALL-P1 + * TARGET-ALL-P2 + * TARGET-ALL-P3 + * TARGET-CCSK + * TARGET-NBL + * TARGET-OS + * TARGET-RT + * TARGET-WT + * The msi_status and msi_score properties can be queried on the GDC Portal for the CPTAC-3 project. + * To query for these fields: go to the [GDC Repository](https://portal.gdc.cancer.gov/repository), click on "Add a File Filter" at the top left of the screen, type msi_score or msi_status in the field, and click on "msi_score" or "msi_status". This should bring up the corresponding filters to use on the portal. + 2. 108 cases from the CPTAC-3 LSCC Cohort were released. Includes the following data types: + * WXS + * WGS + * RNA-Seq + * miRNA-Seq + 3. Aliquot level MAFs were released for MMRF-COMMPASS WXS variants. Open access MAFs are included. + 4. HCMI-CMDC open-access somatic mutations were released to the [Exploration Portal](https://portal.gdc.cancer.gov/exploration). + + A complete list of files for DR25.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + + * [gdc_manifest_20200722_data_release_25.0_active.tsv.gz](https://api.gdc.cancer.gov/data/515b9ae2-3f52-4b92-9475-ff59a4b846b5) + * [gdc_manifest_20200722_data_release_25.0_legacy.tsv.gz](https://api.gdc.cancer.gov/fef95b15-7541-438c-a887-126e4e04dc94) + + ### Bugs Fixed Since Last Release + + * A few supplements from CGCI-BLGSP are now associated with their correct versions. + + ### Known Issues and Workarounds + + * Currently the CPTAC-3 HNSCC cohort does not appear when the "Head and Neck" primary site is selected from the GDC home page. This cohort can be queried by clicking [here](https://portal.gdc.cancer.gov/repository?facetTab=cases&filters=%7B%22op%22%3A%22and%22%2C%22content%22%3A%5B%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22cases.primary_site%22%2C%22value%22%3A%5B%22other%20and%20ill-defined%20sites%22%5D%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%5B%22CPTAC-3%22%5D%7D%7D%5D%7D) + * The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. + * Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. + * Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release + * Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. + * Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. + * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. + * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. + * Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg + * TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated + * TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. + * Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 24.0 + +* __GDC Product__: Data +* __Release Date__: May 7, 2020 + +### New updates + +1. New project released: CGCI-HTMCP-CC - HIV+ Tumor Molecular Characterization Project - Cervical Cancer + * RNA-Seq: Alignments and gene expression levels + * miRNA-Seq: Alignments and miRNA expression levels + * WGS: Alignments + * Targeted Sequencing: Alignments + +2. 110 new cases were released from the HNSCC cohort of CPTAC-3. This includes WXS, WGS, RNA-Seq and miRNA-Seq data. + +3. Aliquot-level WXS MAFs are now available from the following projects: + * CPTAC-2 + * CPTAC-3 + +A complete list of files for DR24.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20200507_data_release_24.0_active.tsv.gz](https://api.gdc.cancer.gov/data/8bc60b7b-8b13-4622-af1a-c684b9fa74c7) +* [gdc_manifest_20200507_data_release_24.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/a3966236-f6ba-4cba-8324-22b5f16963ee) + + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Currently the CPTAC-3 HNSCC cohort does not appear when the "Head and Neck" primary site is selected from the GDC home page. This cohort can be queried by clicking [here](https://portal.gdc.cancer.gov/repository?facetTab=cases&filters=%7B%22op%22%3A%22and%22%2C%22content%22%3A%5B%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22cases.primary_site%22%2C%22value%22%3A%5B%22other%20and%20ill-defined%20sites%22%5D%7D%7D%2C%7B%22op%22%3A%22in%22%2C%22content%22%3A%7B%22field%22%3A%22cases.project.project_id%22%2C%22value%22%3A%5B%22CPTAC-3%22%5D%7D%7D%5D%7D) +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 23.0 + +* __GDC Product__: Data +* __Release Date__: April 7, 2020 + +### New updates + +1. New data types released: + * Aliquot-level MAFs: MAF Files with mutations derived from one tumor/normal pair + * HCMI-CMDC + * TARGET-ALL-P2 + * TARGET-ALL-P3 + * TARGET-AML + * TARGET-NBL + * TARGET-OS + * TARGET-WT + * Note: Previously released TARGET project level MAFs can be downloaded with the following manifest: [TARGET_Project-Level-MAF_GDC-Manifest.txt](https://api.gdc.cancer.gov/data/64be0d29-ba73-45c3-b4ec-646a5aa63980) + * Copy number segment and estimate files from SNP6 ASCAT + * All TCGA Projects + * TARGET-ALL-P2 + * TARGET-AML + +2. To accommodate users who prefer to use project-level MAFs, a MAF aggregation tool was developed by the GDC: + * [Github Release](https://github.com/NCI-GDC/gdc-maf-tool/releases) + +3. New RNA-Seq data was released from HCMI-CMDC for nine additional cases. + +4. Clinical updates were performed for the following projects + * CGCI-BLGSP + * HCMI-CMDC + * WCDT-MCRPC + +A complete list of files for DR23.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20200407_data_release_23.0_active.tsv.gz](https://api.gdc.cancer.gov/data/e04d9cbf-3759-4af5-805b-a3ebbad0d7e3) +* [gdc_manifest_20200407_data_release_23.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/328e7829-1cd0-474a-8ff3-a68a2aa91f28) + + +### Bugs Fixed Since Last Release + +* The 6 HCMI-CMDC cases without clinical data now have clinical data. +* Most of the "associated_entities" fields in CGCI-BLGSP were not populated correct, this has been resolved. + +### Known Issues and Workarounds + +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 22.0 + +* __GDC Product__: Data +* __Release Date__: January 16, 2020 + +### New updates + +1. New projects released: + * WCDT-MCRPC - Genomic Characterization of Metastatic Castration Resistant Prostate Cancer (phs001648) + * RNA-Seq; WGS Data +2. New data from HCMI-CMDC + * 16 New Cases + * Includes WXS, WGS, and RNA-Seq data +3. New data from CPTAC-3 + * 108 New Cases + * Includes WXS, WGS, and RNA-Seq data + * miRNA-Seq data for currently released cases + +A complete list of files for DR22.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20200116_data_release_22.0_active.tsv.gz](https://api.gdc.cancer.gov/data/7a4c2f58-0936-44d3-848e-39ffa59a3683) +* [gdc_manifest_20200116_data_release_22.0_legacy.tsv.gz](https://api.gdc.cancer.gov/data/896aa2d9-e7c5-42d1-9943-c5bd285f5d03) + + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* 6 of the HCMI-CMDC cases are missing clinical nodes + * HCM-CSHL-0060-C18 + * HCM-CSHL-0089-C25 + * HCM-CSHL-0090-C25 + * HCM-CSHL-0092-C25 + * HCM-CSHL-0091-C25 + * HCM-CSHL-0057-C18 +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 21.0 + +* __GDC Product__: Data +* __Release Date__: December 10, 2019 + +### New updates + +1. New projects released: + * GENIE - AACR Project Genomics Evidence Neoplasia Information Exchange (phs001337) + * Includes Targeted Sequencing, Transcript Fusion, Copy Number Estimate from GENIE 5.0 + * AACR Project GENIE is divided by sequencing center: + * GENIE-MSK + * GENIE-DFCI + * GENIE-MDA + * GENIE-JHU + * GENIE-UHN + * GENIE-VICC + * GENIE-GRCC + * GENIE-NKI + +A complete list of files for DR21.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20191210_data_release_21.0_active.txt.gz](https://api.gdc.cancer.gov/data/1b08d5fd-7510-4efb-a6ff-4f564a671ffd) +* [gdc_manifest_20191210_data_release_21.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/482409bc-f1a4-4d10-8456-6b154266335b) + + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* The Copy Number Estimate files in GENIE are labeled on the portal as TXT while the files are actually in TSV format. +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + +## Data Release 20.0 + +* __GDC Product__: Data +* __Release Date__: November 11, 2019 + +### New updates + +1. New projects released: + * CPTAC-2 - CPTAC Proteogenomic Confirmatory Study (phs000892) + * Includes WXS, RNA-Seq, and miRNA-Seq + * OHSU-CNL - Genomic landscape of Neutrophilic Leukemias of Ambiguous Diagnosis (phs001799) + * Includes WXS and RNA-Seq + * No VCF files will be included at this time. They will follow in a later release. +2. New TARGET data released + * TARGET-OS: WGS, WXS + * TARGET-NBL: WGS + * TARGET-AML: miRNA +3. CGCI-BLGSP miRNA-Seq released + + +A complete list of files for DR20.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + + +* [gdc_manifest_20191111_data_release_20.0_active.txt.gz](https://api.gdc.cancer.gov/data/c802c963-e974-422e-88bc-793366026d6a) +* [gdc_manifest_20191111_data_release_20.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/402be47c-a39a-4f5b-9845-102c58a3335e) + + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + + + +## Data Release 19.1 + +* __GDC Product__: Data +* __Release Date__: November 6, 2019 + +### New updates + +* The following cases are no longer available in the GDC Data Portal. They had no data files associated with them in DR 19 so there are no changes in file availability in this release. + * TARGET-00-NAAENF + * TARGET-00-NAAENG + * TARGET-00-NAAENH + * TARGET-00-NAAENI + * TARGET-00-NAAENJ + * TARGET-00-NAAENK + * TARGET-00-NAAENL + * TARGET-00-NAAENM + * TARGET-00-NAAENN + * TARGET-00-NAAENP + * TARGET-00-NAAENR + * TARGET-00-NAAEPE + +A complete list of files for DR19.1 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20190917_data_release_19.0_active.txt.gz](https://api.gdc.cancer.gov/data/04800e48-6404-4d44-ad64-5b58aa2b78a0) +* [gdc_manifest_20190917_data_release_19.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/a0a68dca-fc58-4d1c-aaad-1357807dcbd7) + + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 19.0 + +* __GDC Product__: Data +* __Release Date__: September 17, 2019 + +### New updates + +1. New projects released: + * BEATAML1.0-COHORT - Functional Genomic Landscape of Acute Myeloid Leukemia (phs001657) + * Includes WXS and RNA-Seq +2. New TARGET data released + * TARGET-ALL-P1 RNA-Seq + * TARGET-ALL-P2 RNA-Seq, WXS, and miRNA-Seq + * TARGET-ALL-P3 miRNA-Seq + * TARGET-AML WXS, WGS, and miRNA-Seq + * TARGET-NBL WXS and RNA-Seq + * TARGET-RT WGS and RNA-Seq + * TARGET-WT WGS, WXS, and RNA-Seq +3. Additional CGCI-BLGSP WGS data released +4. Pindel VCFs released for TARGET-ALL-P2, TARGET-ALL-P3, TARGET-AML, TARGET-NBL, TARGET-WT, MMRF-COMMPASS, HCMI-CMDC, and CPTAC-3 +5. Disease-specific staging properties for many projects were released + + +A complete list of files for DR19.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20190917_data_release_19.0_active.txt.gz](https://api.gdc.cancer.gov/data/04800e48-6404-4d44-ad64-5b58aa2b78a0) +* [gdc_manifest_20190917_data_release_19.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/a0a68dca-fc58-4d1c-aaad-1357807dcbd7) + + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 18.0 + +* __GDC Product__: Data +* __Release Date__: July 8, 2019 + +### New updates + +1. New Projects released + * MMRF-COMMPASS - Multiple Myeloma CoMMpass Study (phs000748) + * Includes WGS, WXS, and RNA-Seq + * ORGANOID-PANCREATIC - Pancreas Cancer Organoid Profiling (phs001611) + * Includes WGS, WXS, and RNA-Seq + * TARGET-ALL-P1 - Acute Lymphoblastic Leukemia - Phase I (phs000218) + * Includes WGS + * TARGET-ALL-P2 - Acute Lymphoblastic Leukemia - Phase II (phs000218) + * Includes WGS + * CGCI-BLGSP - Burkitt Lymphoma Genome Sequencing Project (phs000235) + * Includes WGS and RNA-Seq +2. New versions of RNA-Seq data for TARGET-ALL-P3 +3. New RNA-Seq data for TARGET-CCSK +4. New RNA-Seq data for TARGET-OS + + +A complete list of files for DR18.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20190708_data_release_18.0_active.txt.gz](https://api.gdc.cancer.gov/data/0287c593-2450-4d80-8307-2f031c7b34d7) +* [gdc_manifest_20190708_data_release_18.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/95a277cf-c0f8-4c61-82cc-8467ebb658e9) + + +### Bugs Fixed Since Last Release + +* New versions of RNA-Seq data for TARGET-ALL-P3 resolve issue with missing reads from BAM files. + +### Known Issues and Workarounds + +* Some tumor-only annotated VCFs (not raw VCFs) could have a small proportion of variants that appear twice. Tumor-only annotated VCFs can be identified by searching for workflow "GATK4 MuTect2 Annotation" +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file.* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + +## Data Release 17.1 + +* __GDC Product__: Data +* __Release Date__: June 12, 2019 + +### New updates + +1. Rebuilt indices for NCICCR-DLBCL and CTSP-DLBCL1. Fewer files viewable in GDC Data Portal or API. + +A complete list of files for DR17.1 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20190612_data_release_17.1_active.txt.gz](https://api.gdc.cancer.gov/data/7c890b5a-cc23-44b1-821d-7283b5604fdf) +* [gdc_manifest_20190612_data_release_17.1_legacy.txt.gz](https://api.gdc.cancer.gov/data/4d41c32c-90c3-4413-aa93-2dff5d8d41a8) + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + + +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET ALL-P3 RNA-Seq results from DR14 are missing ~18% of reads. Downsampling appears to be completely random and count files have a very high correlation (>99.99%) with complete data. New versions of these files will be created that include the entire set of reads. + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + + +## Data Release 17.0 + +* __GDC Product__: Data +* __Release Date__: June 5, 2019 + +### New updates + +1. New Projects released + * HCMI-CMDC - NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI) (phs001486) + * BEATAML1.0-CRENOLANIB - Clinical Resistance to Crenolanib in Acute Myeloid Leukemia Due to Diverse Molecular Mechanisms (phs001628) +2. RNA-Seq data for NCICCR-DLBCL and CTSP-DLBCL1 are released +3. ATAC-Seq data for TCGA projects are released +4. CPTAC-3 RNA-Seq data are released +5. Clinical data updates for TCGA - to see parser code updates review [API v1.20 release notes](https://docs.gdc.cancer.gov/API/Release_Notes/API_Release_Notes/#v1200) +6. Clinical data updates for other projects to accommodate migration of vital_status, days_to_birth, and days_to_death from the Diagnosis to the Demographic node + +A complete list of files for DR17.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20190605_data_release_17.0_active.txt.gz](https://api.gdc.cancer.gov/data/0493c694-d33a-4005-9461-a0332ce0b663) +* [gdc_manifest_20190605_data_release_17.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/05681495-e346-4e51-ab16-d809bee8a0fa). + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + + +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* TCGA Projects + * Incorrect information about treatment may be included for patients within TCGA-HNSC and TCGA-LGG. Please refer to the clinical XML for accurate information on treatment + * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. + * Two tissue slide images are unavailable for download from GDC Data Portal + * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + * Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). + * Tumor grade property is not populated + * Progression_or_recurrence property is not populated +* TARGET projects + * TARGET ALL-P3 RNA-Seq results from DR14 are missing ~18% of reads. Downsampling appears to be completely random and count files have a very high correlation (>99.99%) with complete data. New versions of these files will be created that include the entire set of reads. + * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D + * 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal + * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank + * There are two cases with identical submitter_id `TARGET-10-PARUYU` + * Some TARGET cases are missing `days_to_last_follow_up` + * Some TARGET cases are missing `age_at_diagnosis` + * Some TARGET files are not connected to all related aliquots + * Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) + * The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data + * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. + * No data from TARGET-MDLS is available. +* Issues in the Legacy Archive + * Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available + * SDF Files are not linked to Project or Case in the Legacy Archive + * Two biotab files are not linked to Project or Case in the Legacy Archive + * SDRF files are not linked to Project or Case in the Legacy Archive + * TARGET-MDLS cases do not have disease_type or primary_site populated + + + + + +## Data Release 16.0 + +* __GDC Product__: Data +* __Release Date__: March 26, 2019 + +### New updates + +1. The CPTAC-3 project (phs001287) is released with WXS and WGS data. RNA-Seq will be released at a later date. Additional project details can be found at on the [CPTAC Data Source page](https://gdc.cancer.gov/about-gdc/contributed-genomic-data-cancer-research/clinical-proteomic-tumor-analysis-consortium-cptac). +2. TARGET-ALL-P3 (phs000218) WGS BAM files are released. +3. VAREPOP-APOLLO (phs001374) VCF files are released. + +A complete list of files for DR16.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20190326_data_release_16.0_active.txt.gz](https://api.gdc.cancer.gov/data/88cd6a25-b46d-435d-ade0-aae709f1f9e3) +* [gdc_manifest_20190326_data_release_16.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/f8b6460c-eec1-4f94-8c2c-f17387549d70). + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* TARGET ALL-P3 RNA-Seq results from DR14 are missing ~18% of reads. Downsampling appears to be completely random and count files have a very high correlation (>99.99%) with complete data. New versions of these files will be created that include the entire set of reads. +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. +* 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal +* Two tissue slide images are unavailable for download from GDC Data Portal +* The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + +* There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank +* There are two cases with identical submitter_id `TARGET-10-PARUYU` +* TARGET-MDLS cases do not have disease_type or primary_site populated +* Some TARGET cases are missing `days_to_last_follow_up` +* Some TARGET cases are missing `age_at_diagnosis` +* Some TARGET files are not connected to all related aliquots +* Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data +* Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* No data from TARGET-MDLS is available. +* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available +* SDF Files are not linked to Project or Case in the Legacy Archive +* Two biotab files are not linked to Project or Case in the Legacy Archive +* SDRF files are not linked to Project or Case in the Legacy Archive +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* Tumor grade property is not populated +* Progression_or_recurrence property is not populated + + + + +## Data Release 15.0 + +* __GDC Product__: Data +* __Release Date__: February 20, 2019 + +### New updates + +1. TARGET-ALL-P3 is now available and includes RNA-Seq and WXS data. +2. New RNA-Seq workflow is now being utilized for new projects. More details can be found in the [RNA-Seq pipeline documentation](../../Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/#rna-seq-alignment-workflow). +3. New tumor only variant calling pipeline is now being utilized for new projects. More details can be found in the [Tumor only pipeline documentation](../../Data/Bioinformatics_Pipelines/DNA_Seq_Variant_Calling_Pipeline/#tumor-only-variant-calling-workflow). + + +A complete list of files for DR15.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20190220_data_release_15.0_active.txt.gz](https://api.gdc.cancer.gov/data/5c44ddf9-2bab-4710-8012-dd677ff09547) +* [gdc_manifest_20190220_data_release_15.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/46aaf192-3d31-4ced-a422-1cd8d3b5df21). + +### Bugs Fixed Since Last Release + +* None + +### Known Issues and Workarounds + +* The read alignment end coordinates in the x.isoform.quantification.txt files produced by the miRNA pipeline are exclusive (i.e. offset by 1) for all TCGA miRNA legacy (GRCh37/hg19) and current harmonized (GRCh38/hg38) miRNA data. This error has no impact on miRNA alignment or quantification - only the coordinates reported in the quantification file. +* TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. +* 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal +* Two tissue slide images are unavailable for download from GDC Data Portal +* The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + +* There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank +* There are two cases with identical submitter_id `TARGET-10-PARUYU` +* TARGET-MDLS cases do not have disease_type or primary_site populated +* Some TARGET cases are missing `days_to_last_follow_up` +* Some TARGET cases are missing `age_at_diagnosis` +* Some TARGET files are not connected to all related aliquots +* Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data +* Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* No data from TARGET-MDLS is available. +* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available +* SDF Files are not linked to Project or Case in the Legacy Archive +* Two biotab files are not linked to Project or Case in the Legacy Archive +* SDRF files are not linked to Project or Case in the Legacy Archive +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* Tumor grade property is not populated +* Progression_or_recurrence property is not populated + + +## Data Release 14.0 + +* __GDC Product__: Data +* __Release Date__: December 18, 2018 + +### New updates + +1. Copy Number Variation (CNV) data derived from GISTIC2 results are now available for download for TCGA projects +2. New miRNA data available for 181 aliquots for TARGET and TCGA +3. Released two SNP6 files (6cd4ef5e-324a-4ace-8779-7a33bd559c83, dfa89ee9-6ee5-460b-bd58-b5ca0e9cb7ac) +4. New versions of TCGA biospecimen supplements are available +5. Updated primary site for `TCGA-AG-3881` to `Unknown` +6. 8 New Harmonized WGS BAM files for TARGET-WT, TARGET-NBL, TARGET-AML added to the portal + +A complete list of files for DR14.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: + +* [gdc_manifest_20181218_data_release_14.0_active.txt.gz](https://api.gdc.cancer.gov/data/2783d247-9784-4f53-a486-61e041520ab5) +* [gdc_manifest_20181218_data_release_14.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/221b0d00-af70-4e2b-ac02-4b6c5d62d43a). + + +### Bugs Fixed Since Last Release + +* FM-AD clinial and biospecimen supplements are now correctly labeled as TSV rather than XLSX + +### Known Issues and Workarounds + +* TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. + * TARGET-20-PASJGZ-04A-02D + * TARGET-30-PAPTLY-01A-01D + * TARGET-20-PAEIKD-09A-01D + * TARGET-20-PASMYS-14A-02D + * TARGET-20-PAMYAS-14A-02D + * TARGET-10-PAPZST-09A-01D +* Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release +* 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. +* 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal +* Two tissue slide images are unavailable for download from GDC Data Portal +* The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. + +* There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank +* There are two cases with identical submitter_id `TARGET-10-PARUYU` +* TARGET-MDLS cases do not have disease_type or primary_site populated +* Some TARGET cases are missing `days_to_last_follow_up` +* Some TARGET cases are missing `age_at_diagnosis` +* Some TARGET files are not connected to all related aliquots +* Samples of TARGET sample_type `Recurrent Blood Derived Cancer - Bone Marrow` are mislabeled as `Recurrent Blood Derived Cancer - Peripheral Blood`. A workaround is to look at the sample barcode, which is -04 for `Recurrent Blood Derived Cancer - Bone Marrow`. (e.g. `TARGET-20-PAMYAS-04A-03R`) +* Mutation frequency may be underestimated when using MAF files for genes that overlap other genes. This is because MAF files only record one gene per variant. +* Most intronic mutations are removed for MAF generation. However, validated variants may rescue these in some cases. Therefore intronic mutations in MAF files are not representative of those called by mutation callers. +* The latest TARGET data is not yet available at the GDC. For the complete and latest data, please see the [TARGET Data Matrix](https://ocg.cancer.gov/programs/target/data-matrix). Data that is not present or is not the most up to date includes: + * All microarray data and metadata + * All sequencing analyzed data and metadata + * 1180 of 12063 sequencing runs of raw data +* Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). +* Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. +* BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. +* No data from TARGET-MDLS is available. +* Slide barcodes (`submitter_id` values for Slide entities in the Legacy Archive) are not available +* SDF Files are not linked to Project or Case in the Legacy Archive +* Two biotab files are not linked to Project or Case in the Legacy Archive +* SDRF files are not linked to Project or Case in the Legacy Archive +* Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg +* Tumor grade property is not populated +* Progression_or_recurrence property is not populated + + ## Data Release 13.0 @@ -33,8 +2606,8 @@ A complete list of files for DR13.0 are listed for the GDC Data Portal and the GDC Legacy Archive are found below: -* [gdc_manifest_20180927_data_release_13.0_active.txt.gz](gdc_manifest_20180927_data_release_13.0_active.txt.gz) -* [gdc_manifest_20180927_data_release_13.0_legacy.txt.gz](gdc_manifest_20180927_data_release_13.0_legacy.txt.gz). +* [gdc_manifest_20180927_data_release_13.0_active.txt.gz](https://api.gdc.cancer.gov/data/d746f9ec-32d6-4d0a-aad3-a2481f5453a9) +* [gdc_manifest_20180927_data_release_13.0_legacy.txt.gz](https://api.gdc.cancer.gov/data/00c5fa11-dab8-4cdc-be3e-8337b9388295). ### Bugs Fixed Since Last Release @@ -44,10 +2617,10 @@ A complete list of files for DR13.0 are listed for the GDC Data Portal and the G ### Known Issues and Workarounds -* 506 Copy Number Segment and 36 Slide Image files are designated as controlled-access on the GDC Data Portal. These files are actually open-access and will be downloadable without a token using [this manifest](gdc_manifest_20181003_data_release_13.0_cnv_slides.txt). +* 506 Copy Number Segment and 36 Slide Image files are designated as controlled-access on the GDC Data Portal. These files are actually open-access and will be downloadable without a token using [this manifest](https://api.gdc.cancer.gov/data/d2da95c4-2576-4018-826f-9a4e1b6aabf5). * 2 Copy Number Segment files from TCGA-TGCT do not appear on the GDC Portal. They can be downloaded using the Data Transfer Tool using the following UUIDs. * 6cd4ef5e-324a-4ace-8779-7a33bd559c83 - RAMPS_p_TCGA_Batch_430_NSP_GenomeWideSNP_6_E07_1538238.nocnv_grch38.seg.v2.txt - * dfa89ee9-6ee5-460b-bd58-b5ca0e9cb7ac - RAMPS_p_TCGA_Batch_430_NSP_GenomeWideSNP_6_E07_1538238.grch38.seg.v2.txt + * dfa89ee9-6ee5-460b-bd58-b5ca0e9cb7ac - RAMPS_p_TCGA_Batch_430_NSP_GenomeWideSNP_6_E07_1538238.grch38.seg.v2.txt * TARGET CGI BAMs in the Legacy Archive for the following aliquots should not be used because they were not repaired and concatenated into their original composite BAM files by CGHub. * TARGET-20-PASJGZ-04A-02D * TARGET-30-PAPTLY-01A-01D @@ -57,7 +2630,7 @@ A complete list of files for DR13.0 are listed for the GDC Data Portal and the G * TARGET-10-PAPZST-09A-01D * Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. -* 11 bam files for TARGET-NBL RNA-Seq are not available in the GDC Data portal +* 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal * Two tissue slide images are unavailable for download from GDC Data Portal * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. @@ -76,7 +2649,7 @@ A complete list of files for DR13.0 are listed for the GDC Data Portal and the G * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MDLS is available. @@ -104,8 +2677,8 @@ A complete list of files for DR13.0 are listed for the GDC Data Portal and the G 4. Updated Copy Number Segment and Masked Copy Number Segment files are now available. These were generated using an improved mapping of hg38 coordinates for the Affymetrix SNP6.0 probe set. 5. VCF files containing SNVs produced from TARGET WGS CGI data are available. The variant calls were initially produced by CGI and lifted over to hg38. -Updated files for this release are listed [here](DR12.0_files_swap.txt.gz). -A complete list of files for DR12.0 are listed for the GDC Data Portal [here](gdc_manifest_20180613_data_release_12.0_active.txt.gz) and the GDC Legacy Archive [here](gdc_manifest_20180613_data_release_12.0_legacy.txt.gz). +Updated files for this release are listed [here](https://api.gdc.cancer.gov/data/780f8b48-895d-4bdd-b53a-fcead5adc3c6). +A complete list of files for DR12.0 are listed for the GDC Data Portal [here](https://api.gdc.cancer.gov/data/cb8fe4f2-8f40-4826-9db5-9a98d7a6c4b5) and the GDC Legacy Archive [here](https://api.gdc.cancer.gov/data/aa131b7d-45af-4dba-871a-9a6081bb39a3). ### Bugs Fixed Since Last Release @@ -118,7 +2691,7 @@ A complete list of files for DR12.0 are listed for the GDC Data Portal [here](gd * Some miRNA files with QC failed reads were not swapped in DR11.0. 361 aliquots remain to be swapped in a later release * 74 Diagnostic TCGA slides are attached to a portion rather than a sample like the rest of the diagnostic slides. The reflects how these original samples were handled. * 36 Diagnostic TCGA slides are not yet available in the active GDC Portal. They are still available in the GDC Legacy Archive. -* 11 bam files for TARGET-NBL RNA-Seq are not available in the GDC Data portal +* 11 BAM files for TARGET-NBL RNA-Seq are not available in the GDC Data portal * Two tissue slide images are unavailable for download from GDC Data Portal * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` are not available. These VCFs files will be replaced in a later release. @@ -137,7 +2710,7 @@ A complete list of files for DR12.0 are listed for the GDC Data Portal [here](gd * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -149,7 +2722,7 @@ A complete list of files for DR12.0 are listed for the GDC Data Portal [here](gd * TCGA-G8-6914 * TCGA-GR-7351 * TCGA-GR-7353 -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MDLS is available. @@ -174,8 +2747,8 @@ A complete list of files for DR12.0 are listed for the GDC Data Portal [here](gd 1. Updated miRNA files to remove QCFail reads. This included all BAM and downstream count files. 2. TCGA Tissue slide images now available in GDC Data Portal. Previously these were found only in the Legacy Archive -Updated files for this release are listed [here](DR11.0_files_swap.txt.gz). -A complete list of files for DR11.0 are listed for the GDC Data Portal [here](gdc_manifest_20180521_data_release_11.0_active.txt.gz) and the GDC Legacy Archive [here](gdc_manifest_20180521_data_release_11.0_legacy.txt.gz). +Updated files for this release are listed [here](https://api.gdc.cancer.gov/data/0ca04712-221b-44d5-b1f0-d0e64e204f31). +A complete list of files for DR11.0 are listed for the GDC Data Portal [here](https://api.gdc.cancer.gov/data/a66a1432-928d-45b3-a07b-40c0ca8fa64e) and the GDC Legacy Archive [here](https://api.gdc.cancer.gov/data/8f21c0e9-65a4-4912-a528-fdcc2531788c). ### Bugs Fixed Since Last Release @@ -185,7 +2758,7 @@ A complete list of files for DR11.0 are listed for the GDC Data Portal [here](gd ### Known Issues and Workarounds * Two tissue slide images are unavailable for download from GDC Data Portal -* RNA-Seq files for TARGET-NBL are attached to the incorrect aliquot. The BAM files contain the correct information in their header but the connection in the GDC to read groups and aliquots is incorrect. The linked file below contains a mapping between aliquots where file are currently associated and the aliquot where they should instead be associated [(mapping file)](correct_aliquot_mappings.tsv). +* RNA-Seq files for TARGET-NBL are attached to the incorrect aliquot. The BAM files contain the correct information in their header but the connection in the GDC to read groups and aliquots is incorrect. The linked file below contains a mapping between aliquots where file are currently associated and the aliquot where they should instead be associated [(mapping file)](https://api.gdc.cancer.gov/data/5f666089-8a49-4478-a126-5afa58575519). * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` were not replaced in DR10.0 and thus do not contain indels. However, the indels from this aliquot can be found in the MAF files and are displayed in the Exploration section in the Data Portal. These VCFs files will be replaced in a later release. * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank @@ -204,7 +2777,7 @@ A complete list of files for DR11.0 are listed for the GDC Data Portal [here](gd * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -216,7 +2789,7 @@ A complete list of files for DR11.0 are listed for the GDC Data Portal [here](gd * TCGA-G8-6914 * TCGA-GR-7351 * TCGA-GR-7353 -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MDLS is available. @@ -245,7 +2818,7 @@ None ### Known Issues and Workarounds -* RNA-Seq files for TARGET-NBL are attached to the incorrect aliquot. The BAM files contain the correct information in their header but the connection in the GDC to read groups and aliquots is incorrect. The linked file below contains a mapping between aliquots where file are currently associated and the aliquot where they should instead be associated [(mapping file)](correct_aliquot_mappings.tsv). +* RNA-Seq files for TARGET-NBL are attached to the incorrect aliquot. The BAM files contain the correct information in their header but the connection in the GDC to read groups and aliquots is incorrect. The linked file below contains a mapping between aliquots where file are currently associated and the aliquot where they should instead be associated [(mapping file)](https://api.gdc.cancer.gov/data/5f666089-8a49-4478-a126-5afa58575519). * The raw and annotated VarScan VCF files for aliquot `TCGA-VR-A8ET-01A-11D-A403-09` were not replaced in DR10.0 and thus do not contain indels. However, the indels from this aliquot can be found in the MAF files and are displayed in the Exploration section in the Data Portal. These VCFs files will be replaced in a later release. * There are 5051 TARGET files for which `experimental_strategy`, `data_format`, `platform`, and `data_subtype` are blank @@ -264,7 +2837,7 @@ None * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -276,7 +2849,7 @@ None * TCGA-G8-6914 * TCGA-GR-7351 * TCGA-GR-7353 -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MDLS is available. @@ -304,7 +2877,7 @@ None 5. Update VarScan VCF files Updated files for this release are listed [here](DR10.0_files_swap.txt.gz). -A complete list of files for DR10.0 are listed for the GDC Data Portal [here](gdc_manifest_20171221_data_release_10.0_active.txt.gz) and the GDC Legacy Archive [here](gdc_manifest_20171221_data_release_10.0_legacy.txt.gz). +A complete list of files for DR10.0 are listed for the GDC Data Portal [here](https://api.gdc.cancer.gov/data/8483eced-0db2-4371-aa9e-d9061f5c1abf) and the GDC Legacy Archive [here](https://api.gdc.cancer.gov/data/0dd41708-d128-41bb-b78b-8c4f77d61afd). ### Bugs Fixed Since Last Release @@ -330,7 +2903,7 @@ None * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -342,7 +2915,7 @@ None * TCGA-G8-6914 * TCGA-GR-7351 * TCGA-GR-7353 -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MDLS is available. @@ -370,8 +2943,8 @@ None 2. Updated RNA-Seq data for TARGET NBL * Includes new BAM and count files -Updated files for this release are listed [here](DR9.0_files_swap.txt.gz). -A complete list of files for DR9.0 are listed [here](gdc_manifest_20171024_data_release_9.0_active.txt.gz). +Updated files for this release are listed [here](https://api.gdc.cancer.gov/data/1acddc99-4912-4c8d-9477-585fad2d7910). +A complete list of files for DR9.0 are listed [here](https://api.gdc.cancer.gov/data/b6e22aaa-4d66-4395-8769-eb74efbcda5c). ### Bugs Fixed Since Last Release @@ -389,7 +2962,7 @@ None * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -401,7 +2974,7 @@ None * TCGA-G8-6914 * TCGA-GR-7351 * TCGA-GR-7353 -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MDLS is available. @@ -422,8 +2995,8 @@ None 1. Released updated miRNA quantification files to address double counting of some normalized counts described in DR7.0 release notes. -Updated files for this release are listed [here](DR8.0_files_swap.txt). -A Complete list of files for DR8.0 are listed [here](gdc_manifest_20170822_data_release_8.0_active.txt.gz). +Updated files for this release are listed [here](https://api.gdc.cancer.gov/data/8db48519-45d5-43a5-93ad-35585b38d229). +A Complete list of files for DR8.0 are listed [here](https://api.gdc.cancer.gov/data/435c3cd0-71d0-4696-8cc7-2f3f8db8f998). ### Bugs Fixed Since Last Release @@ -439,7 +3012,7 @@ None * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -451,7 +3024,7 @@ None * TCGA-G8-6914 * TCGA-GR-7351 * TCGA-GR-7353 -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MDLS is available. @@ -477,8 +3050,8 @@ None 2. Protected MAF files are updated to include flags for OxoG and strand bias. 2. Annotated VCFs are updated to include flags for OxoG artifacts and strand bias. -Updated files for this release are listed [here](DR7.0_files_swap.txt). -A Complete list of files for DR7.0 are listed [here](gdc_manifest_20170629_data_release_7.0.txt.gz) +Updated files for this release are listed [here](https://api.gdc.cancer.gov/data/0e59555f-7688-4473-95f1-5ee2d369a274). +A Complete list of files for DR7.0 are listed [here](https://api.gdc.cancer.gov/data/1b7996f6-e3c6-447c-878f-a4a3ad83dce2) ### Bugs Fixed Since Last Release @@ -503,7 +3076,7 @@ None * All sequencing analyzed data and metadata * 1180 of 12063 sequencing runs of raw data * Demographic information for some TARGET patients is incorrect. The correct information can be found in the associated clinical supplement file. Impacted patients are TARGET-50-PAJNUS. -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -515,7 +3088,7 @@ None * TCGA-G8-6914 * TCGA-GR-7351 * TCGA-GR-7353 -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. * No data from TARGET-MLDS is available. @@ -541,7 +3114,7 @@ None 2. Protected MAFs are updated to include additional variant annotation information 3. Some MuTect2 VCFs updated to include dbSNP and COSMIC annotations found in other VCFs -Updated files for this release are listed [here](DR6.0_files_swap.txt). +Updated files for this release are listed [here](https://api.gdc.cancer.gov/data/cf2c9b07-2683-4337-8987-9f50f12cd5d1). ### Bugs Fixed Since Last Release @@ -549,7 +3122,7 @@ None ### Known Issues and Workarounds -* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](DLBC_Affected_Files.txt). +* There are 11 cases in project TCGA-DLBC that are known to have incorrect WXS data in the GDC Data Portal. Impacted cases are listed below. This affects the BAMs and VCFs associated with these cases in the GDC Data Portal. Corrected BAMs can be found in the GDC Legacy Archive. Variants from affected aliquots appear in the protected MAFs with GDC_FILTER=ContEst to indicate a sample contamination problem, but are removed during the generation of the Somatic MAF file. In a later release we will supply corrected BAM, VCF, and MAF files for these cases. In the mean time, we advise you not to use any of the WXS files associated with these cases in the GDC Data Portal. A list of these files can be found here. [Download list of affected files](https://api.gdc.cancer.gov/data/370678aa-432e-441b-8828-09c168cf1062). * TCGA-FF-8062 * TCGA-FM-8000 * TCGA-G8-6324 @@ -562,7 +3135,7 @@ None * TCGA-GR-7351 * TCGA-GR-7353 * Variants found in VCF and MAF files may contain OxoG artifacts, which are produced during library preparation and may result in the apparent substitutions of C to A or G to T in certain sequence contexts. In the future we will plan to label potential oxoG artifacts in the MAF files. -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Some validated somatic mutations may not be present in open-access MAF files. Please review the protected MAF files in the GDC Data Portal if you are unable to find your mutation in the open-access files. * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. @@ -576,7 +3149,7 @@ None * Progression_or_recurrence property is not populated -Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_notes_manifest.txt) +Details are provided in [Data Release Manifest](https://api.gdc.cancer.gov/data/bb0096b7-efbe-4335-92d1-22b0a64fc0a4)
## Data Release 5.0 @@ -587,11 +3160,11 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_no ### New updates 1. Additional annotations from TCGA DCC are available - * Complete list of updated TCGA files is found [here](DR5.0_CHANGES_TCGA.xlsx) + * Complete list of updated TCGA files is found [here](https://api.gdc.cancer.gov/data/1d7ea03e-ed53-4fe5-90e5-0866c5ff0237) 2. Clinical data added for TARGET ALL P1 and P2 3. Pathology reports now have submitter IDs as assigned by the BCR 4. TARGET Data refresh - * Most recent biospecimen and clinical information from the TARGET DCC. New imported files are listed [here](DR5.0_changes_TARGET.xlsx) + * Most recent biospecimen and clinical information from the TARGET DCC. New imported files are listed [here](https://api.gdc.cancer.gov/data/8523d953-9fcb-41c5-ab83-7ca9eacdfba9) * Updated indexed biospecimen and clinical metadata * Updated SRA XMLs files * Does not include updates to TARGET NBL @@ -603,7 +3176,7 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_no ### Known Issues and Workarounds -* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](tcga-annotations-unavailable-20170315.json). +* Some TCGA annotations are unavailable in the Legacy Archive or Data Portal. These annotations can be found [here](https://api.gdc.cancer.gov/data/62461eae-0cc7-4833-bcec-76c73f37858c). * Some validated somatic mutations may not be present in open-access MAF files. When creating open-access MAF files from the protected versions we are extremely conservative in removing potential germline variants. Our approach is to remove all mutations that are present in dbSNP. In a subsequent release we will provide updated open-access MAF files, which preserve variants found in MC3 or a TCGA validation study. Please review the protected MAF files in the GDC Data Portal if you are unable to find your mutation in the open-access files. * Public MAF files for different variant calling pipelines but the same project may contain different numbers of samples. Samples are omitted from the public MAF files if they have no PASS variants, which can lead to this apparent discrepancy. * BAM files produced by the GDC RNA-Seq Alignment workflow will currently fail validation using the Picard ValidateSamFiles tool. This is caused by STAR2 not recording mate mapping information for unmapped reads, which are retained in our BAM files. Importantly, all affected BAM files are known to behave normally in downstream workflows including expression quantification. @@ -619,7 +3192,7 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_no * Progression_or_recurrence property is not populated -Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_notes_manifest.txt) +Details are provided in [Data Release Manifest](https://api.gdc.cancer.gov/data/bb0096b7-efbe-4335-92d1-22b0a64fc0a4)
@@ -633,7 +3206,7 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_no 1. TARGET ALL P1 and P2 biospecimen and molecular data are now available in the Legacy Archive. Clinical data will be available in a later release. 2. Methylation data from 27k/450k Arrays has been lifted over to hg38 and is now available in the GDC Data Portal 3. Public MAF files are now available for VarScan2, MuSE, and SomaticSniper. MuTect2 MAFs were made available in a previous release. -4. Updated VCFs and MAF files are available for MuTect2 pipeline to compensate for WGA-related false positive indels. See additional information on that change [here](https://gdc.cancer.gov/content/mutect2-insertion-artifacts). A listing of replaced files is provided [here](GDC_Data_v4_mapping_of_replaced_Mutect2_MAF_and_VCF_files.zip). +4. Updated VCFs and MAF files are available for MuTect2 pipeline to compensate for WGA-related false positive indels. See additional information on that change [here](https://gdc.cancer.gov/content/mutect2-insertion-artifacts). A listing of replaced files is provided [here](https://api.gdc.cancer.gov/data/ef4c8578-c8d2-4bcb-86af-901af1a5f0a4). 5. Added submitter_id for Pathology Reports in Legacy Archive ### Bugs Fixed Since Last Release @@ -656,7 +3229,7 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_no * Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg -Details are provided in [Data Release Manifest](Manifests/GDC_Data_v5_release_notes_manifest.txt) +Details are provided in [Data Release Manifest](https://api.gdc.cancer.gov/data/32d23ec5-143f-45c9-91ad-9949daf5538d)
@@ -692,7 +3265,7 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v5_release_no * Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg -Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_notes_manifest.txt) +Details are provided in [Data Release Manifest](https://api.gdc.cancer.gov/data/bb0096b7-efbe-4335-92d1-22b0a64fc0a4)
@@ -723,7 +3296,7 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v3_release_no * SDRF files are not linked to Project or Case in the Legacy Archive * Portion "weight" property is incorrectly described in the Data Dictionary as the weight of the patient in kg, should be described as the weight of the portion in mg -Details are provided in [Data Release Manifest](Manifests/GDC_Data_v2_release_notes_manifest.txt) +Details are provided in [Data Release Manifest](https://api.gdc.cancer.gov/data/b767f710-9631-401e-b24d-aa90f85268fc)
## Initial Data Release (1.0) @@ -763,12 +3336,15 @@ Details are provided in [Data Release Manifest](Manifests/GDC_Data_v2_release_no * TARGET data that failed harmonization or QC, have been newly updated in CGHub, or whose project names are undergoing reorganization: ~76% of WXS aliquots, ~49% of RNA-Seq aliquots, ~57% of miRNA-Seq. * MAF Column #109 "FILTER" entries are separated by both commas and semi-colons. * MAFs are not yet available for query or search in the GDC Data Portal or API. You may download these files using the following manifests, which can be passed directly to the Data Transfer Tool. Links for the open-access TCGA MAFs are provided below for downloading individual files. - * [Open-access MAFs manifest](Manifests/GDC_open_MAFs_manifest.txt) - * [Controlled-access MAFs manifest](Manifests/GDC_controlled_MAFs_manifest.txt) + * [Open-access MAFs manifest](https://api.gdc.cancer.gov/data/d645229f-f5ae-4f93-bd58-1fc7b2271aa5) + * [Controlled-access MAFs manifest](https://api.gdc.cancer.gov/data/34789d4c-aeb6-43f2-88e6-1c44ed8e2d2a) -Details are provided in [Data Release Manifest](Manifests/GDC_Data_v1_release_notes_manifest.txt) +Details are provided in [Data Release Manifest](https://api.gdc.cancer.gov/data/1958147e-371d-41cf-b6bf-3dd1ed4dc237) ### Download Open-access MAF files + +* Please note that these links no longer point to files and will be updated in the future. + TCGA.ACC.mutect.somatic.maf.gz
TCGA.BLCA.mutect.somatic.maf.gz
TCGA.BRCA.mutect.somatic.maf.gz
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+402e743e-8469-4ebc-9277-071730c71444 b47ed9e6-6beb-4bff-807d-ed0634dcbd31.rna_seq.chimeric.gdc_realn.bam 17a5d92625f7936c2102c96bc0131ba2 47581513 BEATAML1.0-COHORT 75685dc7-7f1d-420c-bd9f-b566a5deda7c 28825d09-c94b-4b79-93d0-6d47e665b9f7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric a10000db-80b6-49c1-9e16-6abe7d147bb9 bde26e2baa924a652892586e7d737bf6 47581493 +79e8df71-e338-48cc-9ced-1aedcb27745f 00273c64-36b3-492d-b0c1-482199aaaf34.wxs.MuSE.somatic_annotation.vcf.gz 65530ae05aa40405dcb6f42932c4fa75 252958 BEATAML1.0-COHORT 36c2d37f-c97f-4000-9d90-15a13b5237d6 141a6466-32c1-41d2-9657-92a0e394c351,f778781f-5a3f-4b9b-a043-8f2bf0f178bc Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 3644826e-8002-4cc2-8064-83fefa8d7dbc 54f104bd4f14306cac7cc32c9f7cb8fa 266525 +09f0638a-adc0-4a6d-adee-2bd256ab345f 650bf47b-74f8-44c4-853b-e1ee2803bec1.wxs.SomaticSniper.somatic_annotation.vcf.gz f1edf8de30a81610e8c63eb0bd3f05dd 585173 BEATAML1.0-COHORT 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13b612f6-53c5-48c2-94c4-0057408828e2 74c262b6bc9e5b2e16306cbd91d1d8fb 5227895519 +0c78dbe4-3529-4770-a3b3-40f6b23e70e2 875a01ef-17ed-4ce3-afaa-fe1ade410296.wxs.SomaticSniper.somatic_annotation.vcf.gz e987862a26e9afa2bedb3ce555a29cc9 1625812 BEATAML1.0-COHORT 81b3864a-5869-4487-bfdd-7d20827af7bf 2c6b5af5-2bb9-4e16-9fdd-da66bcce57d0,ac6f8ec2-7bf1-4e18-ab76-0d97241cfd9a Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 02b98c0b-1743-41d5-853f-6bb3ed19ded2 f337d5d5076bd5f054b47946148ac5d7 1722709 +177dced5-c993-4ba1-b45a-09e7c711281e 5a897c44-c24b-481a-8dba-7b3241c2764a.rna_seq.transcriptome.gdc_realn.bam dd9ea969b459bdfc90f5f6488b48f809 11183466362 BEATAML1.0-COHORT d4f36969-4e53-4ee7-8f4a-6aa3f47a6145 f1c4866b-f3d5-4725-8047-6752639a190e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 641ea4fa-3fc7-415e-b897-a61cf9bf30d7 0f822b108a7bba5c08ca322894776f57 12668949879 +350e0cfa-a18e-42f1-b198-c7dede7911de 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Aligned Reads RNA-Seq STAR 2-Pass Transcriptome ea0c7961-9a98-475b-a2b8-c5b242c5399c 920aa810a99b8d7b2ee966c40bcc1157 10784807481 +c2b91f9e-433a-45ae-8b79-751539922657 814c8047-01a1-483f-9595-8adc6e37cf3d.rna_seq.genomic.gdc_realn.bam ef23c118c7f3f36b25fb04403d3cb600 6145060051 BEATAML1.0-COHORT 574ab318-c34d-4468-9aa3-2bd3f5fc7ed6 d3bfb206-f22a-493f-9d1e-b25d42a8463e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 4a2ef3a7-418c-4c81-a155-6f5239d7a842 af998a69116ea9473d134c63553242c5 6145850858 +2caae50e-9c07-4192-925a-b52a5992c8c4 ebb37bba-5e14-4e2e-95af-006b8399ad97.rna_seq.star_splice_junctions.tsv.gz 76de609fe89a38d4dc21d1ef8f0c8bd8 3831760 BEATAML1.0-COHORT c248cdfa-9c00-4495-94ae-c2aa6ded5bad 7a399afc-5832-457b-8461-49870e364108 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 6ea03fff-b6c3-400c-99eb-39767a0e972a 403eaab630771e842cb7070a151edf55 3851639 +75b6a64b-3243-447a-9f8a-62f387a16c8b 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SomaticSniper Annotation 43aa9ec3-df26-477e-ab46-47fac3dffc59 d57338c701cfc45be91ce20b7456f839 2358103 +196c41b3-6538-401b-9fc7-f18b75bfd50e 1d066010-9bde-4b92-85f5-cab27d9ef8ea.rna_seq.star_gene_counts.tsv.gz 1596b13db9078cfed1095aaaad539c36 382081 BEATAML1.0-COHORT cc6fb369-7453-4692-8092-d9cc6bdfa9c5 d8cb96d1-6c31-49b0-8cbe-5bf16b3dbdd5 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 81cd8a50-1a17-425c-91a2-f092d728b77e aeb14d0ff1cc73f836c43dffecc09f70 4198531 +f518515f-ba8b-4ff0-84dd-6e9c8f1ecf6e fc68d7cf-69bf-40e3-96ae-46740b502835.wxs.Pindel.somatic_annotation.vcf.gz f1b6c25e443310466adf5769ef73a86b 18437 BEATAML1.0-COHORT cd88b22d-78e2-4cea-a65b-549bcade99ba 7e230b44-e532-4391-a149-d74681c1298a,fff612f6-2594-49a8-ab43-d4b86e5336fd Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 490e6a40-6329-486c-824c-8c6c906e4cad d3aa23e9bcc1fcaf44c7ef2ea8f625d6 20181 +491815c8-81cb-4ae7-9750-d68b6bd37623 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3003352 +0f8bc503-0049-4e57-b368-0831e8c7ab06 bb2ae6f9-38fe-44f9-ba0e-84cc0b8e09e0.rna_seq.transcriptome.gdc_realn.bam 0aa94ed5c90bfcb9d0b49ab077e1e2a9 9161207128 BEATAML1.0-COHORT 22f48539-643a-45d4-829e-e4f3315a7296 ac987f9e-173b-4b30-8c30-14eb175c531c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome a68eaa82-1de4-4776-bb85-152b09d55be0 a53a02e48c89d17a6fb441cfde20e657 10358324263 +5ed2c471-0fd9-4992-a0bf-a1cab5f7b786 447e06f3-5776-4a0b-a835-f69f6f17ebf8.wxs.SomaticSniper.somatic_annotation.vcf.gz 4bdd51078d64a46d8ba23f7d16294263 3950252 BEATAML1.0-COHORT 67702452-6b17-4477-bd63-b46ae8a682bb 1f85cc8f-dd4f-4f12-ba7a-f8667f1dac30,edc9b7d1-8b59-4048-8b91-5d80058c6547 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 3e539a24-0464-430b-b170-84375eb29dc5 80ec7bcda191644b71e0493f683b51db 4214896 +8bcac9e6-e706-46a3-a793-71a1cc636560 6e4fd697-02e8-4659-b9a9-13a935d8f37c.wxs.MuTect2.somatic_annotation.vcf.gz ab815d3848afef7f3daf8fcc26085011 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Splice Junction Quantification RNA-Seq STAR - Counts eb742e87-1624-4240-9031-8d869a26263e ba81878d1a252e0c325510e624c68e95 2760064 +647339d7-5aef-41f8-be2a-51199f5ee4c7 9f6e5197-dd65-423c-9683-717005a12cd9.rna_seq.star_splice_junctions.tsv.gz d5b910bd11422e9310291f651cdbd5b4 2888391 BEATAML1.0-COHORT b681b92b-2917-4e5a-88a9-1d0094d74644 cf68d2e5-1313-4be8-844c-c78122f1e8a4 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 3db92408-9261-4262-a533-4203216943d8 cc6ffcc5345c415d7dfe6e972e44a917 2907607 +7b94e977-3424-4a98-8cbe-5422c78b5352 931a15e8-20f1-4faf-8624-6279e8640225.wxs.MuSE.somatic_annotation.vcf.gz 97d76954218ea4dc0922c53d12fa9801 233083 BEATAML1.0-COHORT bbdd8b4b-e2af-4cda-97b3-25ec29db6198 6b892bb2-1be5-4bbc-8a36-a35008710f27,fa7ba833-d6ab-4926-a886-c0d9767bcfeb Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation a48ecea0-b19f-4430-8115-bfe366b872af 8069e504eb6e29473c03ee2b5d175243 248722 +31475c93-8234-415d-8902-5ebb7485ccf6 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Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 74ba6428-c349-4c46-b2a3-86f2b2ca8471 13d3a0a19998f2814891b9014dc83e7a 4898203958 +4c9e9dc3-4a73-4aca-8f34-295430bf3c06 5c489b60-ab14-4fbe-83cb-a91a7d6a18ac.rna_seq.star_splice_junctions.tsv.gz 1300d31fcebb21698ded252004ec530d 3171356 BEATAML1.0-COHORT 2d63bb10-5dab-4a0e-85d3-5f181552e6e7 98c2706a-a1f4-4e7a-be46-8c4a564d0fc0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 7af5be4e-7ee5-420a-96b3-abcfed893506 63231aed30154c4f3bd727aac8c66036 3192191 +ddcb74fe-36a5-4df9-96e1-5e968fe0cbca 7b30bd49-f5dd-4a75-a47c-200e88f43f2b.wxs.MuSE.somatic_annotation.vcf.gz 5233a712702c09ff2fb09ab0626637eb 212506 BEATAML1.0-COHORT 93dba667-c35b-492e-ae6a-1a2a6eb7f021 2fd49ee4-92eb-42c0-b247-54af31b291f5,744c3849-21a6-420c-a3dd-0b53eac25746 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation bf84f809-2b94-4dbc-8c2c-938fa56ea8d7 0eb834198e442e15566119cd32a740d9 221786 +2d1bc383-fc9a-48bc-b6e2-46133b741828 e6f191e0-a57a-4b6c-9fab-4f3f8f61ff25.rna_seq.chimeric.gdc_realn.bam 18b83bf31d412ec49798a70f5b08852e 77664624 BEATAML1.0-COHORT fe360c36-cd2a-445a-b4c2-752e7c7de4f6 d13435c2-d72d-44b6-bed1-02695601f141 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ff374c34-70f0-4cd4-8783-ef9d6ceace32 dd5901fdd594501cf6325b1364192b07 77658433 +efc4e586-b660-414b-99a4-b8adc197b63e aac28af3-2a77-4ac4-9959-1fe9ab17f97b.rna_seq.star_gene_counts.tsv.gz 10b64878da8d65dee5844ee1b2910ca1 387868 BEATAML1.0-COHORT 98ea69ff-734c-42c0-8b28-32215168d0ac 088a6350-017d-453e-8727-4512aa2dec02 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 87e1f9f7-5b0f-4bcc-be68-e34bfa550c6d cd936410c76dc472521d15120da6e9a5 4205006 +7f952082-6720-4bea-9035-2b0289cf5689 a5694620-3049-4bf6-b7a6-ec2b4c5811d9.rna_seq.star_gene_counts.tsv.gz 8e538b8a897cc9c5bfa2e935da9dbae6 384570 BEATAML1.0-COHORT f48953aa-661b-4a2b-939c-d56bc0ce032b 10d6f016-0a14-4b38-b593-11c0f08219bb Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts dd434a66-5d54-4004-9e75-b1ef83dd2bc4 36031083485155ee002d80b4fabf3f45 4199728 +3463af80-90e5-4a70-abde-5499cafed31e 8fed7f5d-bef9-4be3-adf6-97352da5a318.rna_seq.star_splice_junctions.tsv.gz 72dbb629cb4005686f0e0aeffb917ae3 3122023 BEATAML1.0-COHORT cdda7773-48b0-4af4-a5af-36ac67a7e7e8 4acb09c0-c94d-4b29-81d6-2ae8932ad2fe Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts ae55500d-307c-4e1f-a9a7-7b983aaf71ff 7611b3c02c4b3db6e4dfa7583dd2b069 3144808 +cf9ee3bb-9fcd-4998-b9ea-3b7b364680bd 97a53247-7024-4bfd-acc6-9c823cc789e6.rna_seq.genomic.gdc_realn.bam ec71f974bbcca85e0e102cf34a05f771 5953346478 BEATAML1.0-COHORT c1b7fe78-2d9c-463e-9964-db3e29453ae1 d4ef5dca-ace7-45ba-9cfa-41c41bae10d7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 7176301e-4904-48e3-a5f1-2f658e141472 77424cdfa53befac24cf46edfc5550f9 5954217056 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RNA-Seq STAR 2-Pass Genome 20e08423-b8d4-4bee-bf5d-23ffbfa0a0fb a610509e70a344e601ab5f8c3a46e171 4803050666 +39994cf8-85ec-42f7-9c3a-d604f1acd4dc fa08b7da-52ed-478e-9ce3-dbf0ae77365b.rna_seq.star_gene_counts.tsv.gz ae6b5a6b44be9d8101e944f8eb0f35e5 394243 BEATAML1.0-COHORT c01c8067-6990-4199-94a7-e0c36bab6dee b95c5e09-6eff-4888-90f7-a891ba805d8b Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts c8bc64f3-5267-4686-87eb-adc3f0242ff1 36a36dfc9d38ad0116edea8d72f94b33 4210049 +28f92263-a403-4f7e-b951-2eaa7e17fc1b 7860922f-7a0f-4057-9e11-7dd957ab0f97.rna_seq.chimeric.gdc_realn.bam 503f2e4f8386f5c58af8f957d5348e49 88667128 BEATAML1.0-COHORT a8e0b40a-1158-4332-978a-3b9a620a4c4d 95d651aa-7bb7-464a-96f1-10b1d96fd97c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 3381eb39-e3af-407f-8615-7c67af94a522 4b38ca9ccf921bfdbb4c422141869377 88642477 +63c9f8d3-4a93-468f-9869-3a6f19eda9aa eff4fff4-817d-4701-9229-620c24c836f7.rna_seq.chimeric.gdc_realn.bam 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MuTect2 Annotation 79937e80-9f76-47e0-8098-4c736f29ff18 adcfef17e12922542515b45201150096 3160091 +9b00dfae-f31f-4d33-93d4-001f1f6db768 79ac4cc6-47ff-4456-8390-4861392d29a3.wxs.MuSE.somatic_annotation.vcf.gz 5c88611f3d7d1cad135a2e9a6612f175 141614 BEATAML1.0-COHORT 058fbf75-e9ba-40f7-9a3f-463af1e90662 fa0a62fe-cef2-4c59-ae60-e33e22ea0821,d3b258d9-3e10-4da1-bb45-4038886298f8 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation b90c0115-f54b-40c4-b924-15f18fac58f7 4a1cf16973dfc4323b4b5f836486c1f2 151108 +2bf797cc-1d2b-401b-b007-68ffb42781cd e6f191e0-a57a-4b6c-9fab-4f3f8f61ff25.rna_seq.star_splice_junctions.tsv.gz 8f7c4769a6d8a64512f2b01ad5512867 2943594 BEATAML1.0-COHORT fe360c36-cd2a-445a-b4c2-752e7c7de4f6 d13435c2-d72d-44b6-bed1-02695601f141 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 612144a3-069f-4e16-83db-a7a376f436a3 142f12106df24ccf9fa0ab0fdfb5b92e 2964671 +9fe4d9bc-577a-4743-a064-fa16c388165c 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af8a7fed-b21b-4321-ba5c-ff9d047b301f a576dacb95326d7634e116e5e3b63f6d 261660 +52589548-2fe7-404b-8fb0-3efd119b6900 fb21b767-7843-4993-a807-d3f139b3dbda.rna_seq.star_splice_junctions.tsv.gz 0de918537428795c16d2b7a172242b1a 3165320 BEATAML1.0-COHORT 064e5f4e-7424-4ea3-aeb7-577acffe8fcf 723466ff-2311-4025-a98f-b382c2ec4aca Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 698175dd-ac0e-48af-8231-13dd816afe7a a9ba6ac5d229371255781d7d79d85bcc 3186191 +23416dc5-ed55-4701-862c-a5e86af7524c ace00fe1-70d6-4257-9882-d68e9210dd36.rna_seq.star_splice_junctions.tsv.gz 61e2440078cf1daf2097707777d0944a 2979312 BEATAML1.0-COHORT b0c6f482-17b0-4ab1-ad1e-b9bbe47d9a94 446bdfaa-6f98-4878-98c9-1ec183841b66 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts d589eefe-4132-4114-9bb2-e76a4f6a8e1b 430a97eccd66a6aa89af6d36ff9c7c8a 3000417 +8c808a59-6a55-411f-8417-6de49cbeeb0f d491f645-3eb8-4f56-9f26-8fb5f13aa06a.rna_seq.genomic.gdc_realn.bam 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+cef8c8e9-7bd6-4598-818b-4e9ffbb70d35 028688dc-e6c3-495e-bf70-76c9ce1c0fc2.rna_seq.transcriptome.gdc_realn.bam 5aca6aaf20d703b9714d0a9777f6fa00 6802159122 BEATAML1.0-COHORT 536a999d-d1b2-4be0-b864-9261e96d33c0 85f00796-3c77-4c07-89f0-8ac74f8d8b97 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 21270521-b5bb-4840-be7b-c49902873105 c04bf7a066d5a43aa71e4b3f62b7a99f 7589333962 +b067c468-d8e7-4f71-8fb8-abf64862cf93 3156b31a-69d1-41be-a9cd-b254de713952.wxs.VarScan2.somatic_annotation.vcf.gz 26de9f3f0ab17e16922bb09e92bc9d99 338963 BEATAML1.0-COHORT 1af331d2-7400-4855-abb2-5ff376b4e48f eb371608-afcf-4451-a339-0f84752c5bbe,74740ced-992b-45c7-b3df-d06f0cccf556 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 47d62936-dee6-43ea-9701-03d44d1352e5 f37f65fee4c9293eac50e3fee6c6dfd7 357965 +791ed034-d1b9-4d04-95fb-8402561f5649 3685428e-cccf-4e2d-974f-efcac60c61d8.wxs.MuSE.somatic_annotation.vcf.gz 1a9ffa28488d52fdb8f68f7f442e3210 202352 BEATAML1.0-COHORT 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28d80baecd296bc3d566b93fcb5ede86 3470136 +14f495e1-299a-4002-b9b1-a48542ca49d2 3f83a288-eaa3-49c4-b6da-e837496f5f99.wxs.MuTect2.somatic_annotation.vcf.gz 095ed6fee02fc638ddf5f8150612befd 3279749 BEATAML1.0-COHORT bbdd8b4b-e2af-4cda-97b3-25ec29db6198 6b892bb2-1be5-4bbc-8a36-a35008710f27,fa7ba833-d6ab-4926-a886-c0d9767bcfeb Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 2173fe2d-dccb-4965-a920-16660d217ac0 0ca1912b795b9f32ae74f4f42ae5aada 3442811 +f86600da-4f51-42b1-bd02-25cc02c0994f 69b17f0f-2e97-4c45-afb6-470aad53b291.rna_seq.star_splice_junctions.tsv.gz 860370a70ad9219b7aaa73da988e14b7 3217988 BEATAML1.0-COHORT 8a83eab2-50ed-4d04-ab62-6fbf3415bcb8 158a4290-efd9-41ce-8568-66bae6fbe9c6 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e676bce7-96c1-46c1-b83a-bc40842f11db 55b8fd255d5a19853f55c892ec189971 3238231 +e02a8136-8d6f-43a5-b7a2-d2ce2829f78f 8e38ba9c-53ba-475b-9512-10a18808cce3.rna_seq.genomic.gdc_realn.bam 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Somatic Mutation WXS MuSE Annotation bfb2dab7-a528-4258-a788-464205d9d8fd 75d83306d7b2b41226f684496430651e 227949 +a660df77-5490-49a0-b29b-301cf0f94e87 2dbaf1eb-f582-429b-acd3-9387672d81b9.wxs.MuSE.somatic_annotation.vcf.gz b3c931d7797841869c0f3f538dccb10c 206028 BEATAML1.0-COHORT 38a7758c-c96b-4d0d-b3e0-29aa77fd7014 ce558dab-c3b8-4c9c-b906-94fce77cc30c,f262d4ea-9001-4ff7-b9f2-3a69af5b5409 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation c5698cdc-f188-4fc2-9cc9-1b497facc251 4b86067372943af289148b07297c26b2 222999 +8786545f-50ec-409a-993d-1416faa14308 ad8eedfd-1660-4975-bfc9-dff236db4b72.wxs.MuTect2.somatic_annotation.vcf.gz 178be39971af660f34b73366423fdf58 3022223 BEATAML1.0-COHORT baf61533-bb00-42e3-805c-3d24e735eeb8 bc089e2b-7b21-4471-97e5-5ba44ffe3265,7d76d200-7a08-4dc0-aa6b-bb021f8f778d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 5e87634c-ab29-45b0-836b-8b52240b75b8 293ba744081881971d9a2be298d1d9fc 3209719 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2-Pass Genome 8aa45553-8688-4460-8177-a91e1094a230 b38c7df8fb54fe29a5f77f5703a7d132 4966390393 +3791a3ed-e8fd-421e-a88f-1b5ece56de3a 3d591312-413f-4122-9165-f04649539287.wxs.VarScan2.somatic_annotation.vcf.gz 33094d7e117bad4277236ca990ff89e4 168029 BEATAML1.0-COHORT 195c7e70-1a6c-448b-9c19-5486f2f3503a 04730d18-8504-4463-89b7-5b017951dc60,53b2a2ca-e083-4b12-9ee0-aa710f85c603 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 439eeb63-5d88-4d7e-99ff-ed3ea8924170 5afa7eb9719fb0feb8f72b2e876f9af7 174209 +a3da5a91-e2a4-43a3-af3c-cf0d749c91e3 45b3c6a7-50e8-495f-9984-c2f94a3961ad.rna_seq.star_gene_counts.tsv.gz 88c60bf147da4204ada70c90d45aaf27 402547 BEATAML1.0-COHORT f0bd0b08-7275-4692-869e-79a8785731d7 60a6b84f-7e10-4c06-9d83-a1f3e4cc7e53 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1039aa8b-3d3c-423c-9e41-a6ec31ebff09 b7b899700737cfd9f04696cf82fba6d8 4212702 +20f5b1ae-1168-4497-a189-3a0531a57ef1 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7fabd55d-7e58-4d1a-ab22-6c2016180c32 09e8a6c0bccf65dbd7ac6f1f91f01d05 4080803124 +dd224301-718a-4ef6-813b-d81394912e67 defc210e-1237-4876-a576-4cb559674556.rna_seq.star_splice_junctions.tsv.gz f14cc1301c824891941a836057177d21 3298170 BEATAML1.0-COHORT d362e3e0-fa95-4543-af06-bfda14c64678 3eb9f68a-3ce5-47c2-bcb7-1db49bdcef41 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e656f8dc-5e42-4879-afce-91d3e97363bf 9c1db1a3b88726f8d96bc118489d2149 3317308 +83f76243-3e2f-454f-b0e0-83b23b9733ef 9f72c48c-ab59-4284-a26d-ef1299165c0a.rna_seq.star_splice_junctions.tsv.gz 5fa2d0653f1b760666f6e43229d01c2d 2658106 BEATAML1.0-COHORT 98c21e0b-1373-4785-8edf-345c55fd370c e3f65fa5-ea32-4804-bbdf-ead88ed7f806 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 63d40319-65a9-434c-94ad-dc6ce083f556 560adf30c3a1436bbe5f241179d9c78c 2678460 +65cec79f-6c0e-4fd1-bd8e-c528b3a8d7dc 4d379843-6334-473e-b0c0-49872490c6f4.rna_seq.star_splice_junctions.tsv.gz 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+914326bc-d49f-4803-850a-9b0d5c7eff2a 2f1b97fb-4b5c-4ac0-874f-55048666465a.wxs.Pindel.somatic_annotation.vcf.gz e6436dd28a848edd3d24daa3b113a602 32749 BEATAML1.0-COHORT 115ae244-7555-466b-98e6-08f347c543c0 75892784-6710-4d9e-8485-ef8283271c27,40fbd21f-2ed9-49be-9bbf-4bcb16dcefec Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 3dfbb1db-bb21-4798-9fc2-4cdbce6bf1da 128b6de845b8996a0b8791754315ab10 36654 +b57e0cf3-78bc-4458-846e-66e4d60d6b85 148b8e29-4cce-414f-a11c-1fe77e5c804e.wxs.VarScan2.somatic_annotation.vcf.gz 2bb89568a7e0b1227c077fe49f675c88 129014 BEATAML1.0-COHORT 71153ee9-9eed-4bf7-ad10-beb4f728ef22 9f5e46f2-e23a-440c-a848-3d09b9cab03f,dce205bd-3b44-4eff-8264-cabe85466edd Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 450f451c-c836-4186-9ff0-62bd853c4255 8ba12448b732868b71f7778ef161090d 135591 +6a3dbc38-0298-467e-9526-3dc1f41ab0ca 1cf5b227-98d8-499f-95c7-3feac0612b42.wxs.MuTect2.somatic_annotation.vcf.gz 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4200206 +65544e8e-524e-45c3-bf5e-50327bdfe3a6 41973cb2-723a-4517-9745-125bb6990c14.rna_seq.transcriptome.gdc_realn.bam e70a2fd9b2cb43b6b0b0637d460a810c 8020577390 BEATAML1.0-COHORT 2d6c24dc-22cd-4ec8-8866-87785ea32434 cfc3aef2-6f8d-4f26-bf6a-b1079ab1a67a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome a6a542da-dbc9-48e5-bec4-f9ef44d8cbd0 ce9c23ec96ff894a613fd82179bb0831 8738559585 +cba0f5b3-1252-491d-ab10-f2ba39a48b7c 8a4751df-8234-4104-9ce4-9df86826683d.wxs.VarScan2.somatic_annotation.vcf.gz 4cc65fc782688c5647a11bdf436c8f68 169107 BEATAML1.0-COHORT 77677638-7bdf-42a4-aa23-0d76da60e0a0 b1bf00f9-b414-4d87-923f-4dcd4af1fbc8,13bc691c-6de8-4ade-89f6-9f998fc947c5 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 122eb44f-82b9-4778-977c-fb166e4fe279 42b7ad712a36a94b6e469509d575b810 176080 +b4bbc178-7500-4dfc-80ef-88e8879103ab 72479e12-1329-4118-b465-d84e1cbab38d.wxs.MuTect2.somatic_annotation.vcf.gz 32f081f76bda1a56a7befd76e30f82a2 3319196 BEATAML1.0-COHORT 8e27e6af-f9c0-41fc-99b9-8af85ce09c28 aaaf7f70-563b-45e5-9c4f-6b1a0fcaddf4,c41c08d3-0a41-4b35-929a-01d1ea2f0788 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 08761139-14e9-4241-8c8c-48fbcd2e3225 893755111aa2722b513277f99c6755d1 3513806 +72cf9b8e-bc5e-4b1b-bdd8-4cfb07d9bcfb 2ac15260-d7ce-4f60-b17a-29c71b3145ed.rna_seq.star_splice_junctions.tsv.gz 8e8a922349cd27fb5696ac723d3864b5 3187128 BEATAML1.0-COHORT 7d9ec6f4-ef88-49e5-8969-4eb6f0d92827 4a5bd958-dfbe-4fdd-b29e-de88c47596af Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 7032ac1d-af6d-48ae-9dfd-b55e3fdb1f99 aecad02d19291e002fcd16625b43b6b3 3206233 +8439e587-6dee-450d-8a14-0d0dbecea8ca 471f5877-d205-4ad5-a214-d45935c92321.rna_seq.star_splice_junctions.tsv.gz 50873f3d45e917ecec84a43897a61c19 3162971 BEATAML1.0-COHORT 0bfcd679-17d9-4723-8308-850c43863d3c 07bd3faf-23c9-474c-8d98-c85892e7bb2c Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 0a4520fe-dbf4-48ca-aeb5-46c4eb0c515c e96d4762d8b3e7833249417e83d9ce77 3183514 +4615df5c-42e6-4eac-b377-6fbaa968c697 fb94f289-089f-4246-982d-1d025bb36267.wxs.MuSE.somatic_annotation.vcf.gz dc276dc0e52216a20b57ab64e809cb45 382378 BEATAML1.0-COHORT 229ff284-ed23-44d9-9553-92e62c97e833 306cfa3d-32c3-4f33-95c0-046d1a4a6cba,641f1dd7-d36d-4021-8c86-73c6f4f87feb Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 1e3f4695-6e31-431d-ae54-52d5eac031f0 1b6afc3d10b97e7e4c47b5b857eb5306 394717 +de62a9db-b2ae-4f1b-8bc5-023be5bca700 fd750a38-fda9-4ac7-afbc-eb4eff2a8630.rna_seq.star_splice_junctions.tsv.gz 000c27e283e3ec92826248d05b8400ed 3026509 BEATAML1.0-COHORT 4ae0449a-2a2c-4d21-b4a6-0ec54a3368c1 31d62d25-3c4c-4b6e-9c17-07cf732cebf3 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 9fb2913d-433e-4e3b-aceb-95ca710ae5fb 5bddcd14cf139060323adc626a20d145 3045282 +73e78284-36e3-4cef-a708-7510e953bb13 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Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 348bf989-fd7d-4a2d-95b6-3e3f9b220e52 625d5809573e283e3082d33319494340 1457991 +3205dd44-22a6-41da-af58-883b8aaa9938 9d176cef-9e5e-4cb2-9e5f-01603b07b49e.rna_seq.star_splice_junctions.tsv.gz c6b60dfe80959b95e75a1306151e0def 3038652 BEATAML1.0-COHORT 126cf4d5-d7f4-4249-940d-707901ad7ea1 c2da5a4d-37f2-4cc3-9694-0ee50ffb0fe6 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts cad68244-6315-4831-ba41-4abc6921b272 96c6f5a539280db7a9695bf5179287dc 3059244 +5594d27e-1ac7-466d-b601-a7755a95e999 e29a22cd-ecc7-4881-9871-63dd76ea3790.rna_seq.star_splice_junctions.tsv.gz bae0f83912146ae953098b12606ab816 3253152 BEATAML1.0-COHORT c2b578db-c239-470e-a4cb-056d499eee63 72a57723-0e05-414f-91e4-cdfb20cd0bb5 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts fba98b2c-7c36-441b-91f8-bad76fcdcd8a 3d411834d9a92baba5abe37a3858f248 3272520 +a3216504-7a53-46a1-be32-b63996cd5b6c 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58b8744f-8ad7-498e-a2ac-924a6b054013,a8a0f2ac-fb33-4381-81f0-8978110ec98e Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 77a4195f-f758-4b9d-858b-168fc7e62d3f 1f39568a3c10af59d407c4cd7440976c 26571 +1ec3a766-e037-47eb-a3d1-f47618952e1e 7249a9cc-9b48-4b34-a363-bed1dea4f9b1.wxs.SomaticSniper.somatic_annotation.vcf.gz dc8011bc8d9658c665c3389b0ab0040e 1099548 BEATAML1.0-COHORT 5ff19e50-b641-40a0-a6dd-1e4042149444 9009b029-6755-4da6-a678-3c1f18903113,d925d5c5-0b85-4c24-81a3-73810005022a Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation eb23e244-dd9f-4d97-b9bf-671ad98afb45 4f2aa7354ad90f6cd4943a79197655b8 1161301 +8531d6e6-dbdf-45a8-818f-481a558e1c7f 30b380bd-e19b-4f60-b406-6b9355c2519a.wxs.MuSE.somatic_annotation.vcf.gz 6692053f6ca954fdfe6f3fc7f156c74e 154608 BEATAML1.0-COHORT f3be4a34-7bbd-4460-b86d-158cc7e2d27a c2e8cf72-0a64-4958-8da5-071f590dc64a,2fe385af-4c80-47b0-b6fd-f8861d8ce08d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation d27a19a3-b9bd-473b-a066-205405a3bb4b c61b427cd1567cdde316a36499adbcd7 163380 +5427c549-c047-4d1f-9b14-9fe4f1ea8017 2d96f341-d122-45d6-a97a-06236ad49fd8.rna_seq.star_splice_junctions.tsv.gz ec8ec624b7c2444e613e33f7e869f36f 3264141 BEATAML1.0-COHORT 443f4714-6e09-4cf7-aec3-80bdd65da229 bf076925-efc3-4332-af7c-511cae120fe0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f7d0b635-8f21-440e-bde6-9e6582768d66 cf46add1b09fdbd44915ed704c30023b 3284650 +5762667d-ac27-405c-a6f7-1ef996eb31ba b5a08c71-1534-478a-beaf-0069e65e765b.rna_seq.genomic.gdc_realn.bam bb5b9cc620e68eddc4e57deb7fd4d438 5425131889 BEATAML1.0-COHORT bc823b7f-aed4-4756-9321-a452fbcbe45c ce8748f8-75cc-4a14-b338-993ee5fe61cc Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 11c58736-976d-4c76-9378-4394f0c7664b 814c1fa66cc00eb24258ad8e9274d920 5425647115 +15a1baea-f2ec-472e-bfa4-278dd356a877 0725a9e1-7fae-4aac-9945-b0f62f60f184.wxs.Pindel.somatic_annotation.vcf.gz b35fa6edaa2aaae482f2cff7a4c0a6ac 45882 BEATAML1.0-COHORT 4ca73767-3f64-49ec-8cd7-d62f8b9e3c0b 618866f2-65ca-4f00-8c91-a5ef7f5f2de1,dc323d87-15b0-4fd2-8b46-3c97ddf8f7e9 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 869a8587-9402-4c6b-a1cc-fb85b83bc93f b02db79900d6de4ced990ed6bae92047 46983 +16f3f0ba-a2fe-4145-9677-ef2a2b976897 5e22dcb2-fbd6-4c0a-b5e4-0171874f12e6.rna_seq.transcriptome.gdc_realn.bam 4429d35c878e9449a0241133a7d1553f 12228596192 BEATAML1.0-COHORT 45f4c1b2-3f02-43f1-8e97-62156570e6c0 e462a1de-aa04-4fbb-9349-91cdc805286d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome ae0e621a-7f38-47c9-a2f3-a7adb173cc98 438220d7582487ff057400b3ea1cd6e8 13591725009 +9ccef62e-9e74-4e48-812a-5e9b0953d881 75ba680d-70d0-4e0e-987d-88e1b8149975.wxs.SomaticSniper.somatic_annotation.vcf.gz a258e9d3f72482ada9b4f4023647307a 1472119 BEATAML1.0-COHORT 8f14bd32-6199-4f8a-8057-7f3cd9e0fe69 684ccfb0-10b0-4e9e-95dd-f3f7f4bc4b97,9c5126ad-f8c4-46a7-96f3-28881b5338f9 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 30c15c80-0145-4d37-b0f2-035d1d8f029a 68a0f0903e79c0300223194779a19962 1554590 +07c3d0de-c22b-4269-8d62-8460be3e21a4 bbc1f69d-b48c-42c9-85f7-e39b2d0193e6.rna_seq.genomic.gdc_realn.bam 5dd1fb2e0162d8c4e0546333e0f29b32 5040961452 BEATAML1.0-COHORT 4e4e7a39-95eb-4250-92a8-60192c83ea6a aab5d60e-5a6d-4892-8c75-46201e074076 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 82d47223-0925-48ea-b7f2-237eef1501eb 10e7a2598ce60107726b3c760c4e1f74 5041955025 +73b4f2de-d120-43c4-a582-adcf67f78f3f 44ab1ef0-6c54-436b-a3d2-8e32535d33db.wxs.MuSE.somatic_annotation.vcf.gz fbc44d0e63445d75e3edc093dc0602fd 243266 BEATAML1.0-COHORT 5b6d03d0-4c5d-4a99-ac25-9bce31f09dbe aa7ac2ae-f646-4055-a605-7a828c8c7925,19f4a743-d209-4e93-ac22-01ce8cbef7a1 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation ffa2c129-f4ee-4cf8-a7b4-55f6b81524d2 2b93c34999bd7c3fbfc4e9c1a5787823 248048 +97670212-583f-4ca8-a51b-f71ca1576681 bfc0913a-f2aa-43cb-99aa-b0e56586385e.rna_seq.star_splice_junctions.tsv.gz 2a1182c72f3b8b6d658422f15e0f160c 2781224 BEATAML1.0-COHORT 81b3864a-5869-4487-bfdd-7d20827af7bf db14297c-7a02-487f-b37b-962a92860018 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 2280da7b-a7a5-44a9-bd95-1b3b1fdd896b 638b103796ac3877398449a72dbdc88f 2797966 +41784a34-6397-41a0-b7f9-ea466f15295a 3d70d642-9f52-44e8-9e63-67a4387b168e.rna_seq.star_gene_counts.tsv.gz dcf984b565b00c45f22bbf013484d542 388100 BEATAML1.0-COHORT af0f9f61-637f-438d-a3ef-afda6d6cc223 5b542f3b-8599-49af-acba-3bfedcac06f9 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 22b2b1d9-adb2-4b1f-94d4-bffaf207aad0 dfb32a4a5de23b8579c656795f4392c0 4204492 +e5da6d0b-56bd-47fa-964e-07373387da12 4bdfdb9c-7722-4a46-b3aa-df71bbf57c9d.wxs.MuTect2.somatic_annotation.vcf.gz 4aae7678b98027a6cc5f11e7d9771071 3220163 BEATAML1.0-COHORT fdc1e6e0-5393-4f31-8178-a6132dae8d63 c23301a9-d8ad-49bb-a877-1903f7ec504b,f4efbbb7-fe6a-445e-9074-77a711e20d7a Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 7837a65b-281a-44fa-b481-458eec17e4ce 2d491e3dd0a71c2182a10515a03b5274 3349936 +47c6d9f8-f8f3-4050-a961-063f77115d4e a51aab4f-17e2-4612-92f5-d9e34c0e22be.rna_seq.star_splice_junctions.tsv.gz 18e7c6d5528135e0180aaa25a3c90c24 2913755 BEATAML1.0-COHORT 2dd9b405-f974-4f86-ba87-cc26e51bcd71 7d56d04d-f8a1-47ae-b48f-cb0b6adeba64 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 607e61b3-b26f-456a-9217-8d080a40f330 b899e2db4cf2e7c22f799fb84af4fc1e 2936215 +b4574939-3616-488c-91c0-51bd3dc5691b a51aab4f-17e2-4612-92f5-d9e34c0e22be.rna_seq.chimeric.gdc_realn.bam 8a99fe5b53527c5f026020ab94f11f18 91840171 BEATAML1.0-COHORT 2dd9b405-f974-4f86-ba87-cc26e51bcd71 7d56d04d-f8a1-47ae-b48f-cb0b6adeba64 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 32c9010a-e332-4409-a4a6-3eb8b6b8aa39 40920cbfe933f70aa1ac59a6e6d3f271 91817054 +915491d3-bf5f-4851-b704-757c73420131 f486abd3-1730-4ec8-b8ed-024061cfd88a.rna_seq.transcriptome.gdc_realn.bam 703e4489dc12b21317ae122d065c1701 8177021009 BEATAML1.0-COHORT bbdd8b4b-e2af-4cda-97b3-25ec29db6198 d6710b51-fb33-413d-9e06-895010574a36 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome f8450088-33d3-42f9-aea2-8fccf6da3b1c 5a0bf405f428772ae3665073e0124a7c 9096285275 +6c3adc65-204b-4e4a-ac1a-bf44b56f0cf3 fde4b7a6-20a0-4c6f-9d81-d2c60100a523.wxs.MuTect2.somatic_annotation.vcf.gz 6335be87959aa559a828077fbfe654c2 3223459 BEATAML1.0-COHORT f95662b9-82f4-4609-b71b-95a6f1914d41 2cd5295a-0ab3-437b-bca3-175ba5d24f8b,d81f9c34-a705-489f-9c1f-4018da5c3378 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 5c310f48-f85f-4a66-821e-c110cca4c8bd 7e108ef61f22a0e60c49ee0c1ac19167 3367739 +5beaf9dd-5486-4ea5-abde-89da7e9f9f3a 45d1b846-f6de-46ca-ae8d-9cc934029013.rna_seq.star_splice_junctions.tsv.gz 282a97520781fc308049d93f21dcbd30 2749734 BEATAML1.0-COHORT 4a546562-5020-4943-bc01-81b5f16ba2cb f88a3528-5d51-4727-aa59-2e4ad21a1c0b Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 11cb593e-1984-44dd-869a-963e19e2a10a 80f03cc2e2c3521ce3644a0f940a9e96 2765249 +3c180258-9041-4481-9c79-75e73d216129 45d1b846-f6de-46ca-ae8d-9cc934029013.rna_seq.transcriptome.gdc_realn.bam 2658fde539dc457c77ab761094329df3 7913791076 BEATAML1.0-COHORT 4a546562-5020-4943-bc01-81b5f16ba2cb f88a3528-5d51-4727-aa59-2e4ad21a1c0b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 3517afa3-f88d-4468-b371-e72d31eb4732 f45186fd74f8491d23cfc0b4a256d819 8757989475 +ed0614ba-1751-4c8a-8b19-324681b227d5 4c50025e-dfc3-47ce-94d6-cb8fb784922d.rna_seq.transcriptome.gdc_realn.bam 03ad9154786f4452f1cefe17624e98ae 7971746498 BEATAML1.0-COHORT 98c21e0b-1373-4785-8edf-345c55fd370c 3dba7f79-2f0d-422d-8739-e8ab49e08fc4 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome d31c19fb-0db6-404a-b2e0-53831064ee00 b31a8a84d5fb00572364663cd8de75c3 8988319259 +51890457-4a4f-4c71-845e-a610a8100f30 cc55d51c-fba4-4803-b833-56e96ee973c2.rna_seq.genomic.gdc_realn.bam c06cfd1a9b6cc09cd79571a97f134359 10024367171 BEATAML1.0-COHORT 8af4b573-af8b-48c5-bc01-5782c24867cd 1e48dcbb-c831-4cec-8bc4-2f1b688f1009 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 1a4cb70e-7be9-46ba-86b4-2e97bb743bce ecbbd0dc54580f5cd5ba1d8e2b5cf7cf 10025959103 +06db1632-2622-466c-ab1d-a6f225b42e7b c96ae1a9-00ed-4484-9f67-4c53f932cce0.rna_seq.star_gene_counts.tsv.gz ec0bdeb7382d8c60d30063e8c8713962 388457 BEATAML1.0-COHORT 422dff38-cde6-41c6-8f3c-26ebd1d0e459 7d477eba-08c0-4269-a2ec-87fff27cf6fe Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts b879ecfa-1731-4cba-a8b6-bb3e4f06623b 3f4b92eafb33d0b44e65dbd548cdc204 4202672 +245a91cd-ba23-48fc-94e6-03d7c0abbbad 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WXS VarScan2 Annotation 993b796e-ff03-4e80-bc13-5ad250bd42f0 06f13cfade8c89982e42b53778426beb 144207 +2bb5aa8b-9dc1-4657-88ac-b58113c08586 5aad1768-ed42-471b-836e-ea1b156aa458.wxs.MuSE.somatic_annotation.vcf.gz d551083dcc1f101bdf13ddfe2010c940 277427 BEATAML1.0-COHORT 97248edb-7c8f-4e28-9ba6-375933147c4e fa9d05eb-8be4-433a-8756-7dc80fdb0bbe,aa2a938e-e687-496b-9def-eff34bdc40ab Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation d4a67ce5-16d4-435c-a97e-2a9b0886a68f 906bb74d4099e5612061f551e029fbd1 284200 +dde30a6b-0dc6-41ba-8edc-c5bacf614285 105ce8ec-a0c7-401b-b650-56e5d79a832d.rna_seq.chimeric.gdc_realn.bam 557ff96bc9a7ddc1cd9f176f94393190 68234746 BEATAML1.0-COHORT 96d78086-22be-4c91-8292-1bfb6051b429 1becd52d-ca3d-4f6e-8278-89a3914a3e91 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric dac555d7-df3e-4fe4-a014-f6906c81fb16 41185393d2dcf8ef62c40e862454646f 68225410 +fb48f120-869d-4fa9-9e20-1b233c1034b3 41e1846a-e6f8-496a-942f-31dc5c86984b.rna_seq.chimeric.gdc_realn.bam 529d954faa07cbce7a82fd6adf70858c 82286775 BEATAML1.0-COHORT 58291cd5-897f-444c-b8f2-a4c886f5dd6f cc9171d7-aac8-4636-8ee5-33ba1a7b3330 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c6f73050-eb77-423c-8f47-9e91035cc8bb 75b0e4429106ff07af390f28c9805c84 82265939 +bd837e22-2e05-4453-8e44-000bb3e32fba 90e79303-22a7-4c03-ad58-a41af7af237e.rna_seq.star_splice_junctions.tsv.gz 196463e6518b53b0e76e152e444dfefa 2729782 BEATAML1.0-COHORT 81f58bba-86e0-4764-8074-e40c20e0fe91 37e5e1f3-331f-4d3f-ab61-bbf18f403a42 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 56db0a6c-75d8-47d3-9aa4-812bb0e87de6 265d000772847fdaca536a36ec5e8dfb 2750903 +f58fc3a7-7672-4c2f-bb06-4d1ef6e0db35 fec36d01-41f7-405e-9749-2d09dd779619.rna_seq.star_gene_counts.tsv.gz ebed705efadfda14b83e2469152f60c3 399148 BEATAML1.0-COHORT 9ad4133f-e4ef-4918-a178-c5fd9aabdbb1 5b2776bd-97d8-4761-885a-a48406b849ad Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 58ecd994-7c26-420e-bdd5-f741d2c1774c 8a9a81e204476200d4ba0d578c1404e8 4214857 +a512ad94-3922-43ed-8843-5ae510201ed1 69511cee-d774-40e2-a5cf-eeb174bfc445.rna_seq.transcriptome.gdc_realn.bam c250f6d3b45d7556b4c74a70166d564d 10376769301 BEATAML1.0-COHORT ca70da7e-cf97-465b-a66a-0cc088c19776 acd120fe-4565-4d31-aa34-6e6f3935768f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 0126157a-0ddc-41ec-b1a3-e5e2a1db813a b2f9692f32d54ae49dc8f006b63cafff 11573564543 +c04faa01-ffca-452e-b692-a806c87a6e5f 00d0c9e3-25e6-4a06-867c-cb398cf17d5a.rna_seq.star_splice_junctions.tsv.gz fe53268ef4e621a9528198fa08a607b7 3457282 BEATAML1.0-COHORT 0bc6b77a-d50e-44a9-abd3-2c69755d4563 52a33e52-60d0-40db-adfa-57a2a8fb65f4 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 1fd308df-5fb5-48c9-bfc4-27fcc7687b27 8aa440626bfdbb03e22228dcca681148 3479754 +51d25e60-b895-4768-afa5-a96a28496bc0 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Somatic Mutation WXS SomaticSniper Annotation bfa0ad7f-da24-4948-aa6b-e27c05d12926 1499666d3f3723047ae57ede7a46e103 3100262 +889e0a78-5133-49e4-abdc-fb2dc14dcd41 0a18d99c-8378-4d87-8e21-d8a0802a2f9d.wxs.Pindel.somatic_annotation.vcf.gz 2eac83250a57f519dd0efaa05ed4964c 51984 BEATAML1.0-COHORT ae11e443-c3dd-4fe6-9363-7a2302e15d66 d1701c95-1fc0-4c33-ac40-006e789fadee,553511e3-5389-4d38-863f-a8ff317e9921 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 4da12889-74e5-44d1-aabf-3a4016c8436c dd2de42440ead8307ac25f40d767e0aa 54638 +264279a0-eb04-4706-9f37-e05b5354e2b6 f6a98c88-8777-4f88-89ca-9ee3823600ce.rna_seq.star_gene_counts.tsv.gz 2f6f12a4924caea77a9ecb7aa7aa4bb4 380167 BEATAML1.0-COHORT 93dba667-c35b-492e-ae6a-1a2a6eb7f021 ef25bcaa-4b33-45da-b56e-edf8d427ed7a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts e48798e2-a60e-452c-9b47-dedb61e2b523 5ac7e770a9ed8320136f70a478c07106 4199104 +eb6e2f88-d90f-49da-ab4e-0cec9b49d0d8 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+900f5a7b-24b2-465b-8513-823a38fe8658 fea7e3be-889d-452b-a2bd-78ec5e12a5ac.wxs.MuSE.somatic_annotation.vcf.gz 8a4ab52072f9bf3f1ae194626f98988f 311330 BEATAML1.0-COHORT 66845c5c-5e3d-4f6d-95fe-d7887cdfbf86 740162ee-7d96-4e68-8226-9439382f607f,f6b9fccc-8da6-4bb4-8d36-89e81d79b670 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 61d9d65a-b000-455e-a80b-eff205da611b 8b6c9ccb9224526651e51e880982460e 328891 +7c0571af-b826-425d-9837-128c590a6750 7aa5e55e-6592-44c4-b78b-d8a63a5e4b68.rna_seq.star_splice_junctions.tsv.gz 15cb691e337cc74a908289c302b63edc 2563555 BEATAML1.0-COHORT b0a04585-07fc-4437-a149-c070ee7ff1a2 e6d9f241-05f5-4806-be4d-ddc74bb85e6e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts c3d3e544-9cc6-4fd3-a185-b8f9a772b59d dc963e039270083d5863303a263a0856 2581392 +9ff76e8c-de05-479c-9880-175def8664eb e0ec2526-7c49-4cdf-ba24-913c219fa15f.wxs.VarScan2.somatic_annotation.vcf.gz 79d2cbb967034694a32cd62df6ba3d08 137203 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Counts a32bcf58-7b20-4a86-89b0-8f2292363a44 51026275d8be410e93479b9b25dcfa14 2794214 +2698e14e-1cf9-4302-89ce-6e6ec7cd0323 ba10b06f-a384-42ee-9600-91b7fa7f15a9.rna_seq.star_gene_counts.tsv.gz 107d5d88a831c5a80f755a11c10f67bd 380268 BEATAML1.0-COHORT 260849cb-3d56-4430-93d0-1f2968ae25f1 62c5477f-89d9-4a8f-b516-4d71c21d74ff Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 67469a95-a401-4e54-b515-4cfa3648b61e 0e66ebefffab1768df0b4678e7aee168 4200421 +30d5dd54-d995-49fb-bed9-f1d3da24caa7 c437993e-71ec-49fa-ada1-8b1fc4d5b640.rna_seq.chimeric.gdc_realn.bam ffebf7345a4efb1bf970dc6428c0d8c1 59576648 BEATAML1.0-COHORT 98c21e0b-1373-4785-8edf-345c55fd370c c70e0d31-d2fe-4411-859e-5701687d0fe4 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 7ec1df4e-ddea-4212-91bf-cc0a6a201afa d1f6ea0b20b6923db38136b5ef4e6b9b 59567047 +8d8ad37d-8c95-4676-b9c1-1f4e31e960a3 84d53cb6-3d89-4172-b8dd-f7e57233e6a5.wxs.MuSE.somatic_annotation.vcf.gz 6888862ce0130e7b8856d49296022090 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946ac9683034e1dbf12a7b8b15b6b2f8 4204458 +f56e09f3-c53d-42d6-a1f3-4ae3a72b3295 a6bcfa39-6498-473d-a10c-8747e74b6649.wxs.SomaticSniper.somatic_annotation.vcf.gz 7bedb75ba237d9cb421ed41833098df4 937298 BEATAML1.0-COHORT b681b92b-2917-4e5a-88a9-1d0094d74644 d2d7033a-0968-4dbd-8ee4-36ca89f16a5b,955ff62a-3b11-49fb-8fcc-e369cdc478d3 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 11ec55b0-156d-4200-ad9e-51c1ea8a0813 1a3d4764cf6adc942d71fad265d64492 995842 +a8e14450-3f9e-4658-951a-cada1418f925 d3382a58-6a11-4c0b-86a4-ce566ed2ef62.rna_seq.genomic.gdc_realn.bam bc893aedb21012e7850654654fa2d995 5839266259 BEATAML1.0-COHORT 84e35c18-d61d-4a16-b9c7-29547474b401 5758f87c-89df-4b22-affa-7bb4614ba74a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 579633f0-be5e-40bc-b4f1-bec12499c724 99266a0852867bcda6ea4f3498d235dc 5840271579 +d1aa1dbc-4aac-424d-a62d-9b83c2b2398e 41973cb2-723a-4517-9745-125bb6990c14.rna_seq.star_gene_counts.tsv.gz 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8b05c90dcff8c9208bf89be9c5ef10f1 1513525 +f9b9cbe7-d3bf-4a08-8f91-280d7550e566 501c50b9-f511-4a3d-a118-d1b4ff1221b5.rna_seq.star_splice_junctions.tsv.gz dc72f16ccb5f16f515431de595a3b151 3351829 BEATAML1.0-COHORT 841bb338-9529-4f75-86ae-89bf04da813c 19e10cb9-bc9c-440b-ada5-60601f0c00a1 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 98b2c64d-02bb-492a-8b91-693c9431a127 b05a5ea64e8eb1bd8ed202894b8ade1f 3374591 +8009a484-2744-4040-b8e5-bf8304ecc7d0 73c54017-a8a9-419d-88be-7cb0f8bc89e3.wxs.MuTect2.somatic_annotation.vcf.gz 24a5ff4a435ca2de3fb21deff6b82ae8 2935159 BEATAML1.0-COHORT bfb16010-1769-4b4b-9ca4-0241892f4401 cd9cac9e-4a6d-4ba9-8a0f-003a1866858d,400bcbc5-03e8-4d3a-bc66-caf02702cfea Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation f8662792-ea18-4344-a4fc-74d0e8b90ffc d2e88930edf6855280ec25190c096054 3085109 +a9f91323-43b0-48ce-9d27-5d8f1330ec34 d870daf4-eade-4925-8a5c-1cfec2822375.rna_seq.star_splice_junctions.tsv.gz 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Somatic Mutation WXS Pindel Annotation 965a2f10-f3b7-42c1-9745-ff58728a833c 21c085f260f17027914b4d66e896ff57 19346 +5e62bcd8-586f-4bb5-bc0b-6ba511f7b66d 944ccae3-102b-4671-af60-0d73035df5eb.rna_seq.star_splice_junctions.tsv.gz 5ebb0d273f9ff0aa773950e86e86bd14 3348262 BEATAML1.0-COHORT 1ef8342d-d5dd-4554-98b4-16a80344e171 cd28dbc6-6ff5-4f82-a2e7-2a3eca8e955d Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 15c1c66e-5349-47b3-be48-b669864727f4 24302564f0d83492a70253236e363447 3370917 +a888bc65-a43f-40fa-9001-8a6ad5aa99ca f11cb1b5-03b0-45f7-b4f9-155d7b103ba1.rna_seq.star_splice_junctions.tsv.gz 46ed4c709067bfa692278d6711d534dc 2826530 BEATAML1.0-COHORT c22d2cd3-448b-46a6-87a7-11f58e735da3 38b68669-bda0-4110-932b-764422ce65f1 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 2738edb9-8f32-4989-a37a-74125acefd71 7e2a8435ce82a97faa2ec5b2f69ef41e 2843252 +57486ab5-323d-4e65-bbcc-22b3dd955fc3 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Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 49c1180c-0fdb-4ac0-aed2-39bd6fa8e352 388e5f6561530b47acc86359dcb49a2f 4202538 +6f6866bd-3402-4bac-8b76-afb858c93bdf be4195ba-4e0c-461f-b649-c79cdd5ef125.wxs.VarScan2.somatic_annotation.vcf.gz 65eb6e47c17a4729266486848236aaf3 548414 BEATAML1.0-COHORT 6463eaea-0df6-48ff-a8e6-5c4d9446361d 4fdd2601-77e1-4448-8340-4b125f93f3ab,916e7871-4d77-40e9-921f-b555a5f4e4d9 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation d06e0fd2-3241-4db8-96d5-468efa8de5d1 0f700c2a8b7c785efa33ab69d50025f8 582476 +dc8ef538-039b-4fa8-8fa4-9e0f819c3df8 5bf1e37f-7ae2-4e9b-bdd6-b968510b0e2c.wxs.MuTect2.somatic_annotation.vcf.gz 54b9de9a067acd19500aa38d861b14bc 3389864 BEATAML1.0-COHORT fe176f25-0d90-469a-bc40-ce9b3a1e178e 2d234a2a-8c0f-45cf-977e-adf66fae04b5,b0713525-df8f-4f1b-977d-894380baf9cd Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 64614a63-9e3f-4eda-9914-de569e332ca3 7688b170041a23dd6127fab5255e90dc 3544509 +a81dec4d-51fe-42f8-b8fb-1f9dc69cce63 11b9c8d7-7f25-4998-a27b-95b29ccf7e6b.wxs.MuTect2.somatic_annotation.vcf.gz 59992ef50d454c5e6eda8fd9258a2414 3466969 BEATAML1.0-COHORT 9ef4c32f-be55-47f9-a49e-ba18c3d3bade 8bcd361e-76fa-4b79-817f-d38192faacf5,5b940682-56fc-4975-8764-5e948e75d687 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 18e3fb9a-483f-4ac5-b84d-535f58a0f6f2 49df8d37411ff7cac578f082d5d8ae32 3643578 +d5aff7bc-bf44-4c6a-bfe6-3e253394a937 33da3076-2b5a-4b33-a8f8-aa80c647e6ab.wxs.Pindel.somatic_annotation.vcf.gz cfae0811befdf4e3b24e4db48e6d30be 19951 BEATAML1.0-COHORT dbf8b74b-75a5-4963-9217-a4394fcc6278 d3fe10af-9c49-4950-bc36-d38fee89a48d,dbfeab35-a7e4-4720-9de9-29fe6c202bfc Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 68b06f96-1548-441c-8025-528039e80d97 f616e5f566c5d4bf5d837e2a55aadd1d 19776 +57b8110e-b679-4de4-8733-34dd6ca0d062 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Annotated Somatic Mutation WXS MuTect2 Annotation 1371170d-daf5-428b-8e91-b247cc4e127d bf511f4bd1f9923c638d0dcf0a53ee4d 2340606 +72378aec-6b6b-4162-acb0-e3415a93701b 5f812b01-d583-4da7-9caf-10e18504b3b7.wxs.MuTect2.somatic_annotation.vcf.gz 5509029c883b91bd2f54a4061cac8f4a 4506651 BEATAML1.0-COHORT 4ce5db07-8519-4826-baa4-d9c70695cf98 95708f4a-49f0-4ba5-b9d4-578b73873d71,969d8ec1-ddcd-421b-96ac-ddc0d9a871cc Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 75a9e18c-f1d0-4af2-8185-ce565fa72add 64ff77107dee7cf49b4b6d5d09eb7e1c 4649503 +4ef3f256-ff72-4687-b8e8-e777c5440ec0 5a897c44-c24b-481a-8dba-7b3241c2764a.rna_seq.star_splice_junctions.tsv.gz 31700fbe4225eaf7fdef437639eb97da 3329644 BEATAML1.0-COHORT d4f36969-4e53-4ee7-8f4a-6aa3f47a6145 f1c4866b-f3d5-4725-8047-6752639a190e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 614f7bd8-add5-4bbd-880c-f9cbe370cdb7 1b9fa8679fb9749a4f26f662911d6251 3350935 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28825d09-c94b-4b79-93d0-6d47e665b9f7 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 171d52f5-7b74-43a9-8c61-69bed947114f 7f186018bb18290ecb6d71e257fcc1ee 4199506 +299f8278-e234-4f43-87ad-35b1fee1595a 3cdca177-7f4d-4c13-aed4-ef25251e46a1.rna_seq.star_splice_junctions.tsv.gz 53b99195e460e8de4ccf986bd94c1409 2560489 BEATAML1.0-COHORT 13fc70d1-3574-4651-9d15-e4bcc4bb6382 1bec6aa6-85e2-4da6-be1a-8b3a5361d893 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 237b157d-f969-4c8b-a2c3-ad360ad7ae81 9a06ccc3f180bd585c68f35651b270c6 2579095 +356d518d-184b-4e50-a88f-279f8812c8bf 990debad-b99a-40ae-bfd9-d87e7342ca97.rna_seq.genomic.gdc_realn.bam 2aae648bd855afead6d38d072de945b3 8067019596 BEATAML1.0-COHORT 281209cd-a142-462c-90b2-03bf75910496 c893be24-ea71-4815-80cf-7c7be596657a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 9bbd5ea7-1025-47fc-acb9-3f71faed7c83 7fba11aac492dac5a6e4e44041d3338c 8068732688 +02d192e1-844c-4b40-ad11-8d7ddc462542 a1aedc11-062b-4161-8c79-d02d3a5d59bc.wxs.VarScan2.somatic_annotation.vcf.gz 98c5f57eb076921e3f3ea3f7052aab04 102110 BEATAML1.0-COHORT fc50a10a-405d-423d-bda9-4552f7f92447 53a34aa8-02ec-4a03-a0d1-6959eb085671,fedf6184-43cc-45b6-b4b4-510c33bd7f89 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 369bbe57-d9ab-49eb-b36f-d2a4ef88f67a 9e856e0f500513637ad5438406956834 115014 +5d5607cc-d337-4d67-8035-4bce12f7a04d 378a91f0-3c53-47d5-8f9d-b0ec053714f9.rna_seq.star_splice_junctions.tsv.gz efb56a8b6a6626013bcc0cf084283a3e 2997526 BEATAML1.0-COHORT ea7bebc2-3477-408b-bed5-a19824bc1cc9 72f17323-cd6b-4400-ba06-8f03d180329e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts de47581d-eee0-4d05-830a-1d5954cbf40d 136b8e9d6efe718fc6b2750e88ee7889 3016590 +67a992cc-40a4-4da7-8f5e-6d260ae8991b b29678fb-5ed3-42fb-987c-2fded52a104f.rna_seq.chimeric.gdc_realn.bam a44809cc2061788f607cb71486366dc7 70924940 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10746 CGCI-BLGSP ee385ea4-54db-4033-b46a-8c397ed4aea9 3711aeb1-47b6-4d82-a8ee-4d7d27b79b91,f9e0138f-0b84-4e4e-9042-48fd5427bd75 Somatic Structural Variation Structural Rearrangement WGS BRASS eb78280d-9519-4ec2-908c-361d45972618 639e64ee1aa57fac39eb410057b99be2 37938 +525aa005-06d9-45dd-9440-f31548c8760f e8468b4c-c749-4bcc-a09a-01ea5453e510.arriba.rna_fusion.bedpe 4a91265515d020b7104c4330ec795d58 2114 CGCI-BLGSP 7e0e68c6-4055-485c-8d34-651e803af78c 664580da-73ba-4af9-abc2-4f406999a1dd Structural Variation Transcript Fusion RNA-Seq Arriba 42ceb448-699f-4bbb-910b-018518d8ec0f 0dd6b6ad97b67f5aa04c00355a5a90a4 2157 +a374b5d4-b45e-41a6-a715-ac4e623ca558 c436a49c-0303-468a-8e5c-c4ccf21eb08f.wgs.BRASS.raw_structural_variation.bedpe.gz d3b6d02a11b83f3e364b5c3fe6d1d54f 13859 CGCI-BLGSP 56105a23-4ced-4511-aa90-b956db97b881 be7b49d3-da24-4136-babf-c51d19e31434,971b1da9-28ad-480e-a550-73e1774a231b Somatic Structural Variation Structural Rearrangement WGS BRASS 2b00378f-c9b9-4dfd-92c8-004c807bb3ca 88b02e2622ad67dc36c81e11b3afa8fa 47164 +1ba76b9b-457b-4321-ac9f-827ce2839a49 684a3049-7db9-4b9c-b318-14013f59c222.rna_seq.star_gene_counts.tsv.gz 534faaf9c24e9e880c43b974df778cc2 404172 CGCI-BLGSP 0196393b-aa14-432c-bfcc-1f858c14cd4f 6ec4d872-e00b-47a5-9cd7-b095e09f8e4e Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 61c962c9-25ce-4f42-a423-a265aeffee8e 75f0d003bf6e2616dacc20b9752cf361 4225767 +332c4f48-7a19-458c-beed-346626954b4c 69ec8cfb-efdb-45ce-be13-12796def6b7f.star_fusion.rna_fusion.bedpe 893d0466ed190e6db755cb71217d9f4f 2401 CGCI-BLGSP 0024c94c-88ff-49d9-8dc4-bf77f832d85e 174dacb5-1f2b-4bf7-9ca9-9032a7cdb4ef Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 4eabb8c7-a847-4cee-b9cf-e78021899c83 58b73065dd8d6b4d6e509af5b2e68956 1979 +edee20ab-a5bd-4409-8c38-0281bd3d4b9d e2c2f95c-3f1d-4fd6-8faa-9f9d73054eff.rna_seq.star_splice_junctions.tsv.gz 3b529243d45d61f54b1cf06197857689 3098888 CGCI-BLGSP ce4274a3-7c59-4392-aa8c-14f4d2c134fd dabc4596-656f-4132-a65f-d9bdb0ce432e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 7b2f3f3d-0751-4b99-b393-57cbc26ad6ba cac40f8b3b36ed0bd1764d52f4196d9a 3183316 +7099a373-dbc3-4720-a1d6-4baa33ef23d9 75c618c4-1d48-45d8-b932-39f69e19cb85.rna_seq.star_gene_counts.tsv.gz f6e99300e85a049911a4342aa55b597f 410890 CGCI-BLGSP 3703e3e9-1f3a-445e-9538-d924014c822d 2e9fa249-9648-4b81-9894-1caa574d6041 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts fc205f7b-b2fd-469c-a85d-d5aea94235a3 18c8fb8d5109423d8cd4b4bd0edc329c 4232130 +c81cb777-edb6-4ba8-86f5-db4b9e575818 6dc7b4b9-8209-47ee-8b94-48815ab7e5b2.rna_seq.genomic.gdc_realn.bam 1a61800d8d3b3094415733167a88df68 12771893801 CGCI-BLGSP 32ca8921-9f22-4854-a451-b98f10513f20 c65baac8-2a69-4654-8e62-6d1f113ffcdd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 68919957-222a-432f-a55b-7a0f975d29cd c42ba3fc73f547e84e7a9e5e9f72a4e5 14036375243 +b51954b3-1217-4551-a304-70f375922150 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35e80027-b59d-4cf6-92a1-162f2f79ce82 Structural Variation Transcript Fusion RNA-Seq Arriba 87f5152a-9879-4851-920b-9f22239244ce fb2ce17f8317f8d57c61fbe0c50df474 2438 +99b2ab3e-c71d-4d79-b6a0-4229923f7bc6 5656a116-2e23-436c-8341-3eae83035998.rna_seq.star_splice_junctions.tsv.gz d583c81ce2d62451d59a9cc39d2ef591 3061033 CGCI-BLGSP 0f4cddb3-c60e-4d95-b90a-3e26756a7bfc 35e80027-b59d-4cf6-92a1-162f2f79ce82 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e0913ae1-2ba3-4d7e-aae8-584db713e70a 3ce13250738aac82042540a670f87c37 3148285 +bd6b6532-cb23-4c44-8198-603b1124286b ab595c6b-b79e-4f98-ad60-f4a97e1448fc.rna_seq.star_splice_junctions.tsv.gz 0bd1b2ac608f351ad87847ff61f35b3e 2886844 CGCI-BLGSP 60acb146-43b3-44a3-9791-79284dae285e 2defb97f-3d9d-4624-8447-5d6b9e92e7df Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5ac718e2-bb32-42c6-82e5-8c17816a9847 9fab0398ec32a49c20ccd405df62a72f 2953791 +d94037aa-165f-4f89-8c2c-e997a097e154 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Variation Gene Level Copy Number WGS AscatNGS 9006ebac-253f-4cbc-93f8-1e55a37bdc4c bd7ba6c15e71db8029c2a7895974f3e0 3442760 +ec0f578b-a9e3-4161-ab76-f5433136fcc7 56c2f382-5952-4426-bdd6-79b0980b05c4.rna_seq.genomic.gdc_realn.bam bc1f54146947f66a2cabd453eecff8c3 10147320448 CGCI-BLGSP 8ef78bfd-48cd-433b-a3ff-b8c4e755406e 92fc379f-38c8-4ad6-ba50-9de64d555ba8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 7c247018-dde3-488e-b2a1-68ff5f5c60c6 863de220873691ab4224f6f110870a34 10873536582 +14dec4ad-7e27-4f29-ae6a-87cd35e41588 684a3049-7db9-4b9c-b318-14013f59c222.rna_seq.transcriptome.gdc_realn.bam b71ed111e5d961ee57e3ad2614ef045c 12025142904 CGCI-BLGSP 0196393b-aa14-432c-bfcc-1f858c14cd4f 6ec4d872-e00b-47a5-9cd7-b095e09f8e4e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 0f16924e-321a-4d0d-b8b1-cf795e071da9 dd68f6b105122bc506311f00a8155a15 14470014457 +72d3ab72-af86-4455-85c6-6dbec20932e7 db252b7a-4595-4947-b9ce-d8ddb719550c.rna_seq.star_splice_junctions.tsv.gz 7d8074e70a4810143016419b77314bbe 2893195 CGCI-BLGSP 0ee808be-13bc-4d15-a519-e2b7e960e809 1529cc13-192c-4969-bb1d-c695f166fd2f Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts c2adf6cf-41ed-44b3-9d75-926a2ef946a8 8f07d26b614b76b9de969e1497b57378 2954750 +94f929cd-3d28-4c82-be5a-7695e5fdef20 5ca3f400-4ac4-45d7-9049-4281f2a69113.rna_seq.chimeric.gdc_realn.bam 1851d19c1517c1b54e8a655b0a168dd3 159515973 CGCI-BLGSP bd25db19-92dd-4d8e-8b07-4dba8095cfcb fffaf700-0acd-49ee-95cf-5b295772242d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric bcc5214a-3b58-4c07-9a6c-c578a5b686b0 81358901cf586fa7274c8c3ec62ce47e 169116549 +dbe34657-21d0-4b67-b1fa-e68d141700b7 9c399209-a9a2-41de-887d-ea30949fd78d.rna_seq.chimeric.gdc_realn.bam 2e997c2f16cc00438f92c754db82ebee 147509943 CGCI-BLGSP fcd39a3f-169a-463f-8153-17ebc1b218a8 4db256e1-290a-4c7a-8852-c4f2658a2869 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 675eaf37-ce0b-49d6-97e9-a326e0e371f2 c33bc54f6d35bd77a13fef075e1a760e 158718675 +a83619e9-2e53-40c5-b041-d9e60cce7974 7119b68c-6a19-4e4f-be6d-f8f685c19d21.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP d7619ad6-3a8d-40c7-9ed9-e746cfe7999c 66428f29-c9df-4236-96b9-d50b89409ef4 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 0d0e551a-e17f-4e3e-8616-ae87530a1784 6e5690795ff424264402ab9d2661b62b 229 +8330ca74-2609-4e05-84d4-933a1c08d163 c28e898d-d866-4b94-aadc-1c5a791a95a5.rna_seq.chimeric.gdc_realn.bam b9ac686a12f7a89fd76965bda01538c5 78193338 CGCI-BLGSP 213e9f9d-7340-460c-93a3-edd559b42009 e587bb35-4d34-4a5c-b11b-b1d6992b1482 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 413a7703-bb5b-49fd-941c-30679855717a 0dc8a9b30c910df3a05827a2f0ee814e 81701102 +a1905d10-934f-4e4c-b859-fe699bd563a3 d0cf0dbb-7310-459c-aa1a-b1193f5b741c.wgs.BRASS.raw_structural_variation.bedpe.gz 9ff72cd47f49c817cbc01042c1df9009 5489 CGCI-BLGSP d691aab7-cdcd-4c0a-8294-91e29f97c00f 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Reads RNA-Seq STAR 2-Pass Chimeric b4449aa8-a6e4-4765-aa5f-8d2ba2600d79 4c324a240f58df25ab9df484178ffb4a 220975899 +a9daf071-e0d4-43b5-af86-afac1ec460c3 d0825601-6c65-4dbb-86fe-49f0193999fa.wgs.ASCAT.gene_level.copy_number_variation.tsv 5c8ea6a8a6d2aea5eafb348f03e6b2c6 3481180 CGCI-BLGSP 853704eb-f49e-4509-82dc-47a85c7335f2 95d2e1ce-0333-44e7-bcbe-8534358835a7,cb85529d-59a4-40bb-8c6c-1661c510e18b Copy Number Variation Gene Level Copy Number WGS AscatNGS c9575b4b-d634-4540-94ce-929a2e2af0da 375ada04aa7c4b83fd6f150367c7e877 3441260 +e1aeb38a-7e88-47ec-8be0-2635fabeb189 954e228a-1b4e-4abd-966f-9b36c6b5859b.wgs.BRASS.raw_structural_variation.bedpe.gz 9d65e5dcd9a89b9b7176551f74f5b5f9 5753 CGCI-BLGSP 06c07e2d-a04d-4099-a29f-948e40558dd1 296ad0f9-da09-410f-97bf-92ac7c180335,66e279a0-016d-4b61-b051-9d3a385d4791 Somatic Structural Variation Structural Rearrangement WGS BRASS 8a704813-a155-45a9-bab8-3cc9fa3a60f0 2c7b59248b1ffdbd0b174384a683787c 19994 +9a445b75-4d0b-4758-876d-89e4b6ccf69e 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Reads RNA-Seq STAR 2-Pass Chimeric b170653f-0206-4890-94d1-a1d310bad0c5 97fdc56239392d1f0843c7b2d42804df 153545835 +c8747229-c766-45f8-badc-33ce749cc1d5 29f449c8-ad7f-4376-a683-1ad75fa31709.rna_seq.chimeric.gdc_realn.bam bf9f2bc3fae1750b1e31a66286fdfcaf 248244930 CGCI-BLGSP c96f21de-3dd6-47ed-a796-6270c1817dd7 353174d3-4bd6-4e08-8234-013da78fc871 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 380dc2c6-253b-4882-b0c6-56d307449476 490ee35f1967a4f2af6f265e8a0f08af 255692456 +fd3742f9-723d-46f6-b49a-08e39aefa0c9 5656a116-2e23-436c-8341-3eae83035998.rna_seq.chimeric.gdc_realn.bam 534cfd7ad70748b24a19364e8d3abbc0 108570019 CGCI-BLGSP 0f4cddb3-c60e-4d95-b90a-3e26756a7bfc 35e80027-b59d-4cf6-92a1-162f2f79ce82 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric dbb3c268-0c1a-4cbd-9242-613828533cec 7728012f7fff331837e008389e7208fe 114792211 +ef6383ba-bd10-42ad-bfd8-031f87bc146a a6321322-5625-4136-b9c6-4a47faaafbec.rna_seq.star_splice_junctions.tsv.gz 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b0c269a6-d633-4a09-acfc-38f7518122b3 47c89ea6ec27b2a23a75b4fc08f88444 4648 +86e451e2-6aff-459d-92f0-ec9ce3ac12c1 3e45c90e-3e32-4d62-ba4a-a23fb166ebdc.wgs.BRASS.raw_structural_variation.bedpe.gz d19d21d97b730ea909e989ada2200019 8673 CGCI-BLGSP 48823727-d7d5-4efa-b374-17e3cfffad91 92c574dc-47eb-4cc6-b71d-8d6d13be4c32,c91ceab1-43d4-4fbb-b311-bb5b714c22aa Somatic Structural Variation Structural Rearrangement WGS BRASS 843445c9-2116-4d32-9613-da7ece5d2495 d75b7d0b007190a0cd4ed656421a28ca 29810 +915e70f2-c52b-4fe0-b89f-a9eaba67396f f940cfa8-4cea-41b1-942e-ab3b462cc370.rna_seq.star_splice_junctions.tsv.gz d77fec906bb716c6c84bf7e47f92660f 3170005 CGCI-BLGSP c2010e3f-26f4-408f-95f2-9c06a43bee88 662c9e01-2a4f-4431-83b1-0dfb3c21b335 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts c61cefc3-25fa-4266-8d5f-8fb65990fb78 4f52df3849ff1854c3e94b37274940cc 3247146 +5b2cf480-de1d-4c3c-a43d-3c3a37001a16 622cef07-0e4c-4707-94fe-0e6d087510ac.star_fusion.rna_fusion.bedpe 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+e7322848-0fa4-4a24-8885-a3f241e5eb8d 5cc5c4a6-266f-49d0-a192-9053e6fb9d6a.rna_seq.star_gene_counts.tsv.gz 716aa8039b8abf5f5758dc03f9627525 396172 CGCI-BLGSP b22261d6-12e3-464d-99cb-da3ae8ba6ba6 9d34db0e-55a8-47b6-8de6-2522c926a463 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts f926881e-a2e8-493a-b37f-21bc2c8c59d4 29dc6d30d99e4d6dd93f71d78e4a99f7 4217406 +536b0f32-a5ee-424d-8a0f-980421a71e4f caf047d8-ea14-4887-8432-11210392e479.arriba.rna_fusion.bedpe 0eb1b4f931d122ce96880b67700dcf29 6330 CGCI-BLGSP 92194f18-046a-4222-9409-679b8872e6bf 4be4fb19-b505-4de7-b26b-a4fc582b3b8a Structural Variation Transcript Fusion RNA-Seq Arriba 7d6d6098-c0e1-4e69-b1da-f5b8e52ee9db 0a0b37a70e8bdf21cdfbd7e6b386e4a3 5787 +8b527126-c516-4cb4-9ae2-6d698966f619 adefcf80-c82b-4853-a26a-858212f12984.rna_seq.chimeric.gdc_realn.bam 1a8d52fe96f241adad2c1f5137577a2b 165009939 CGCI-BLGSP 359381c1-34bb-4b8a-ba43-f06bce194341 e52905dc-0faf-4828-a893-945d32d46805 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 14b43aca-401c-4110-b6da-70d14cc12a3a 62a2d4bc130ba6f6db0dae8e985cd506 169772851 +c06b77e9-a9ba-401a-a3ff-c8efbb2ffe39 649824de-2c58-49ed-97d0-f75da2378cf7.rna_seq.star_gene_counts.tsv.gz 4375d03dbfdd61383fbdf523a98d9764 410239 CGCI-BLGSP d0f47e8d-df1e-48e6-a127-6ffdcf7be450 f32def78-5bd9-4514-b517-3a06086ffc7c Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 6e9e94be-4c08-4eac-9692-2711d87c74f7 e670636366be86d883b47a1abbf15496 4229390 +64e69328-5a80-4c4b-aaf1-ff3cad1ff2a7 39bdbc5f-295e-42ef-924e-3c493c6e71be.rna_seq.star_gene_counts.tsv.gz a6370fe095558d9ad01341a9728d663e 393532 CGCI-BLGSP 98540fd8-1bb7-413c-b2d8-857e6e25309f 15010d6f-c931-4fe2-be6c-e11b632f8f93 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts f083d5f4-0465-4720-aff1-19df55456f01 954873e8e3b625b121d316738882cb1d 4215128 +233d2c72-8d4b-4b5c-a50b-cf21af85ea99 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Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric be700a72-4fae-4a87-86d2-26ec0a2ab2d4 86929a95abd070fb8d897911f1e8355b 122721791 +4f5a1780-0199-472b-91b6-e7e6a8d4068a 45876bca-f8b6-4be0-8232-1ba7f5afa6ed.rna_seq.transcriptome.gdc_realn.bam 197ca6a9db886b898efa9f36f7dd2181 12358368944 CGCI-BLGSP 257f421f-d0c9-4510-b7dc-7e98925041a9 aa07f36d-66d1-4a8f-8214-c414179151a7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 28fdd311-831a-4c77-b3d6-0887336f8697 b1f0a25f1c3c568c5d50aff931a4e694 15064100557 +a5ea5c74-7632-453c-b3eb-b0482fc2cd62 352716fd-204d-4c01-bbf1-013a667ad12a.rna_seq.transcriptome.gdc_realn.bam c6ac831b6005f9a5a50c8bf958565814 10343914033 CGCI-BLGSP 39f9996d-b217-4222-98ea-47c210d49e93 0c672ada-5bf8-4549-82f9-c9b8cb747aba Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome f18200a3-1d9a-4c89-b405-ac7a26d9919a 5977c9020086a5d29b7138874896fbbf 12118776115 +1662cb27-9d5f-46ff-8a1f-5ce596b057f2 a07ebe99-d21c-4b2f-9f12-11ddcb56701e.rna_seq.star_splice_junctions.tsv.gz 5a827cfe10ebaea44d4a762c30ba284e 2462658 CGCI-BLGSP e90aedbb-8398-41e3-9bfb-df17f91c1eb8 258fb876-8fa2-4c9d-b8a0-b2ad7ac27962 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 28f6ff89-4c85-4e26-bf8d-3ab8500186a0 90702c26a035a78e2be6d0ad71706e4a 2504603 +3c08ca5a-5158-468b-84e9-70fdc29daf4f f2d06098-9816-46f8-ba03-eefec5697cde.star_fusion.rna_fusion.bedpe 9ecef57183cc288e766a5149e5df4084 1063 CGCI-BLGSP bcb4326c-3c7f-48e8-837a-b43bb2535a0e 784a65a6-e398-4c51-9744-c475933bf478 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion eafcf954-782f-43ac-ac49-106a3170b0a7 6e5690795ff424264402ab9d2661b62b 229 +87b59233-7a3f-41ba-b772-47a5d46e75bf c436a49c-0303-468a-8e5c-c4ccf21eb08f.wgs.ASCAT.gene_level.copy_number_variation.tsv ce8c9a6ffbf08c13772c538e50897b80 3481129 CGCI-BLGSP 56105a23-4ced-4511-aa90-b956db97b881 be7b49d3-da24-4136-babf-c51d19e31434,971b1da9-28ad-480e-a550-73e1774a231b Copy Number Variation Gene Level Copy Number WGS AscatNGS 4e24b649-773e-4631-844f-e11dcdb85fac 3f57c257e95dc3b4739d7dd535d436ae 3441218 +f67120b2-9e31-493f-995e-43bdafa9bb5b 9a0ac5b0-6744-474f-947b-77c666ed3d73.rna_seq.star_gene_counts.tsv.gz d37516fb19096dd8f8923257959d7a65 407162 CGCI-BLGSP ceeec59b-7f6a-4769-b75b-41405c41e177 8967be7c-33f0-4127-96af-4ed4cd98303e Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7f616ba1-6ebc-47ca-9c21-16b31590f7f4 43ef2ee11c42b5273de0bdb374c169c2 4226871 +301fc7db-9938-4d88-b057-90cdb290dac6 ce8460bb-6fc8-47ff-8694-1db8bfbd7144.rna_seq.transcriptome.gdc_realn.bam f4ccd7c83f48bf535a5cbb866bffdcae 14374706543 CGCI-BLGSP 5b4325c0-a7f5-436f-a7f3-630358e3ba2e bccbe421-db78-4cab-bc2d-ea31d7068582 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome e6fb4c5a-afc6-4a0f-807d-e61b5ff557a5 402aab465a4a12daaf1f82fae330758a 18023943300 +f07e63fe-5d1d-439b-a515-ae58f4743617 ab2ddd77-9ca4-4e8a-95c9-fad532661172.rna_seq.star_gene_counts.tsv.gz d09e3bc8609c7f3ba62f671c738c50d5 407348 CGCI-BLGSP 49b5173b-fc55-4ae5-8b72-964f2173395d cc40c6e2-8ffb-4b3c-9da5-2d9edb7eef62 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 9cc83737-90a8-4765-89b4-e8a4683b27fd 3c459365bc2d15bd6681aee7b7c9d70b 4227384 +f60fcf1c-1922-40d7-986e-a6aa7b1a94ba cf417655-9985-4f19-b941-2acb0e8f418c.arriba.rna_fusion.bedpe d1d4bda14277b8ba6525648a30fb2e91 6918 CGCI-BLGSP 7dcc3723-aed6-4d2f-ad8b-afa443634139 e091e258-4d2e-4bae-a56f-d35a051044dd Structural Variation Transcript Fusion RNA-Seq Arriba 8d5c6dbe-c336-425a-abf4-af1ee66e664a a17dbdab5426d4d358e4e5561898f15b 6988 +ffd89422-ff53-481c-953c-965043bfeda3 a9313ed1-72b9-4e74-b624-db89a56d3832.star_fusion.rna_fusion.bedpe 894872c3c65d55db17b5b572b73a7d15 727 CGCI-BLGSP 32ca8921-9f22-4854-a451-b98f10513f20 c65baac8-2a69-4654-8e62-6d1f113ffcdd Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 6cc3e229-0947-44ce-87ea-450aa5284313 77c143c675fc23bdd2564d0c42c6e2f5 447 +ecbc479e-d7a5-4ad5-8276-054e460c7ce4 f0ee0712-8bad-4a66-a231-8478a2021d68.rna_seq.chimeric.gdc_realn.bam 03c645f7ebd01e85ecbfc4af8a75e492 83240290 CGCI-BLGSP 3dc70167-c921-4cfe-b784-20d22817532d 0e2e0e31-bfc8-4753-8c7e-fb64c5c36553 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 13c0fe71-a7a4-46c3-87ea-daadfb363a6b 4098744dc9215a1c7e5ffe6f2c48b695 87982524 +ff6c76c3-89c6-4024-926e-0f17d3bfc3b1 125a69d6-5062-415a-8a51-8ba983a0bba2.rna_seq.star_splice_junctions.tsv.gz 92620c1da6baa2da2721e3a5b7cb843a 2944324 CGCI-BLGSP 75a86324-6a4e-4921-bc3e-375b848f3d34 8c6dbbba-1f3c-48b4-b48c-a3e46286f60f Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5e022eda-0d37-4b39-971e-98be472fde22 fea25911193e9e00c57ba54ea33b8734 3035515 +a4cee21e-a0c5-41d8-9fac-5b6fa1deceda c8744c5d-1753-48cd-8274-cbec800b184f.rna_seq.transcriptome.gdc_realn.bam 6cbf5677d7cb1fe80efce1361d379db4 9282653608 CGCI-BLGSP 5fadbb10-de7f-482f-8460-54d513b5de89 38d43672-4e34-477b-a2dc-9fe1f8cd450e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome c1d8a034-9a65-42ff-8467-7aab9c95ed74 a610df1fe6c204f464b08a31a8e3ce57 11174506900 +379cd9dd-3178-4eb9-b5be-1d4fcf6835d6 45876bca-f8b6-4be0-8232-1ba7f5afa6ed.rna_seq.genomic.gdc_realn.bam 25d7642c3599c19eccfe92aaf82d45e5 16257299657 CGCI-BLGSP 257f421f-d0c9-4510-b7dc-7e98925041a9 aa07f36d-66d1-4a8f-8214-c414179151a7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome b80b9333-fd8f-4773-94ac-e2497a08096c 4bee388cb239d9f1687c2a6d675b6189 17798122130 +8ee17b97-55a5-4c82-92b5-7958ce07258d 0186c448-fb61-4429-b9db-b8feb72f4709.rna_seq.star_gene_counts.tsv.gz 0f3805f178829b7e6a93e78810e72f3a 412352 CGCI-BLGSP 75664f55-936b-42cc-b0ed-f219112c06f2 ccbfd547-c8e6-44d1-a013-69ff6428e655 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 204193fe-5fd1-44ea-9868-fa4cda508ae9 f55bb16d10e81c5afd12c48e2a0c6b72 4230681 +a509520f-7870-40a8-a97d-d80377c1cced 9d9af23a-2399-42af-a4e3-215f48a8a057.rna_seq.star_splice_junctions.tsv.gz 143ee167ea8d000df403501de2d77dd3 3236592 CGCI-BLGSP b5befdad-1ff2-408f-ac0f-8af149b7d606 c5871626-85e7-4718-a779-ea4e3738f041 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts ec0f2e90-5a6d-4a93-acd1-ad5f438ff198 ed70ba11f15defd95d7edd6244228391 3340091 +b5dd3725-3fca-443e-b5e9-93d844835330 a07ebe99-d21c-4b2f-9f12-11ddcb56701e.rna_seq.chimeric.gdc_realn.bam 36722db661754395f2077667f2431fd7 66768794 CGCI-BLGSP e90aedbb-8398-41e3-9bfb-df17f91c1eb8 258fb876-8fa2-4c9d-b8a0-b2ad7ac27962 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e7ad5c39-183e-47bd-b564-177d433173cb 780068c1ad6fb1dc05e9e1d052411f07 68728133 +0e97637a-69f3-45c0-a8ca-f508c3143bbc e2c2f95c-3f1d-4fd6-8faa-9f9d73054eff.rna_seq.star_gene_counts.tsv.gz 552c029018649b4ce2238e3ed23b11f1 403701 CGCI-BLGSP ce4274a3-7c59-4392-aa8c-14f4d2c134fd dabc4596-656f-4132-a65f-d9bdb0ce432e Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts c9de88be-6ce3-491a-802a-06a82a7ec885 98026475a5b1cfc7ad7e45a217351567 4225992 +568fd4e4-22cd-4b47-b338-23088eccd97f 1cdf825f-90c5-42d4-9e01-ae6bb0035f2f.rna_seq.chimeric.gdc_realn.bam eae00b5b4b8f3171c8b7e7ee88e49c1a 126266853 CGCI-BLGSP 8c9c36bd-ca35-4158-ae79-b317d3a61128 94205a3b-72ee-476c-9f30-8e52b9f66418 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b234ad5c-bde1-49e9-9afb-29d7d3c8b72d 81dec251a7dbadd71bdf63b0d0f90aca 132932016 +eda9421b-ab9a-4532-ab58-b660ba7b7f45 9c8ed150-492f-4475-ad45-184590068a11.rna_seq.star_gene_counts.tsv.gz 9d3b9d6785842561647496e9e2d8d0b8 407669 CGCI-BLGSP d073b5bf-f145-4ce9-b938-527634f164e4 843c0c90-8e87-43fc-8610-10da9ad6e567 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts c8d36672-f1e2-4425-85f4-a35f44c2296c 1615213d95fd4b9ed4a860b2af1e0495 4230814 +a1b35454-1cc2-40d3-b432-81a4f99b251d 737ea3bb-ec46-4707-99a1-bf3f61052aaa.rna_seq.star_splice_junctions.tsv.gz 3ed885d2a01dc996a399fed0d92b7b5c 2864377 CGCI-BLGSP bcb4326c-3c7f-48e8-837a-b43bb2535a0e 784a65a6-e398-4c51-9744-c475933bf478 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 1e5106a7-73ad-48cc-94c3-ce80ecbc2f34 6435f22fb955522d3f77c1f844a8c194 2923453 +53e3a84d-378a-4447-9eb9-d138cc3ea318 8e3ee77a-c4a8-4160-bafd-effff20b945d.rna_seq.genomic.gdc_realn.bam 52ed8762209f1e0d2fcbe9870f2cf172 13137482655 CGCI-BLGSP 89335258-7991-4e19-87e2-60bf747d89bd fe44714d-e304-417d-bad6-acc48e127bd8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 2980628a-d155-48a6-bcd0-5bd75392479b 0aa580e56e4bafe46b9b58f2a025eba2 14643402187 +f9e0f89a-9a6b-40de-a39d-faea5c25d6b9 64740673-3511-4b90-b796-30dd470bfca4.rna_seq.transcriptome.gdc_realn.bam f3f43a2ca3a94f2862ece04fd4af21a5 9514362432 CGCI-BLGSP 886e1609-e89c-4d5e-ab9d-4f9ae18c937a b6a72a45-38ce-419b-be45-3b4808047c72 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome d7c3f9ff-dd16-4999-bbb7-6a8cd85edfb7 a96b83da6c0602901b662a719ffe771e 11357154910 +fdfc663c-60bb-42bd-8053-c232e55cd2e4 9c8ed150-492f-4475-ad45-184590068a11.rna_seq.star_splice_junctions.tsv.gz ecb1b78248c9d8a22d2f961e5751e6a4 3153565 CGCI-BLGSP d073b5bf-f145-4ce9-b938-527634f164e4 843c0c90-8e87-43fc-8610-10da9ad6e567 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 60371ae0-78b6-4fbc-9adc-c36bfdd18315 3c7daeebcc3c90fdb08ba4afc9dff2bc 3270988 +6b4a226e-fd0f-48b0-a72b-178cc3397277 6fe02f08-0979-4b31-a6d8-39f343dc30e2.star_fusion.rna_fusion.bedpe 25d2cdd08c9da0d524750f934a7d0b1f 463 CGCI-BLGSP f9ffbc74-e1c1-4579-8465-cb2b96a1200a 4f8933d2-6f2b-4ec5-9415-c647d2c56193 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion a031ab92-d05d-452a-8f1a-a61eada7d475 26d21d7849a0a72d7b649fd6e89ca84a 881 +8026a530-ab7d-4929-8fe3-88334f5cdd9e 179056b3-a66d-4bd6-a513-795948e0f5be.rna_seq.star_splice_junctions.tsv.gz 09903191d5ebaa84546b37882e925ecc 3249642 CGCI-BLGSP 32f687ba-28e5-4efd-9e27-5835f6416fb4 0783dc52-8dcf-46f7-9e1a-93252e11efda Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 52948e33-f895-44fa-ba4d-28d9f55de0ae a41b5ecf85e1cf3fc9c7835cc243da3e 3324040 +cb237318-bcf8-4914-b206-e6b6357e3789 9c14c3af-492d-4b09-98ba-c87fd82936af.arriba.rna_fusion.bedpe 4969070a271aa18247159d4a295540ef 6400 CGCI-BLGSP 90e9183f-7210-4922-a653-21c86e488887 a244ceda-46a6-4461-8506-778e4ec75e2b Structural Variation Transcript Fusion RNA-Seq Arriba 1c580fbc-feaa-4107-8bb6-3496eeab8b3b ce9881d67e15e2e3f5079cabb7e8fc3d 5191 +44192c41-e773-4164-b91f-27e6546aa603 e5354a59-9d68-448f-ab12-ddca4b459650.rna_seq.star_gene_counts.tsv.gz 834c9ed5d61479f68883f523f6bcc220 401074 CGCI-BLGSP 58576f61-cf0d-4542-9f88-257ee412af7f cad655ea-5320-483f-b35f-a28d64d9210b Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 348542d5-1b69-475d-943e-87fd34fce9f1 a9a9fc71e9d8df457959328d2ac5ea0e 4218621 +17595638-dcaa-4800-b3d0-947adb4a2b4a 52966518-c40b-4b5a-bb24-fe779bb02441.arriba.rna_fusion.bedpe 241bb858a9ee1f481dec9d4374bd7186 3955 CGCI-BLGSP b59a2c3c-7085-49c5-909a-c8504b1ae2a5 f66b1acc-8129-4b33-b06f-e3937a157c14 Structural Variation Transcript Fusion RNA-Seq Arriba 949c4cd9-617c-42c7-986a-bc121058b927 3c633b9a91dd5812bca704de156e1678 2819 +7aee8e6e-da8a-4780-956b-2591b7b09aa1 6236b0ef-6d23-4883-af4c-3f9639574079.rna_seq.star_gene_counts.tsv.gz 866aa52b7464ebe502c7205cfe0b70f3 411621 CGCI-BLGSP 557ad893-cb31-4fd6-bdfb-7f7930787dec a2ec82e8-7c6c-4f2b-a80b-595b6fb24409 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 70fe1ec9-64e4-4c30-82aa-bb0debce82f3 48a068b695af32e9e5e50f3e72df0a28 4231230 +a2a62f19-3e08-404e-b643-47d1ce6154c0 f06ccfd8-eceb-4653-9eaa-af6281f9cea6.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP af918a1b-56ac-4ebc-af60-b0823023c185 aac8c165-4613-4ff1-a6a0-48229c398010 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 557e8fc9-2ae3-4b31-b9c8-1c41dd581dbb 6e5690795ff424264402ab9d2661b62b 229 +3d3c0db4-154a-45a5-9200-ec298d5110c5 94624811-7716-4ae8-bc12-d36129bee6e2.wgs.ASCAT.gene_level.copy_number_variation.tsv 75dbe4c37e885985b6b96320d81b9360 3482764 CGCI-BLGSP c2282c90-795d-4c90-9c4b-51e340f98ac4 44178db9-61fc-46df-b0a0-b15ed4b9b757,fc14b753-ac6d-43b4-9521-a56f47f9c109 Copy Number Variation Gene Level Copy Number WGS AscatNGS e791c10a-6057-4b57-bf72-7787fb27510e cbe2ce1ab5080dd066b0e7d7cbf873ed 3442757 +d790f47e-7ae5-4d85-b4a9-418a08bbf3aa c28e898d-d866-4b94-aadc-1c5a791a95a5.rna_seq.genomic.gdc_realn.bam d23ffd197a2f42177d9bb47eb4a1f438 10683305660 CGCI-BLGSP 213e9f9d-7340-460c-93a3-edd559b42009 e587bb35-4d34-4a5c-b11b-b1d6992b1482 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 14618555-3c88-4e4d-9f6e-054a8af0a2b3 ceceb364cf117b23ed953666e7c1e147 11539197617 +5245decd-2b9d-4a68-9f41-00eb2b0a0497 10cd0f13-d3ff-4939-be62-6f661b7f2372.arriba.rna_fusion.bedpe dcef0d054b84da243fd0fee61103a6fa 4562 CGCI-BLGSP 2a587474-c6c3-4322-b1ad-a11f2d205bb4 79288db5-aa59-4656-9955-d59272d4f7d7 Structural Variation Transcript Fusion RNA-Seq Arriba 5af0e0de-96ac-4d10-96ef-98bc455b1909 c702f894c572bff3af7a30252ab2d153 4149 +d115c3d5-8588-454a-ad8b-ad32b0aa587e 10e693d1-4ebd-4b3b-9781-f3ac72f24908.wgs.ASCAT.gene_level.copy_number_variation.tsv b3628502c223a5de2aed770048a11cc5 3482758 CGCI-BLGSP 39dce88d-112c-4a3d-b2d2-11e0616594d8 6fdd85b6-8185-416a-ab8b-d45f37c523ed,e3542ca3-2bec-43d8-a124-ae66d7b5e7c4 Copy Number Variation Gene Level Copy Number WGS AscatNGS 9b8ac7e5-4586-48da-9526-58f0274197e8 5323e30a527dd78990875ba3a20e7525 3442751 +b32dd599-ca00-48d2-954f-cc2bf06017cf e24b4649-8857-4fef-b986-6fa1f8c18b41.rna_seq.transcriptome.gdc_realn.bam 9202ecff127899897878881e2579ec00 10304161638 CGCI-BLGSP 853704eb-f49e-4509-82dc-47a85c7335f2 082efedc-0c4d-4331-ab3b-20a9cfb77a79 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome ca9c59a3-2692-4470-a821-1f8f06d8014b d879ae29d7ccff2efe8f6d122928d187 12382346778 +b70e44cd-47f1-4e0c-b1b6-d9843c2a4ef0 c8143bd9-0b2e-4ff1-a9da-f0ff1f3ff97c.rna_seq.star_gene_counts.tsv.gz ead48870b5680f85d1fb142735370332 403821 CGCI-BLGSP f9ffbc74-e1c1-4579-8465-cb2b96a1200a 4f8933d2-6f2b-4ec5-9415-c647d2c56193 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 5c944889-9f82-4e72-992f-5c5d056b4bae 9c33b89d8695cc413bf0c92acf3cdb57 4225759 +061468e3-95cf-4b16-ac2e-4c981a26cb4a adb7f256-a485-4aaf-ab8a-ec766ecbd81b.star_fusion.rna_fusion.bedpe e2d224a8ef2842e57b9e0bd0b0c1a09d 506 CGCI-BLGSP 6c957218-bef4-48c6-9c8d-0352dd8d6077 c345daff-b4a7-43b4-98dc-406cd3ecd37b Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 949975a6-3b62-4f5a-8593-4c6d520cb97f 6e5690795ff424264402ab9d2661b62b 229 +28189a23-7bd4-4763-8888-432c57fa1b44 a5e3d4f6-564b-4c13-9caf-7104776a503c.wgs.BRASS.raw_structural_variation.bedpe.gz fc1cbc67e30545673ecfe331a91b999a 11072 CGCI-BLGSP c7494967-0585-4929-a4e1-4f0d76c406c6 e6c91164-272e-4ed3-899a-995a28a0d3d6,6e257f50-7a7d-4a6e-ba7e-bf3406edf42f Somatic Structural Variation Structural Rearrangement WGS BRASS d0508472-27d1-417b-aa1a-210bdf91ca09 1a8a08a1b554da71222646e9b4e0ed56 40032 +e562504e-af02-4c0c-a494-41d1b69824c2 5043606a-ece0-4c52-acb0-32087429b361.rna_seq.star_splice_junctions.tsv.gz 744591b3da4935f8f4ae329eaf1376b2 3284732 CGCI-BLGSP c2282c90-795d-4c90-9c4b-51e340f98ac4 fcf6c07b-c1a4-4f0f-8691-5e35c111d3b1 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 0f406f10-0ee3-4b7b-a478-f13356d9a566 2603c738b767578cdd9064fafde0b86a 3358719 +a3721e70-ad6f-44a2-83f9-b1abf7553544 f80fe651-5309-4d89-958b-2c16aa33ebac.arriba.rna_fusion.bedpe 3b7edb99792cf2c1579ed8508d469082 2110 CGCI-BLGSP d691aab7-cdcd-4c0a-8294-91e29f97c00f 9eb3f03a-d123-4eb9-bfad-d4a1e2d07035 Structural Variation Transcript Fusion RNA-Seq Arriba 3945a2e4-e4cd-4dc2-9dc5-7de30d6ba631 c3e7534e95e37b330fed141bf0758c12 2260 +f7d965d5-659f-40ce-8e6f-7b1461ea3031 01af0eb4-3f14-4f29-8341-e1f76b01c96b.star_fusion.rna_fusion.bedpe 0621fdc1c142afbf20c88a81e27736f6 1597 CGCI-BLGSP 3703e3e9-1f3a-445e-9538-d924014c822d 2e9fa249-9648-4b81-9894-1caa574d6041 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 0c3cf43e-6514-430f-9ac5-99986587af7f 75ce702c12fb0f10a677487307155cf9 661 +5486ea05-8a99-4c75-95f9-875e1ee30cc3 649824de-2c58-49ed-97d0-f75da2378cf7.rna_seq.star_splice_junctions.tsv.gz 2c8d79d8611dba114294c519cd105a9c 3610081 CGCI-BLGSP d0f47e8d-df1e-48e6-a127-6ffdcf7be450 f32def78-5bd9-4514-b517-3a06086ffc7c Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 0bfd7cba-c4bf-4f29-9b25-85e5abf2fd37 8f51e0554496205cd057336aa11e158d 3706942 +e72c1131-e428-499c-8ac7-feefd3e25430 067edaa5-dd57-4c5a-95f5-913a4780f8fe.arriba.rna_fusion.bedpe 42f277f563bd3be6b52e7e9286188d16 4977 CGCI-BLGSP f4a0bef2-c397-4149-830f-8d5f62e1b5e8 39eeb322-1c7a-4859-8c3e-848e0f83233f Structural Variation Transcript Fusion RNA-Seq Arriba cd0c849c-798e-476f-972c-eeb5bacf7746 395ef349ce5b3aada19c213ded31c11c 5622 +4fcd7b54-cfdc-4052-b806-c8314d72cb03 8235d7c0-284d-4b65-b272-5a62e4fa6dae.rna_seq.genomic.gdc_realn.bam 50960db74f042ef2f45676e66f6dbf03 14814131822 CGCI-BLGSP 1baeae6c-057e-4f47-9f8d-5d42aee5d3fc 503e33b8-a5b0-44f5-ba00-8eff720e3808 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome f9c36f84-095d-4ead-ab04-abdfb1794d4b 093b267543cf32e3299cdfa4a6853de0 16103290905 +240ed28f-f7ae-47ad-aab8-f3ed52dcde63 122ac1b4-5181-49bc-9a37-773abb21772b.wgs.ASCAT.gene_level.copy_number_variation.tsv 9910b95310b8837d0365abffa8babcf0 3481135 CGCI-BLGSP bcb4326c-3c7f-48e8-837a-b43bb2535a0e 98310363-1681-44f1-ab47-2a5a8296309c,3293b918-454d-435d-bace-b0275ec97f70 Copy Number Variation Gene Level Copy Number WGS AscatNGS 60811ee9-44ba-4037-bcbf-721ee6d98769 1e2978a72c52a3e1c6aefcab9614a52e 3441212 +6b7ccf1e-96d4-49ae-872d-1ab9556bbb0f 5656a116-2e23-436c-8341-3eae83035998.rna_seq.genomic.gdc_realn.bam 26d2510619b2d52b977d1e39c5232848 12199415446 CGCI-BLGSP 0f4cddb3-c60e-4d95-b90a-3e26756a7bfc 35e80027-b59d-4cf6-92a1-162f2f79ce82 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 14597b2b-e0f5-4815-8a9b-ee2397f0ad89 1f949b864f53a72e1749b0322b6f9d08 13287846785 +f8bf60bd-fb1e-4c48-875d-4cffc84feb1c 93d95528-00b9-4c45-9525-24a55d6a4cd0.rna_seq.star_splice_junctions.tsv.gz 3bbe8066467a485aa8cd90165de3479a 3163120 CGCI-BLGSP c334fa41-78ea-41ab-97e7-44db7fa8b460 de0f94cf-4f71-4d6e-982c-440365d880ad Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5c35d407-2060-470f-8fd0-6346da3ae666 8ddb2ed0ba3161c302b7f80166e3b21c 3253617 +df39e988-2f3f-4570-99d9-2ad0a54e21f0 c27ee106-9a5e-4e44-9b73-c16e56fbb0d0.arriba.rna_fusion.bedpe 00942b9ea3b84b8338da9e4b8885ff3a 3489 CGCI-BLGSP 06c07e2d-a04d-4099-a29f-948e40558dd1 2e9ae889-acac-4f29-aa7a-a6584ba571e8 Structural Variation Transcript Fusion RNA-Seq Arriba 53596527-d626-48fa-9828-d0150ba470aa 206f54e3b4381d7cade5f6259a278199 2809 +b77a19d6-d185-4e76-aa77-5537067783cc e1ac94bb-edfe-4785-8ea0-7919f374b0b3.rna_seq.chimeric.gdc_realn.bam bfa8b0e26d7b9833675bcbdb89203739 231224421 CGCI-BLGSP f4a0bef2-c397-4149-830f-8d5f62e1b5e8 39eeb322-1c7a-4859-8c3e-848e0f83233f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 4f24fc9d-d649-49c2-b94d-01f0be294b8e 26e5aa0eedfebb0b73b1b6abe49ae585 238117643 +5cbc5587-6139-471b-b4e3-5ca914196b25 9d9af23a-2399-42af-a4e3-215f48a8a057.rna_seq.star_gene_counts.tsv.gz b5a214e381da058b638a1144bbaf00cf 402449 CGCI-BLGSP b5befdad-1ff2-408f-ac0f-8af149b7d606 c5871626-85e7-4718-a779-ea4e3738f041 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 55e47ddc-aba0-47d1-80dd-1dcb6011bc60 e5e9bc9d712ddc8276bce325243d917d 4224753 +6029c3fb-c743-4e27-b595-8709ea6010fe 674e747f-4ae6-4fcb-af7f-1ebbd05f2820.wgs.BRASS.raw_structural_variation.bedpe.gz 6fb599326e8ea7d4e31eaf06c0db9549 9818 CGCI-BLGSP fcd39a3f-169a-463f-8153-17ebc1b218a8 7eaec814-8ca5-475f-8f84-a1285277adb9,731c7b44-04ac-4f34-a6e7-faa389c4fc03 Somatic Structural Variation Structural Rearrangement WGS BRASS 2a035dd0-3aa6-4bf9-93de-74c42db7b182 f8765306d25a152a1819780997dd56f0 34726 +20be8993-1d41-40dd-b91f-539c8082efd0 0186c448-fb61-4429-b9db-b8feb72f4709.rna_seq.star_splice_junctions.tsv.gz 65c78e6449b0b6c0ec0b9b35c3cd4365 3575459 CGCI-BLGSP 75664f55-936b-42cc-b0ed-f219112c06f2 ccbfd547-c8e6-44d1-a013-69ff6428e655 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 4b6e8863-4794-4ba9-b6d0-a1451f8237f6 39081ef4ce32ffbb577ee758bbaed0f5 3705067 +db2fe650-8817-4638-8bbe-83a1713bfeae ab595c6b-b79e-4f98-ad60-f4a97e1448fc.rna_seq.chimeric.gdc_realn.bam 50c4bd1905b1c06d6e9e3eca0678e1bc 157664635 CGCI-BLGSP 60acb146-43b3-44a3-9791-79284dae285e 2defb97f-3d9d-4624-8447-5d6b9e92e7df Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 1941a2b2-0579-4fef-8e53-75eeb37c2b72 ea4bb01c881c54c5c6f55b8f406fd251 163602537 +858b0dbe-9d32-487c-9353-35f5c8ae1644 61b31fd9-fbf7-4d9d-a06f-d5b6fe9013ba.rna_seq.genomic.gdc_realn.bam b36a5a2b8bc8fb0c239082adb8550842 10621118902 CGCI-BLGSP 2e21d338-6ec3-423e-9f7f-8b61fe428c3b 4bde5ce8-b94d-4609-b0d2-5f8d8422f289 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome f91cf846-0594-4733-9f47-f18dacb3e425 74672211b3e6ca908d40e343c8ee333e 11408971350 +ab752a66-c5d4-43ea-a6b0-622b994b9576 74d5f338-f046-41fb-afdd-0124c8ee9513.wgs.BRASS.raw_structural_variation.bedpe.gz 66f75451a38c2440a0a5a8450fa7d8e0 11371 CGCI-BLGSP 2e21d338-6ec3-423e-9f7f-8b61fe428c3b 25546b91-8f29-4cbe-9214-e04db26126d0,f1d43ca4-06d0-43d4-b528-49ffbf1021c5 Somatic Structural Variation Structural Rearrangement WGS BRASS 6c80f59c-758f-41a3-9142-97035920e514 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+88cd8609-428b-46bf-9fbf-ca60b345c218 36c429ce-ff62-444d-b5ac-c35dd9358437.rna_seq.transcriptome.gdc_realn.bam 7b83362e619083bccee26d9c06a73f0a 13274260487 CGCI-BLGSP a349d361-885a-427d-967e-cacf830bc829 d5b61e46-dcc8-4bb8-af82-28b0837e6200 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 19339405-8ebe-4510-91a5-615538d0705d a6165307484bac59a0899d6470b4d500 15825321408 +9ab63eff-a40c-4f01-aa90-4d427938d860 47c6cfc1-16dd-4674-89f4-fc8255e60cf5.arriba.rna_fusion.bedpe 638434932edaf97eeb1a9c5f1d1b578b 5118 CGCI-BLGSP 486fa825-324f-4011-b43c-f6454702e0d6 01a6744f-6d5d-47ab-9455-30327866164f Structural Variation Transcript Fusion RNA-Seq Arriba 19b80bbf-2f93-4b7e-b9f7-315995ca6a94 8c8c74e4ad3434d4b074c6ec7fdf5a45 3939 +2242b28a-f719-4b7c-b6ca-513b0d0be372 1cdf825f-90c5-42d4-9e01-ae6bb0035f2f.rna_seq.genomic.gdc_realn.bam f1f6c0b25d23c9f2badbf276555b3f08 13524250243 CGCI-BLGSP 8c9c36bd-ca35-4158-ae79-b317d3a61128 94205a3b-72ee-476c-9f30-8e52b9f66418 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 9c0220db-b764-4aaa-ac3f-8e5587e4b833 997050a431c307708ddce701e5c72801 14743483614 +34830f39-4ab3-4622-8343-5a64820fde92 cb67e36c-bf6d-4980-a9b2-109fe67294d1.arriba.rna_fusion.bedpe 750c7bb993aa75b24879de9c1422ff99 5658 CGCI-BLGSP 13c615c0-74b2-4b41-9a05-b8a71eca0685 88b60fb0-18f1-413c-860a-f057bb371d47 Structural Variation Transcript Fusion RNA-Seq Arriba a4b234b3-542b-414c-adbb-6f553e15a1ff 9e735445d62c4cd52cd674f1c5512ab5 4689 +decdeaf3-f4d8-48ce-8116-8b584ba3fd05 c28e898d-d866-4b94-aadc-1c5a791a95a5.rna_seq.star_gene_counts.tsv.gz 3d0d4e818beea0d85c239f2c3f545326 401621 CGCI-BLGSP 213e9f9d-7340-460c-93a3-edd559b42009 e587bb35-4d34-4a5c-b11b-b1d6992b1482 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 5b18cb06-e065-423c-add3-7e05f37ca07e 909c19a5aead28f955e84a6de344f7cb 4223308 +d409d664-7e76-496a-9347-616bf4f1e4ed d739d611-9b08-4d27-9902-0e82f2a2bc1b.rna_seq.chimeric.gdc_realn.bam 90abc54486e52014bf2059bc15de66c7 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2-Pass Chimeric 7639c2cb-7552-497c-9e02-b7cd8480946b 86096fa9bee07f965c70fe3871a2bfca 290170008 +6cdf1374-142c-4d2e-a346-2dd6dcf38d6a 351712ad-9254-4175-9ac7-f0d24847ac9e.rna_seq.genomic.gdc_realn.bam e864408fc929523bff95df28d9136b32 10832957528 CGCI-BLGSP e0ca8db8-b71b-4a63-96b4-96d368cc4fd6 9be49a9b-548e-4214-b553-156bc083f9dc Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 41bc59f3-5143-430d-98f2-7ef3457ca4a1 91f7eb6583a8bd8b1a985a5e1be7147a 11858043240 +45ef7a03-c415-4ef5-93e5-0d7bfc4110a5 da4a05d1-4d1f-4571-8ebc-7ce7f764147e.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 8eb3f8de-84ee-49cd-ae33-5cdc3cbebf3d 0fd505be-a785-424e-9a45-02d31e014793 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 98ee5579-be6c-4237-9b12-e1a2fe59f3a5 6e5690795ff424264402ab9d2661b62b 229 +d08072cd-e6e4-4d1f-8d6b-603e29a6a0d1 9a0ac5b0-6744-474f-947b-77c666ed3d73.rna_seq.star_splice_junctions.tsv.gz 9e26eecc1337d50c22abab7ec4a0f435 3118623 CGCI-BLGSP 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+91072dcf-5925-494b-a33c-0bfcc54a95fd 3ac2826e-cd0a-4c2d-9b3d-53fb5ef1cd96.arriba.rna_fusion.bedpe 14adc2f43b16acca803bec9c813ee369 1537 CGCI-BLGSP 886e1609-e89c-4d5e-ab9d-4f9ae18c937a b6a72a45-38ce-419b-be45-3b4808047c72 Structural Variation Transcript Fusion RNA-Seq Arriba 7bc07e8b-8cec-4066-a865-ab2dd0d36080 d174c0f94ddd30ec43c2e71bcb4bbd59 658 +e21ffa56-68c3-4d93-94d1-4911333d58ec 6bd72fbf-f317-479a-935a-9260a2420e58.wgs.ASCAT.gene_level.copy_number_variation.tsv 2c3816b93399638d1c94864ebc64417b 3482777 CGCI-BLGSP 2843599b-b36f-460b-8563-2e022974103f 141b91bb-dee1-468c-979b-537e7add0040,43c169c4-5701-4678-b976-84a03801f090 Copy Number Variation Gene Level Copy Number WGS AscatNGS c3120fe0-a059-49c2-9221-60680a3c703d 7befd53fc1b0675cf9a8bc2198716eb4 3442750 +d1b894c5-d176-475e-b8df-94a0755d2c35 e5354a59-9d68-448f-ab12-ddca4b459650.rna_seq.chimeric.gdc_realn.bam d0097b8b1d272384f4f34b3a311bc829 72703388 CGCI-BLGSP 58576f61-cf0d-4542-9f88-257ee412af7f cad655ea-5320-483f-b35f-a28d64d9210b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric d83e4b4e-ef71-45e3-8567-9346298c4464 98e7afca42ded1433bb52b0d309b94ed 75624833 +3b1c339c-bd95-4583-aef2-ab929a862cd1 0c6ccd67-2fd2-45d9-a147-d1b6eb6a0b52.wgs.BRASS.raw_structural_variation.bedpe.gz 2936bce683d421961eb69fd8977ebf33 12920 CGCI-BLGSP 3cfb178a-c476-4c0f-968e-55c57239e7c7 239774ff-88cc-49c2-82a4-f756b90cfa38,c30f3ac7-1641-4b53-92b9-f193951e6263 Somatic Structural Variation Structural Rearrangement WGS BRASS 8310e08a-ad51-4bdb-bd8d-55e3b705a390 4c0608e39d8a614f0a54852bb1126f7a 48640 +6fe15b6d-4825-476d-a4c7-a4c1eab6462c db252b7a-4595-4947-b9ce-d8ddb719550c.rna_seq.transcriptome.gdc_realn.bam c8078cbc797e91ea58d5561cfe15b36e 9143803812 CGCI-BLGSP 0ee808be-13bc-4d15-a519-e2b7e960e809 1529cc13-192c-4969-bb1d-c695f166fd2f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b0930183-6d24-4f1c-ad2f-e673e0ab9e4e 4875fb47df9308a60abca8053cf5fedb 10637827652 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RNA-Seq STAR 2-Pass Genome 778d9de5-3513-47fb-8fac-000b4ec144e4 33573109aaa7b2206efdf20db6622994 11719536895 +e366bb86-cb86-49de-b45b-f3079b9f1cf3 d23ab351-5c1d-4db9-beac-249d96519e19.rna_seq.genomic.gdc_realn.bam 8cd9caf1f00fcfca2457f4d49bd4b8df 16498667272 CGCI-BLGSP 2a587474-c6c3-4322-b1ad-a11f2d205bb4 79288db5-aa59-4656-9955-d59272d4f7d7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 60d5d136-cede-4a51-b91b-c20c1ff5c3d7 172813e0c104ce045a335a30470bdacb 18088012976 +8e674fc6-dcb8-4008-99e4-dcb061883993 9d9af23a-2399-42af-a4e3-215f48a8a057.rna_seq.transcriptome.gdc_realn.bam 2f696d6b979e61b9ec40221fb5d1c85b 14998294503 CGCI-BLGSP b5befdad-1ff2-408f-ac0f-8af149b7d606 c5871626-85e7-4718-a779-ea4e3738f041 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 716381a5-3c86-4264-afe6-56fa51b737f0 ce59fee03d6bf728295907e6bd9e687e 18280483066 +37f132af-d38a-476f-b601-16ab0c2483e1 5a6f3886-eb08-4239-b82b-384244ba61c6.wgs.ASCAT.gene_level.copy_number_variation.tsv 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Rearrangement WGS BRASS 76b907f5-9911-46e7-9607-dbaf8d3f1551 365268722b259009b64dd769882814b6 26245 +687b516c-c51e-4e42-acef-2ee0b641d6c7 291757ba-ba52-4886-a774-16dab0b8497c.arriba.rna_fusion.bedpe 80338fddeb5634a823b336f46db1b68d 4161 CGCI-BLGSP 32ca8921-9f22-4854-a451-b98f10513f20 c65baac8-2a69-4654-8e62-6d1f113ffcdd Structural Variation Transcript Fusion RNA-Seq Arriba 7a167efb-3c8b-4f10-b878-0133cc266d09 04387a3b528869cc93952ed25dc7433b 3648 +2cc74348-4b7f-46e4-be29-8f1e9ab43d1c 61b31fd9-fbf7-4d9d-a06f-d5b6fe9013ba.rna_seq.chimeric.gdc_realn.bam 4085a1ef74d9a19e6f326491cb5ed460 163612054 CGCI-BLGSP 2e21d338-6ec3-423e-9f7f-8b61fe428c3b 4bde5ce8-b94d-4609-b0d2-5f8d8422f289 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ad7c3734-aaee-4d4e-b1d0-0fc81662e917 908f9f6852e5ad7547ecb2ac3a52cd59 170122769 +264bedd6-955a-4bfb-9eff-d1d561261813 8923e365-26e6-4459-a012-9e76a2fb10dd.rna_seq.genomic.gdc_realn.bam 7246fbc39f17a536c628e36aa90e13c1 12175769102 CGCI-BLGSP 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+35a8f04a-0099-49c3-b02f-c13c4066c5c0 84b0a6bb-18df-428b-915b-f7e884751db3.rna_seq.transcriptome.gdc_realn.bam ccb898df1f46f52dad0fab014ee9f69c 12777907866 CGCI-BLGSP 0ceb3081-4c6f-4fd9-9535-5accddf76bc4 bbcefef2-c5b5-4c88-9058-dd4ae2200d41 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 811d0b43-6cfe-4773-bc30-503f267b101e 4a37b393a31558e5846dd15a18029218 15378114680 +14f07931-bafb-4564-94be-a913c6be2323 915bf14c-4669-4cb8-b1a7-27f0ddcfd96f.wgs.BRASS.raw_structural_variation.bedpe.gz 6e8d123a15cbb4f99256021e1c6ce773 10104 CGCI-BLGSP 98540fd8-1bb7-413c-b2d8-857e6e25309f f0b137d7-2609-4532-806f-bb0a6e2b5bdf,60d70cf0-c41b-4f81-b04e-6165a41565c3 Somatic Structural Variation Structural Rearrangement WGS BRASS 5b324f0d-9b13-4522-8843-8d7352ac06e9 7f425617582272f7a23f471ee0071fb3 35448 +8ebeaa9f-1252-4e01-9002-9612ce3132f8 9cf2754c-e825-44d1-b4a7-a9caff2bf55c.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP ef5d356c-89c9-48b1-a567-519aa478f166 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Quantification RNA-Seq STAR - Counts 9b2125cf-af56-4613-8c2a-d45056bbbed6 8de3f89fa67dc5240020c6b302f7cd31 4225205 +6d617bbb-71f4-40ec-8926-ea4498bcd32d c40951db-0aa0-42e2-a4df-209b7d2d49f9.wgs.BRASS.raw_structural_variation.bedpe.gz dedd6728ed1bab8fce184ea49c6b14a3 8351 CGCI-BLGSP d073b5bf-f145-4ce9-b938-527634f164e4 742964e3-c03c-4642-9f8a-74837a5ca9e0,58335d7e-d75a-4ad3-8bf8-f77e8886cb56 Somatic Structural Variation Structural Rearrangement WGS BRASS cc882625-54aa-4e64-ac40-4cf6903db1f4 546e6804f95f166b74c613751cd806a5 29230 +11e0c7d2-ec1e-40c1-a457-0bc31cbfca5a d5d42073-bfc6-4f5e-b350-180bb27a308f.rna_seq.chimeric.gdc_realn.bam 57f0ed7cb150b2a881c2eec55eb35250 99502134 CGCI-BLGSP 7c0891c3-7ddd-460b-a8e7-b33a63844ed1 14ddc614-f974-40ae-99d7-5827f7a6ae6c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 54c116bb-4e5a-4153-a5ea-61e0e2786a90 e2eb9a7dca62483c3e48da2d4d35699c 103919520 +caf3002d-0725-4503-97e3-98585e67d2e6 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Reads RNA-Seq STAR 2-Pass Chimeric 2e3a23b3-4243-476f-8814-cba0e72bc39b 8b7a522c6abf4a815572aef97dd5947f 212771346 +c84527cb-c724-4c47-8474-24512d599d65 1d55f600-6b0a-447f-a5d7-3d12f6f3155b.arriba.rna_fusion.bedpe 82bd1bdb6bd123ca0bca1aeae5940bfd 2458 CGCI-BLGSP 853704eb-f49e-4509-82dc-47a85c7335f2 082efedc-0c4d-4331-ab3b-20a9cfb77a79 Structural Variation Transcript Fusion RNA-Seq Arriba aaba6852-0c89-4dd3-a14e-19e4c6b1a17e de905b2204962f9cce367406d9bb7ade 2416 +5987bfa9-b8f5-4039-8f49-96acd609d480 261bb0a6-0ff3-43de-8064-785b45781e01.wgs.ASCAT.gene_level.copy_number_variation.tsv c8ea4fc78f8b6811d70da6c7f15a5d33 3482752 CGCI-BLGSP c96f21de-3dd6-47ed-a796-6270c1817dd7 10fbb06a-563b-4fe7-9508-1bbe5b129a5f,701fff05-b71a-4225-a691-15ddffdb4171 Copy Number Variation Gene Level Copy Number WGS AscatNGS ca83b18a-c9c4-4fee-a75b-5167e9816bce e0f4917f53a477499eb3919f8db7bc4c 3442745 +141c2a68-ca13-4d3c-94d7-fda1f30550d5 fce5f34c-4d08-4ac9-81e9-e6cac336f02a.rna_seq.star_gene_counts.tsv.gz 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Profiling Splice Junction Quantification RNA-Seq STAR - Counts b3339f40-718f-4783-af41-a474d1fd312e 70e24b6a04ad8330456531b197837a73 3595933 +2fd67299-bad1-4e83-842a-f7db6140398c 97010645-5202-49bf-b2f6-01de4580c6fa.star_fusion.rna_fusion.bedpe 27837b4c37de000b5bc0bb22cd7cb113 1005 CGCI-BLGSP 92194f18-046a-4222-9409-679b8872e6bf 4be4fb19-b505-4de7-b26b-a4fc582b3b8a Structural Variation Transcript Fusion RNA-Seq STAR-Fusion f9a79be3-484b-4a8f-91df-b3e228e082db 6e5690795ff424264402ab9d2661b62b 229 +7266ea0d-170f-41e9-824b-2a8370f03935 0aaf0573-e374-4a05-a654-0bfabc70dc49.arriba.rna_fusion.bedpe 7009ac5f99a5d4f36798d8896ba431ef 19188 CGCI-BLGSP eb6e891a-b8ab-4261-808a-d543d1dc07d7 e2393e0e-5506-4017-8960-6df5d3248e0e Structural Variation Transcript Fusion RNA-Seq Arriba a9674479-61f6-41f4-8a1f-a5ef486c07f2 4fd161286e361354ae3b07d5933167ea 19574 +6fc97f7f-8056-4b8f-ba38-2792bf742aad 6520b5f0-c551-4423-9835-fa2a10b94453.rna_seq.star_splice_junctions.tsv.gz 24c56770a8de4d757daf893826424f0f 3110337 CGCI-BLGSP 571e6d8a-1e84-4f99-8b0f-e55dd126426a 2bc66ae4-12b5-4230-8d97-74461598f17e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 86d1c346-01ac-4cec-9245-7af5695062ec a8f121770d1ee7542de4e8968e2b4819 3176254 +67ee5c63-7a2a-40f9-a1d6-dbaee0b3b7e7 a5e3d4f6-564b-4c13-9caf-7104776a503c.wgs.ASCAT.gene_level.copy_number_variation.tsv 00d31de93b16b674e8f8913215b4447a 3481132 CGCI-BLGSP c7494967-0585-4929-a4e1-4f0d76c406c6 e6c91164-272e-4ed3-899a-995a28a0d3d6,6e257f50-7a7d-4a6e-ba7e-bf3406edf42f Copy Number Variation Gene Level Copy Number WGS AscatNGS dcde9e78-939d-4178-84d8-4b227c862719 2d802a64177ebae75fbb69eb66315936 3441209 +6e275e4a-3baf-4865-9e91-834d50115752 9f76d633-deb6-47c4-8f61-fdbfdf06bb67.rna_seq.genomic.gdc_realn.bam 7885b694a54a6d60a675eb6d02feaa82 7597965938 CGCI-BLGSP 2d9d88c8-d827-4bc8-88c6-75e0d0c3f988 515c31a3-2b95-4159-942c-bcb8ab8c8820 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 66a3ce59-2f64-4f73-9db8-c23741ebfdda 6adea6265ac899f1a55e08bea7eedb36 8116324624 +35b57970-4101-4a2a-882c-33bbd9d8b343 60d15789-cbe6-4e53-bd12-bb262de18bc9.rna_seq.transcriptome.gdc_realn.bam b721ac080bf15dfc8c1d5c25c48fc2e0 8181850699 CGCI-BLGSP 1a81e2c4-b637-4028-ab28-4c64bc8bab76 9871641f-0dd2-4358-88d0-5ecd57a61665 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2f9536b4-cfc5-4b0a-b578-e8baf6677f81 8ce13647d14923654acceac4e81e0f36 9821021219 +6cc268c7-ab18-4298-bbc3-8cd1e4649853 5a508643-d1c9-4fa6-8eba-62b37e2309cb.arriba.rna_fusion.bedpe 52338335b60781b5ff7d5090b2a22b39 6796 CGCI-BLGSP be578313-e34c-4f26-aba6-4dc05dfd6f4d 759526cb-c73d-4139-9d42-606d85fa7423 Structural Variation Transcript Fusion RNA-Seq Arriba 2c9749a6-10e1-4dc0-af8f-b309ba392ba0 13d178c0414fdab1569e2a38d84a6c2d 6206 +75a07a3d-08a2-436d-9d31-9761b30e53ac c6935568-24de-4859-a11a-88a43494ffea.rna_seq.transcriptome.gdc_realn.bam 2530d54d1c396242d25d31c9088dd030 7888709832 CGCI-BLGSP ef5d356c-89c9-48b1-a567-519aa478f166 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b252b8b6-a0fe-4259-8a81-30ec8c72c89d.rna_seq.genomic.gdc_realn.bam 84cb7509938b89c618041466320c3850 11434127056 CGCI-BLGSP fcfdb847-5081-4086-8d32-25a281097390 2352a75e-96e2-4067-afc6-1d855f7312a8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 3fe63159-c5f0-4aef-8a1f-056b12442ac7 5bd6f9b4f0e278819ee427317041edfe 12770941263 +26ff194e-17b1-41a8-bd39-5f6259f9f27f 39bdbc5f-295e-42ef-924e-3c493c6e71be.rna_seq.genomic.gdc_realn.bam 8095d99bbe95b59c2339848e44c55a61 9408569075 CGCI-BLGSP 98540fd8-1bb7-413c-b2d8-857e6e25309f 15010d6f-c931-4fe2-be6c-e11b632f8f93 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a5d58e70-78c6-49d3-a169-25c6c7af3442 d8d942143b8b133c65f14064b12fd213 10344767100 +f0ac8f51-31a8-43a3-aa32-cdc488fc2406 8effa2dd-dde4-48ea-8c52-fbe799f1a83f.rna_seq.genomic.gdc_realn.bam e49036ba96d0d7b8682cf394576312fc 11095388263 CGCI-BLGSP f1e5c114-3957-4667-88bf-f7821c75e43f 65122907-b42f-4265-bacb-007f96424e38 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 581a146c-3330-4c25-a308-4fb57eb28709 645e0af2c88e7388a135c2faf852460e 11733129577 +f9ffe168-ec08-41ad-8373-b1761be8e51b 612403e3-9a73-4071-addb-d3373d991a63.arriba.rna_fusion.bedpe 5b055f52dbe36c0ac59513acd8717a4d 6287 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 2ee24626-72ed-4070-b034-92f88e7659c3 Structural Variation Transcript Fusion RNA-Seq Arriba 9d19000b-b1d2-4317-99e8-6dbf8a651c78 6e307910ca4e92b1d043f0f7fdb638e6 4273 +b790a350-b915-4e4f-b511-e5d53ea0dfbe 693f76b5-6d30-4bbf-85a4-f9e6f43d5f70.rna_seq.transcriptome.gdc_realn.bam edbbcc66d35449179fe7858348b80466 6933843445 CGCI-BLGSP f90e6333-f59e-4f6b-b7f9-17ba10e4a600 f9627688-8e25-4ede-bde0-8da01ed7528a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 25b9b7f4-078f-448e-9618-0610b1b46d3c 7add1a1e1cbcc3f5d6338e5af3c86507 8399965729 +394acf94-eda3-4727-b397-4f6610dd59a7 e24b4649-8857-4fef-b986-6fa1f8c18b41.rna_seq.genomic.gdc_realn.bam e8da608bb8e4c76e1c0abbfa8a711f4d 10388799940 CGCI-BLGSP 853704eb-f49e-4509-82dc-47a85c7335f2 082efedc-0c4d-4331-ab3b-20a9cfb77a79 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 5a2077e4-bdd7-4dea-b5b6-32a15682f7c5 992e33ad7ef6f30dd8c97cadd3de96a3 11394368537 +1a5d9ddb-52a6-4138-b19c-7dd443fce896 3841dc77-132e-4073-93e9-c71bd5a5819f.rna_seq.genomic.gdc_realn.bam 70b39f75b1eae95eee51a54d3b25439b 17843481322 CGCI-BLGSP 0024c94c-88ff-49d9-8dc4-bf77f832d85e 174dacb5-1f2b-4bf7-9ca9-9032a7cdb4ef Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a3518855-d771-4bdc-9bc4-a03388b98e77 4a8154701a1a0da959a27735ba7e9ee2 19772647630 +58f033f4-64dc-47c5-9ee5-abcdc5f810d2 8235d7c0-284d-4b65-b272-5a62e4fa6dae.rna_seq.transcriptome.gdc_realn.bam a521b107c1688fcbbce09d5e95c326e6 13681022338 CGCI-BLGSP 1baeae6c-057e-4f47-9f8d-5d42aee5d3fc 503e33b8-a5b0-44f5-ba00-8eff720e3808 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 56a33960-280f-440d-bc14-9f3cb0f31d93 12abcd4abcb8f4daf3d3a32a3a75f42f 16058479423 +d6393ea4-24fb-4e43-ad68-0c1c77a2374c 362a1ae3-1344-445c-8c05-5b36c9c123c3.rna_seq.star_splice_junctions.tsv.gz 8d7a9597fc4a9f3e76004c9c2efd710f 3205893 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 2ee24626-72ed-4070-b034-92f88e7659c3 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts b9dd7902-ffda-4c67-97ea-3612407a349e 0e3aae5bc628fd755ab04ef5acea9585 3276394 +95fe56f6-f6d5-46ea-81a5-e64d158d43c2 16e638e5-d192-44df-ae58-6936b40406b8.rna_seq.transcriptome.gdc_realn.bam 5c9ec5db9b2a1db9112601a65530ea17 10257989110 CGCI-BLGSP 486fa825-324f-4011-b43c-f6454702e0d6 01a6744f-6d5d-47ab-9455-30327866164f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome c239444b-e57b-483f-9c77-3f04c7e88465 95465d99361353cc8a3c003d275e4d4e 12511513652 +c8f0719b-dcd3-4ba2-aaa3-568a65fd81d2 d1ba7609-7c75-4079-a89b-e706a0b98701.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 7277e644-f3da-414a-9821-8037cc99ef9f 0632bc4c-43a7-4651-b18b-c813b214190a Structural Variation Transcript Fusion RNA-Seq STAR-Fusion b770f086-d58d-437e-b94a-93f931ffc593 6e5690795ff424264402ab9d2661b62b 229 +bde5a563-f08e-4758-a2e3-2f75c7812aba 16f86676-8b5c-42cd-ac6e-9024cee0e3c1.rna_seq.transcriptome.gdc_realn.bam 45e9393c2b868c5e8784695d3cf8fbf7 9589036701 CGCI-BLGSP b59a2c3c-7085-49c5-909a-c8504b1ae2a5 f66b1acc-8129-4b33-b06f-e3937a157c14 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 19f52f2b-a548-4577-a98e-86f1b34aad14 5ec1730f6ac5a107e747eb0d9b3f4dd1 11502265966 +32c04c7b-922a-4f0d-856b-ed66915f644d 30863c44-1371-4a19-9a01-472a3f58a613.arriba.rna_fusion.bedpe 9a55ac79e900a67f90e4b216d62e2c73 5177 CGCI-BLGSP 4b3049a4-2d42-4f9f-be26-bcb02b3aef04 06b696dc-ec61-4a82-ab41-e35255ba07d1 Structural Variation Transcript Fusion RNA-Seq Arriba fa210005-ad83-408f-b12d-b046b96f7024 a372e3861bbaab2abef9058b20f60cfb 4556 +ea5b68d5-0d1e-44f6-8fdf-43294df3656e 56c2f382-5952-4426-bdd6-79b0980b05c4.rna_seq.transcriptome.gdc_realn.bam 473c8a47d8493d23efeb729293abfad8 12599461874 CGCI-BLGSP 8ef78bfd-48cd-433b-a3ff-b8c4e755406e 92fc379f-38c8-4ad6-ba50-9de64d555ba8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 3ea46a8a-30b8-4fc7-87d2-de00e3e7bfbd e7a625405f21419879c0a2e8c5163ae3 14950927693 +5f538341-0244-4a48-b921-3f2d77559b9d 351712ad-9254-4175-9ac7-f0d24847ac9e.rna_seq.star_splice_junctions.tsv.gz 6379adb4956f53c66053569fa88b724c 3276993 CGCI-BLGSP e0ca8db8-b71b-4a63-96b4-96d368cc4fd6 9be49a9b-548e-4214-b553-156bc083f9dc Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts c19d47d2-918f-428c-bae3-b8a33c8878af e67498757d18cb472b1337449a25c4b2 3363950 +951881c0-2bcb-420b-8ce8-573d7692546a d4e33af0-46d6-441d-9d4d-8edef2458650.arriba.rna_fusion.bedpe 6c2edd75ee7e55e25664fc2725c9479c 3842 CGCI-BLGSP a7dfd3c9-4b94-4802-97c6-a096b276aeaf ac110d72-7f92-4581-a859-91e34e160825 Structural Variation Transcript Fusion RNA-Seq Arriba 15be4c38-f67c-4381-a8cb-52129e51a7ad 8e6dd518f05ac0dae67f9b31bb39b84f 4026 +d10fd9c3-0e94-47b2-9993-598d12f91669 b16c36d2-12d1-458a-9b91-864ff4a28bef.wgs.ASCAT.gene_level.copy_number_variation.tsv 3f8047312ddcca8807092d6e2eaa40e3 3482761 CGCI-BLGSP 75664f55-936b-42cc-b0ed-f219112c06f2 3fd6e94c-211a-485a-adc6-c8315e8a34e8,01752346-bee8-454a-98b9-f5269a22c07b Copy Number Variation Gene Level Copy Number WGS AscatNGS b3bcab62-a0eb-48e2-b204-ececafb25bfa fde580af4965bfa13db9fa401673fe58 3442754 +0701b562-659e-4fbc-800e-cc847f29e001 72bd90fd-a354-445b-ad5c-1e1d598264fd.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP c7494967-0585-4929-a4e1-4f0d76c406c6 7ed0f0ba-c6dd-47d2-8ddc-f9e6fef17e1f Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 7a7eba77-f4ed-4b92-bc33-1a22398be247 a2c9d05c7014f9cc425bb0aa27196601 448 +eb166cfb-d113-48b2-9a77-8e93cd5355d1 e9f6a146-7067-47be-bc37-c964b6d709e6.rna_seq.chimeric.gdc_realn.bam 945f18ab9f5193c72197e2bb1e0e4525 261664519 CGCI-BLGSP ee385ea4-54db-4033-b46a-8c397ed4aea9 8454651f-596a-4851-9055-ebd6e32527a7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ce38fa4d-738f-4a8b-981d-a1cd8fd8037e 813efc4a323093335a7f63b3d9869032 269762070 +987cb4e4-6262-41f8-9a73-7a96b4cd09d6 15a04b3a-88bb-4ebc-982a-939dfac3561b.wgs.BRASS.raw_structural_variation.bedpe.gz 70466381b80df418c6966ae0b8a78a54 11659 CGCI-BLGSP 8ef78bfd-48cd-433b-a3ff-b8c4e755406e 54371e6f-c22e-4a68-80e5-5eb757a978e1,f8c8405c-0c51-4f71-8687-2f9f90fe3df7 Somatic Structural Variation Structural Rearrangement WGS BRASS 4ae99f5c-0be2-4b68-8847-bb91a7dc5c44 284dbbc90ce3ac7f74566b67f643f979 40756 +1879b380-95ea-41f5-b7e5-3b5b8194afbe 39bdbc5f-295e-42ef-924e-3c493c6e71be.rna_seq.star_splice_junctions.tsv.gz 5cfb6f0a2dd1642ce2c274e3e6ca5728 2880050 CGCI-BLGSP 98540fd8-1bb7-413c-b2d8-857e6e25309f 15010d6f-c931-4fe2-be6c-e11b632f8f93 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 12d8db4f-e26c-4bcf-acf8-946ef0beee46 300bd61d279095465d6d9dcc79625cb6 2956484 +07d2362f-eb39-4f5e-894a-62d55c3e0216 b84fc850-bce1-40d4-962e-46a738da48d0.rna_seq.star_gene_counts.tsv.gz 180f4d5203299ffad88ac9a7d761ac3b 404021 CGCI-BLGSP 4b3049a4-2d42-4f9f-be26-bcb02b3aef04 06b696dc-ec61-4a82-ab41-e35255ba07d1 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 47f38ac3-fde7-41ce-ba6a-3f0418e8fd1b e75f88bf459fd46faa2bd154ccaaae41 4223987 +51eeee2c-2e5d-45b2-858e-5dc0ebad3c6a 2de1924d-7e2b-4344-a801-4e0e9392ad3d.arriba.rna_fusion.bedpe 815fa188ea3e8ade2ffd90ca3e8cecb9 1906 CGCI-BLGSP c9e0f3c5-f996-435d-8d2a-d32420aaaf9b 9450c716-a971-41f9-8d90-b8bab953de39 Structural Variation Transcript Fusion RNA-Seq Arriba 749c70c5-1eeb-4d3a-a6fc-fd43b5f13ed3 446fcfb6f1c594e661174f1dedc72de5 2791 +4f92b90f-db5e-4f5a-a633-f300bc2cac1f 681840d9-e016-414d-8983-5a2436fe757b.wgs.BRASS.raw_structural_variation.bedpe.gz 978ba50d071f499d146fc84e20776ab0 13937 CGCI-BLGSP 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Reads RNA-Seq STAR 2-Pass Genome aeaac441-611b-4271-a022-178909c921d8 c4d2dbc4c6e50661550c6eb456fbea00 10617886585 +3a64690c-1406-4544-b720-0e5cab875de3 62da2a66-2151-42d4-9f7c-ff1da8d9bbd5.arriba.rna_fusion.bedpe 016600a66aa4230c58d6bf6d65a94982 3133 CGCI-BLGSP fcd39a3f-169a-463f-8153-17ebc1b218a8 4db256e1-290a-4c7a-8852-c4f2658a2869 Structural Variation Transcript Fusion RNA-Seq Arriba 30b51bcd-5b9e-4eb7-9ca6-0d713b4968e2 6b49af6d49d00451b945028443b26d05 2711 +e0efa4e2-01bf-46b9-ab17-69e99dc262ea d0825601-6c65-4dbb-86fe-49f0193999fa.wgs.BRASS.raw_structural_variation.bedpe.gz 6beee2ef60734f459f0d51ac5b62cd87 8283 CGCI-BLGSP 853704eb-f49e-4509-82dc-47a85c7335f2 95d2e1ce-0333-44e7-bcbe-8534358835a7,cb85529d-59a4-40bb-8c6c-1661c510e18b Somatic Structural Variation Structural Rearrangement WGS BRASS b5ddcfdf-243a-498b-99e5-ebb27d563397 d7cbd825ebd79dd92d47b3a72f601a3e 28908 +42d90089-735d-4a86-b05e-6776ca76c236 ca9a68a1-a51f-4eb2-b8ca-b07b982d882a.arriba.rna_fusion.bedpe 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Chimeric 7f518998-bf47-4d08-ab12-0fab002f03ce 34b49ce9f23d22e73158726359681d45 307505137 +a392bbbc-b3d8-4919-9295-51a4cf0bb45c f940cfa8-4cea-41b1-942e-ab3b462cc370.rna_seq.star_gene_counts.tsv.gz 94d5d1d089799305c4bedbe018ab7eae 408234 CGCI-BLGSP c2010e3f-26f4-408f-95f2-9c06a43bee88 662c9e01-2a4f-4431-83b1-0dfb3c21b335 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 53f0b535-b69b-4b0a-b538-179477875a29 718fa2cf9726d24e17a9bee2b40fa86c 4228244 +8977d71d-066c-4657-9df4-d532c4690463 125a69d6-5062-415a-8a51-8ba983a0bba2.rna_seq.genomic.gdc_realn.bam 153671efb419ee2a37e5dc3474006fed 10902390948 CGCI-BLGSP 75a86324-6a4e-4921-bc3e-375b848f3d34 8c6dbbba-1f3c-48b4-b48c-a3e46286f60f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 239e0b77-6aea-4325-a73d-02983e09cf6a e8c7d991fb8c1564ccf3a0d9cc5365e6 12248567905 +5124ef56-a907-4fb8-9b28-9a6837b7c2dc 1d008808-e43a-416c-8519-768416ce6105.star_fusion.rna_fusion.bedpe cfb352990f28eab8241c5767044a4b0a 1643 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66428f29-c9df-4236-96b9-d50b89409ef4 Structural Variation Transcript Fusion RNA-Seq Arriba b0229021-6585-48a7-9429-dbe7c5e6ac81 2576900d5265d983a45d680793098f80 7224 +e20f3eca-60e6-4337-9050-b9d8caf2716b 6e86852f-e6d5-47ef-b882-d712eaed45bc.rna_seq.star_gene_counts.tsv.gz 7df3269f37de3a31e6d65e7d9a07ac60 407231 CGCI-BLGSP eb6e891a-b8ab-4261-808a-d543d1dc07d7 e2393e0e-5506-4017-8960-6df5d3248e0e Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts fac1a77d-1b58-44ed-80dc-3d407dd13018 b9f32a548b50c19990b865b357aec80c 4227078 +fb2bb7d8-da38-46a7-80a1-5e7ac1cf95c7 649824de-2c58-49ed-97d0-f75da2378cf7.rna_seq.genomic.gdc_realn.bam ffe5f58b9bfe27d2591fef8199491182 16692556833 CGCI-BLGSP d0f47e8d-df1e-48e6-a127-6ffdcf7be450 f32def78-5bd9-4514-b517-3a06086ffc7c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 5a891052-daa1-4164-9a1a-71d7b46d64e7 31a775784a9574d82165af1c2078d0f7 18374041148 +1f67c73b-a14a-4629-88fc-5c758ae44eac 19c8bf8e-a115-4747-96b5-351cd3a78de7.rna_seq.genomic.gdc_realn.bam 4f17e31a46492bafd546235bdd2c953e 11461509397 CGCI-BLGSP a789950d-3cbe-4de1-bba3-00ee3e0e7a46 abe0a243-4500-4444-b31d-b23a28954c85 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 78b91a9a-11a4-4126-8eac-ae81d1a25603 d9cfea22000b494dc19a84a4dd0ead44 12424626600 +239ed70a-3c09-41af-b954-ed20589e8205 e6095c1d-7f6b-40f9-9196-0e5295ab449e.rna_seq.star_gene_counts.tsv.gz ce4470371b618d41eed7a43ac81d7760 394727 CGCI-BLGSP 2d3e842c-e596-4e30-ad13-525b0cff690f 69862ab4-2a6f-4d39-bbd1-3170f16d32ce Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1ccd1d0a-0761-4f72-ab99-c6ec43251228 3bfdfd140d4c4f82525938537bbae156 4216293 +3559e3aa-fe73-4021-9ae7-ce77d849abee adefcf80-c82b-4853-a26a-858212f12984.rna_seq.transcriptome.gdc_realn.bam 75345d2a915b65e3514f94b1fff105f8 13920154130 CGCI-BLGSP 359381c1-34bb-4b8a-ba43-f06bce194341 e52905dc-0faf-4828-a893-945d32d46805 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 19694caa-70a8-4f64-b186-28606cc3ae20 63546dbbc9b03c1c53509d82ce8fe6a6 16601651776 +3c16c6bb-0821-492a-acfa-a1d1792b96d8 9a0ac5b0-6744-474f-947b-77c666ed3d73.rna_seq.chimeric.gdc_realn.bam fe70a5aca14f0add70d0734f7f85592e 159564352 CGCI-BLGSP ceeec59b-7f6a-4769-b75b-41405c41e177 8967be7c-33f0-4127-96af-4ed4cd98303e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b8696980-f504-4c47-b552-ea85211bd247 98e4c864fd70563fd4fd43ee4296535f 165540866 +030999fa-c3d3-43bf-a03f-75df8c619127 d739d611-9b08-4d27-9902-0e82f2a2bc1b.rna_seq.transcriptome.gdc_realn.bam 36029a6d9120364e5d6050a7e2f78242 8120055102 CGCI-BLGSP ad1b4563-3d9e-4d1d-993f-28e0e35c750b 88e15ea7-42d5-4858-b13d-40f4ed99fbc0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 31fc6695-f471-4d51-9dbc-3269bc2a1382 03b26bad288d7ac7a45ed1a650c65747 9818822455 +6a1fbbe8-12ab-488e-9747-73c02a471953 75c618c4-1d48-45d8-b932-39f69e19cb85.rna_seq.genomic.gdc_realn.bam 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12405536511 +a406df3c-0580-4277-9cd9-c9886455cf8e 2492d0fb-9840-4ba0-99ee-98598255e4de.rna_seq.chimeric.gdc_realn.bam 44348d95a50793e84b7d3ed7524eb004 107022174 CGCI-BLGSP c7494967-0585-4929-a4e1-4f0d76c406c6 7ed0f0ba-c6dd-47d2-8ddc-f9e6fef17e1f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 09a73ff3-959e-409f-813c-d9e6a5348514 476e11a93362684c6ee61e9ae762adba 112327783 +df03279f-7f58-4ef6-ae33-9160680e4588 7ce4c73f-5fbd-4fc6-8cd8-ae0919c041ab.arriba.rna_fusion.bedpe 7ca59cf411ca73870a639f9dbe880230 5590 CGCI-BLGSP 4a460794-5919-4e36-aa5b-67eb318884bb 86029bcf-efc2-4701-8834-2a635997a292 Structural Variation Transcript Fusion RNA-Seq Arriba 829f12ea-472a-4c2d-add0-550cc2f80d68 0b9ce11dd95126cd960a465ff9f8ed07 4048 +96d9b328-348b-4af1-a49f-b355966f4535 36c429ce-ff62-444d-b5ac-c35dd9358437.rna_seq.star_gene_counts.tsv.gz 3f28cdf6256de1b499960beb88fecdd3 414115 CGCI-BLGSP a349d361-885a-427d-967e-cacf830bc829 d5b61e46-dcc8-4bb8-af82-28b0837e6200 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 3b02bfe4-9018-4eb9-a357-591b20581ceb dcf672fc5da77a0064e17edb3e909ae3 4234929 +6aa23568-4da3-4a72-ba4b-40b1f6768d77 c6cefa7e-c66c-413d-834c-2f164fd3b48c.rna_seq.transcriptome.gdc_realn.bam 263e88840955182e55f22746f32207f2 11485506048 CGCI-BLGSP e8a5b8dd-cf75-4d13-88d6-018af64a0fbb 30d2ec35-3db2-489f-b270-eca924d552c0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b0aed9eb-d542-4338-9417-cfa80b7be311 c1188ebabeb5ec20fbd1093ff4f31e75 13629896983 +29892d02-ab23-41cd-93e7-21a00965aa41 f676f0f5-1792-4aea-bd0b-05d476607607.rna_seq.star_splice_junctions.tsv.gz 00d7d996743e88306f01adc74e1491aa 3138765 CGCI-BLGSP d04504c8-766f-4829-9d11-cc32f3052f63 5cb27d44-2c43-40c8-a294-f952ba67f0ad Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 2a73796e-af94-41df-a40f-4fe35235636d c259aa86fdeb42d3c68a3c208a11d325 3432078 +797ad9b4-52b6-4c88-9143-79cbba407438 8923e365-26e6-4459-a012-9e76a2fb10dd.rna_seq.star_gene_counts.tsv.gz a14de2c5b9dce39978dc5c515ed5956d 410136 CGCI-BLGSP d691aab7-cdcd-4c0a-8294-91e29f97c00f 9eb3f03a-d123-4eb9-bfad-d4a1e2d07035 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts cb07fc44-d39f-4e4d-8f24-a4cabb78fddd 5b5fa2a87801565da05591b7f84ae519 4234001 +a0727d6a-8ec7-4789-a791-a091e1225d30 a0bdd5e0-c764-4ce6-ac95-9f1e81543abc.wgs.ASCAT.gene_level.copy_number_variation.tsv 938f6cfb07eafdaae328bf31c59e2ef4 3482758 CGCI-BLGSP 2ef3e472-4a43-48a5-917f-c336194c0373 df141029-7ae6-4228-b918-e607beac87a2,2b8e2a22-36b9-4c5c-b060-cd5024561804 Copy Number Variation Gene Level Copy Number WGS AscatNGS 5935de52-353f-45d3-8f18-d97788c7a010 9a09e315ca51f6f129ad5ca21b843eb0 3442754 +342c893b-c266-4df7-a06d-6500b39510a0 c28e898d-d866-4b94-aadc-1c5a791a95a5.rna_seq.star_splice_junctions.tsv.gz d16fb9c01f1171398a494c531a550b13 3121860 CGCI-BLGSP 213e9f9d-7340-460c-93a3-edd559b42009 e587bb35-4d34-4a5c-b11b-b1d6992b1482 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 650f84d7-bd05-4989-8bc3-1365b6038041 6e3551e88f2a24e09bcf4fe9c2c495bd 3194549 +5a1f0a9c-13da-4493-9078-94d77378a83e 0283f768-3a40-4203-86f8-4287f9003c94.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 58576f61-cf0d-4542-9f88-257ee412af7f cad655ea-5320-483f-b35f-a28d64d9210b Structural Variation Transcript Fusion RNA-Seq STAR-Fusion d134dea1-9869-44e4-8bb2-8649bb54625c 6e5690795ff424264402ab9d2661b62b 229 +90b31569-b96c-44fd-b4ca-13004b0f7151 69a39039-1f2f-4da5-af55-c2ff362b190c.rna_seq.chimeric.gdc_realn.bam 81b48d382d9623a5e05b33ed8acdde96 137790910 CGCI-BLGSP 4dc94896-aed1-48af-b1f0-6ddbf91a8cd2 891ce72a-f858-4bfd-93ae-d034b38389d8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e591b690-ae76-4271-b927-cd80ddcb0965 4c729a81f29ce6e108c00dcd700e6c07 143552343 +a158c932-8537-42bf-98f3-80aed058656f b3d16f53-5681-49a1-9ba0-1c5ad6d3b301.rna_seq.star_splice_junctions.tsv.gz d8e58e8f28175d1f37bf28c3b56ebaa7 3122566 CGCI-BLGSP af918a1b-56ac-4ebc-af60-b0823023c185 aac8c165-4613-4ff1-a6a0-48229c398010 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5dd0d4c3-e3ac-4369-ad73-6921ba1602a8 0e4892c3c90b616bae71adbe2641c595 3252758 +773bf751-8226-425d-af1a-6c442d729f6a 7c19689e-9f82-4cd3-9989-ff5b827df388.star_fusion.rna_fusion.bedpe ee8f81655b5ffdee6175352a9d151fdc 1283 CGCI-BLGSP ad1b4563-3d9e-4d1d-993f-28e0e35c750b 88e15ea7-42d5-4858-b13d-40f4ed99fbc0 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion efe67b27-9a7c-4ec5-9d3b-0e147e2d46bc 6e5690795ff424264402ab9d2661b62b 229 +72d1d4d5-c4e3-49d0-aa7e-5479247d6463 b02c9adc-d35b-4b5d-a0f7-c652a10ecac2.wgs.BRASS.raw_structural_variation.bedpe.gz 35fb9c53ab6c90a5344e6bb79e1807d1 11718 CGCI-BLGSP f4a0bef2-c397-4149-830f-8d5f62e1b5e8 15f97967-a3f9-41fe-8641-f351b96e31e1,f10fbda6-ffaa-4ed2-8ab7-c2dde2d38483 Somatic Structural Variation Structural Rearrangement WGS BRASS e2278506-0ded-4ffa-bf98-35d612a7d548 74fb5219019d368324d3769e0b0e7f94 42889 +6ea26bee-ea01-4845-8083-ad4296e8b831 16e638e5-d192-44df-ae58-6936b40406b8.rna_seq.star_gene_counts.tsv.gz c11c4b0a9afe86c9e8c74ca862636034 408100 CGCI-BLGSP 486fa825-324f-4011-b43c-f6454702e0d6 01a6744f-6d5d-47ab-9455-30327866164f Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1d607266-d536-4ef0-908a-9b709ab60767 93b331e29b87817b2706061e87bd93bf 4230614 +3e8ade81-e021-4afa-9558-21f163d5d6f2 8ea1a4a5-b911-419c-8c45-56ceba409b28.star_fusion.rna_fusion.bedpe 20904437c20945b5585c6bb8f3a3ecb5 4139 CGCI-BLGSP 486fa825-324f-4011-b43c-f6454702e0d6 01a6744f-6d5d-47ab-9455-30327866164f Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 5a8a0efe-b52e-4aca-bcb1-aab4eedc719b 6ab9b2c48360805f00d652d51c070b96 1525 +cfbe7d89-f348-4a85-8d76-8dbd7fa3ef00 2e9d4c25-bc24-4ca5-9200-3cd440a1123f.arriba.rna_fusion.bedpe 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+c59cdbda-cce5-47a8-b5ab-777d3bfcede7 32afa270-2c49-4634-be92-d215ffb6fc59.rna_seq.star_gene_counts.tsv.gz b87b1a87c8b610f8ed5668b8d6efcf4d 401936 CGCI-BLGSP 39dce88d-112c-4a3d-b2d2-11e0616594d8 46a48950-f657-4a52-8b40-436aebc4defc Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1947fcfa-504e-40b9-a11f-bf5ad65a3521 3c2b4969d48f9999f693229e84c4bfae 4226711 +cfacefd4-2532-4ec4-98d0-fe213817a5c5 551d6887-ca61-4365-8411-2deb635e9a81.rna_seq.star_splice_junctions.tsv.gz 02b37a8df75910d9a5d8392e4df14261 3844697 CGCI-BLGSP d991215a-fd4f-434d-a17a-cf106aa72edf 9fab0517-1d81-4178-a09a-a3d7f8f1f0e9 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 93983aab-ac74-4d1e-b3d8-0df409c47e68 06153d2b8bbb59e1dff87c9aa09888f4 3946315 +483963ce-31c2-47b4-bc33-480b712e4481 36c429ce-ff62-444d-b5ac-c35dd9358437.rna_seq.genomic.gdc_realn.bam 052d2131255817a476116f0f196ab5cb 14183118781 CGCI-BLGSP a349d361-885a-427d-967e-cacf830bc829 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Aligned Reads RNA-Seq STAR 2-Pass Genome 3224556c-1dfe-4970-aa50-e0f3b843442a 14a06f8d66deaa934398c26bb8a89f39 13687782303 +c7330a37-197d-45db-b213-2c426979a1b0 ab2ddd77-9ca4-4e8a-95c9-fad532661172.rna_seq.transcriptome.gdc_realn.bam 3a317b7281dc08ec1cd06e42b2c6689c 11478784938 CGCI-BLGSP 49b5173b-fc55-4ae5-8b72-964f2173395d cc40c6e2-8ffb-4b3c-9da5-2d9edb7eef62 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b7b0a4fc-7587-4fce-a948-5a160b7e79f2 405bed294e3c3f74ed0c39e2ed8686b8 13917969542 +0a8baa20-4e29-4772-a0b4-0f1de0c169c8 56c2f382-5952-4426-bdd6-79b0980b05c4.rna_seq.star_gene_counts.tsv.gz f89cfdc951e896e42b7e888c8c28261e 397207 CGCI-BLGSP 8ef78bfd-48cd-433b-a3ff-b8c4e755406e 92fc379f-38c8-4ad6-ba50-9de64d555ba8 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts cce1821e-f1bb-4296-9d20-5db1af0df5aa ad486c01058104e32710a70107547c6c 4216848 +3a65b315-0830-44a0-a9ec-f87a0dc56002 34ea397b-3647-4973-a867-1f7cef4d3955.arriba.rna_fusion.bedpe 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Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 96424f1a-5ff7-4384-99f9-febcaad82068 c1d727f7279d6b0824c66f7b6ddf0925 13532734727 +a9248779-ef13-4506-9443-f957a869ee0b 38eac1d6-a0ce-4b3b-8acb-60ac51cfca9a.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 2d3e842c-e596-4e30-ad13-525b0cff690f 69862ab4-2a6f-4d39-bbd1-3170f16d32ce Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 9ed78a73-2bcd-45e4-b1a3-68856a249ba9 6e5690795ff424264402ab9d2661b62b 229 +7c2b90db-cd58-4496-b877-edd897861ef7 b3d16f53-5681-49a1-9ba0-1c5ad6d3b301.rna_seq.genomic.gdc_realn.bam 43b8bc0a46c84068bbe2d98cf5254f56 14087095777 CGCI-BLGSP af918a1b-56ac-4ebc-af60-b0823023c185 aac8c165-4613-4ff1-a6a0-48229c398010 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome e801583e-fed2-4c89-9068-3cf215985903 dfcfef090cd5420203ff6492c5f0dfb8 16026836350 +15b645a6-b4ff-40a0-a38c-7579e534c1a2 e2c2f95c-3f1d-4fd6-8faa-9f9d73054eff.rna_seq.transcriptome.gdc_realn.bam 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Quantification RNA-Seq STAR - Counts 43326da6-f908-4b44-a3c6-e75478d8ba5f 4acd6e2c00d2d6e642199ad33a50b29d 3782833 +2a27e765-f8f3-4ee0-94ed-14d70ddf58e4 d23ab351-5c1d-4db9-beac-249d96519e19.rna_seq.star_splice_junctions.tsv.gz 6e0fa95942301575d4cad553e33ebe3a 3270608 CGCI-BLGSP 2a587474-c6c3-4322-b1ad-a11f2d205bb4 79288db5-aa59-4656-9955-d59272d4f7d7 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f0ec4e36-aa80-4844-99d1-537f9606a1e5 93b7e70baab79b7587bcd930625e082d 3371082 +154524c1-ed74-45d3-8491-1d986be3198e c6cefa7e-c66c-413d-834c-2f164fd3b48c.rna_seq.star_gene_counts.tsv.gz 5843511cc4db9d5f0c068cf0ec2b6d4b 394392 CGCI-BLGSP e8a5b8dd-cf75-4d13-88d6-018af64a0fbb 30d2ec35-3db2-489f-b270-eca924d552c0 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7754ce0b-5fab-40b1-ac2c-d8c8269bf9a0 e5b68dca8f4ff773ee472c1e54ea93c2 4214019 +ffaa4a05-8513-446c-8551-c4c574fd8401 f4d0d51a-946f-4454-936f-6286b69a7b61.arriba.rna_fusion.bedpe 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349e62b27986ce8a6335d9e12f974b19 14507233262 +cf8ddd06-966f-4b70-8f36-6954acd538d7 b8e3a265-dfe6-4971-bab3-41a0bf3aaae6.arriba.rna_fusion.bedpe f3d6951fd532cbf24718cea5b3fd0ac2 7986 CGCI-BLGSP f9ffbc74-e1c1-4579-8465-cb2b96a1200a 4f8933d2-6f2b-4ec5-9415-c647d2c56193 Structural Variation Transcript Fusion RNA-Seq Arriba e04484b3-7fea-4c01-9edf-2c98dd5e4ce9 461b5b4b6530a4a0921f81eecd5d670d 7307 +40a17ce2-b275-42f5-8a9b-76799b704c51 9a0ac5b0-6744-474f-947b-77c666ed3d73.rna_seq.transcriptome.gdc_realn.bam 134d0161e8e78d3b2577074a717ea153 12329029265 CGCI-BLGSP ceeec59b-7f6a-4769-b75b-41405c41e177 8967be7c-33f0-4127-96af-4ed4cd98303e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 550d8d1c-f882-473e-98b6-55ad093b6d40 ac373c24c7333925fd2f8dc937964ca7 14591969233 +a0c742d8-d244-4ab9-a124-4f2cfe4273b4 ed294bad-682e-48e7-9329-60c202332400.star_fusion.rna_fusion.bedpe 43869209d67b8a2772b9df73b5976ca7 741 CGCI-BLGSP 56105a23-4ced-4511-aa90-b956db97b881 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Splice Junction Quantification RNA-Seq STAR - Counts 0e2b42df-9bc3-424b-bcbd-d50cd8ed6294 7239609dfb4220683cb0ae26f02f0b4b 3034378 +36f34b7d-845a-4c4d-8e08-3b11de2e363f 379409bd-a918-4479-8635-9aee6bd8e4e1.rna_seq.star_gene_counts.tsv.gz 04f680c131e61335fc8df9937493cd75 404940 CGCI-BLGSP 90e9183f-7210-4922-a653-21c86e488887 a244ceda-46a6-4461-8506-778e4ec75e2b Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts e730269f-3b4f-42fe-b2e0-aa0c68243411 679b5200700b17ec0a593d579b1a09fc 4226229 +91a53670-981b-4c96-b933-f92cbe292711 2a3f6588-b301-4c8f-955c-c4607000b36a.rna_seq.star_splice_junctions.tsv.gz a2fbd05a558c9575950313cc2333a94f 3141861 CGCI-BLGSP 48823727-d7d5-4efa-b374-17e3cfffad91 79528e46-4e76-449c-a35c-25a97ae31f8e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 3827bed9-a79d-498e-9887-27ab2c3ce593 1fbf53a776f0482adb15b24849d35ee6 3222781 +373fec34-b280-4e5d-b2a7-e29ec7ce9367 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Junction Quantification RNA-Seq STAR - Counts 00a58d13-d7b1-4260-80b1-6af957ad21db 17fe10b685dc827ee8a6d266a60746b8 3194467 +7f116c0f-2dd0-4207-999e-ea0ce2a7866a 8e3ee77a-c4a8-4160-bafd-effff20b945d.rna_seq.star_splice_junctions.tsv.gz 9735f4a1e350d7c08fdced19641dab32 3306457 CGCI-BLGSP 89335258-7991-4e19-87e2-60bf747d89bd fe44714d-e304-417d-bad6-acc48e127bd8 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts bea0e433-8187-48c3-b40a-93314f4a1e3f f06356ce54be97b73797b7b81a50bff8 3414303 +aef32765-dd58-44ae-b505-6234417696b5 6adf5986-0f2b-4942-8403-e9fcb0a47677.wgs.BRASS.raw_structural_variation.bedpe.gz 746ac7f028c93ac2574b6a5f36b1c1b7 9919 CGCI-BLGSP 60acb146-43b3-44a3-9791-79284dae285e 85585007-9bce-4a8d-bd9e-ea0aa278439e,c44d913b-0c32-49b0-9f86-ce77352c5593 Somatic Structural Variation Structural Rearrangement WGS BRASS 776ea20b-2cc1-4748-86c9-3b3dd7d7b9e0 12365e97f79b28012df25bef7eee5bb1 33319 +c907b8d7-664c-481a-8a55-54c037e41a86 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RNA-Seq Arriba 5bacfca3-a358-4b0c-88ae-32123bc1b4e8 d7aa8dbea4b0fe689a67a067ac1c2281 6704 +e248b647-cb73-4768-91c6-13933b1369dc de46c011-295e-41cc-b396-38a8b8d5e0a0.wgs.ASCAT.gene_level.copy_number_variation.tsv 3f4d240cbbea50da81727ff53796e27d 3481162 CGCI-BLGSP 2721630e-8b64-4e64-8177-49f0fa84cfeb 81816fdf-1593-45b8-b17b-b4b77d5c21cc,610123a7-2848-452a-833a-74dc067951e9 Copy Number Variation Gene Level Copy Number WGS AscatNGS c1853b85-507c-4ada-88fa-53e6d3da05cd 776ad2150ce747531d8f50f6849eccca 3441239 +2a68b8b8-2538-403a-bd92-c6ce9a369a0a eaa16509-a7ca-4b22-82fc-c66de634ac9e.star_fusion.rna_fusion.bedpe d1d4dbea93f6b7e1eef64fc2d04bf90b 3730 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 2ee24626-72ed-4070-b034-92f88e7659c3 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 7b0aa110-9e16-4279-847e-4f604a99f912 514bdb3e2500974d6d1841a34a97214e 655 +aea0df98-b2f9-41d4-9f5c-ab05c8a53acc 6bd72fbf-f317-479a-935a-9260a2420e58.wgs.BRASS.raw_structural_variation.bedpe.gz 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3adda5c5-3a4a-4f50-b777-bdc00af33845 0caedcfb63a0ed55dee7cb35207e7386 156258039 +ed291cdd-505e-4dc0-bd86-2598ad912f68 d5d42073-bfc6-4f5e-b350-180bb27a308f.rna_seq.star_gene_counts.tsv.gz 83c4d1139597af31bf4e9ceb02d44278 405806 CGCI-BLGSP 7c0891c3-7ddd-460b-a8e7-b33a63844ed1 14ddc614-f974-40ae-99d7-5827f7a6ae6c Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts f72a491d-5a81-432f-8b43-71f22572915f 78ce1befa1912430d366519973fe64f6 4226505 +07e3462e-0c4a-4760-be56-a0b36dc97d0b a56acb60-2e34-4f4f-b37f-527fc3c682ad.star_fusion.rna_fusion.bedpe b98e48b22023b9b5d3cdf89923ec02b2 1103 CGCI-BLGSP be578313-e34c-4f26-aba6-4dc05dfd6f4d 759526cb-c73d-4139-9d42-606d85fa7423 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 1af033a6-e4f2-4aea-9e23-2de22df9b22b a982b6295f1438c2078ddd00b47e54ac 443 +7be4cb5e-0513-4660-be24-2e1c48b5ed1b 60d15789-cbe6-4e53-bd12-bb262de18bc9.rna_seq.star_gene_counts.tsv.gz 00fca87b0ff22e6f4c5cdaf99f1abb07 404011 CGCI-BLGSP 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15a04b3a-88bb-4ebc-982a-939dfac3561b.wgs.ASCAT.gene_level.copy_number_variation.tsv cefa93d9967f578176f3a0f088f560c2 3481168 CGCI-BLGSP 8ef78bfd-48cd-433b-a3ff-b8c4e755406e 54371e6f-c22e-4a68-80e5-5eb757a978e1,f8c8405c-0c51-4f71-8687-2f9f90fe3df7 Copy Number Variation Gene Level Copy Number WGS AscatNGS 86174105-6495-4b49-a4d6-cbac6b2264bc 6917bc54efc389afc803f8f0edb83e0f 3441245 +8ff1ccaf-f24f-4539-a77d-f64b0420a41a 5a7138dc-4366-4b32-9d42-9f2bc9fc9a35.wgs.BRASS.raw_structural_variation.bedpe.gz aad70316220770403be192797de159fe 11221 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 a3ce67ad-e4f9-411d-949c-88fb3df3f7c9,8d9f8491-048b-4c55-9d34-fa7124a17ac0 Somatic Structural Variation Structural Rearrangement WGS BRASS b407da4c-2efb-4495-a3e9-bf20d72cd6ea 10902adae04046318de73ef26580840b 38436 +516f4fbf-894c-41f4-bd33-ab57627cf075 98494a90-2563-40e4-b9f1-415e1f03cd1e.arriba.rna_fusion.bedpe 9e91a3c39628303b2b72a242938731cd 990 CGCI-BLGSP 39dce88d-112c-4a3d-b2d2-11e0616594d8 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2-Pass Genome 6bd69da2-d1f2-44b0-ac42-ee0f02b60154 789574f71b251887d9d191d8bca6ba76 17003484876 +5a9c6eb7-22b4-4dcc-9e62-80f8c12d32e0 75c618c4-1d48-45d8-b932-39f69e19cb85.rna_seq.transcriptome.gdc_realn.bam 6924aa78d7a0f72246e1d8e8dc83fdbf 8447910636 CGCI-BLGSP 3703e3e9-1f3a-445e-9538-d924014c822d 2e9fa249-9648-4b81-9894-1caa574d6041 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 7fb57c81-d1bc-4cbb-9ae6-f8170495716f 78eb2ff5438ff84748d7fce17ebdd6d5 10341398248 +1c5975ee-c11d-4832-a852-e1ce866ec675 c8143bd9-0b2e-4ff1-a9da-f0ff1f3ff97c.rna_seq.genomic.gdc_realn.bam c1376dca6f4f433a5f722e7f4c1ed448 13550112216 CGCI-BLGSP f9ffbc74-e1c1-4579-8465-cb2b96a1200a 4f8933d2-6f2b-4ec5-9415-c647d2c56193 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome cf090ac2-d506-46b7-9bd7-20c93471add4 277015f0e0ef68aabac6c99e3f39df18 14958597543 +d50d17eb-44ab-4d4f-b066-774972ec42c7 8e3ee77a-c4a8-4160-bafd-effff20b945d.rna_seq.transcriptome.gdc_realn.bam 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Counts fb14b292-0057-4edc-8aa3-c536d52beaf6 502e9c89b0184998705c45b69fe66234 4228020 +316b6c7d-0379-4b01-b976-d6aa031d4bfc c6cefa7e-c66c-413d-834c-2f164fd3b48c.rna_seq.star_splice_junctions.tsv.gz 1b50726a290b667f195e22649196c1b8 2800284 CGCI-BLGSP e8a5b8dd-cf75-4d13-88d6-018af64a0fbb 30d2ec35-3db2-489f-b270-eca924d552c0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 602c5533-0f86-448d-ad69-13ac2ea01ba2 1d133e90ba1bee5e3ed1d69f2604576c 2862779 +aa6b8186-0669-4480-9130-8e55cb892eaa 379409bd-a918-4479-8635-9aee6bd8e4e1.rna_seq.genomic.gdc_realn.bam 934e0f8dfc88eebb23d72ee9ddb89281 12927729157 CGCI-BLGSP 90e9183f-7210-4922-a653-21c86e488887 a244ceda-46a6-4461-8506-778e4ec75e2b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 241c6412-ece7-4da8-b1e6-bbe60ead533c 9bc2d241413652122b4d4ac46cd9787b 14306394744 +210184c1-2717-4173-b5ac-6f906e424c9b d5ba9ec7-93b2-4627-82ff-377fa62349d1.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 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Aligned Reads RNA-Seq STAR 2-Pass Chimeric 2af73c68-8cc7-4c0c-bf41-a7f22fbfebf1 9073d4aaa795b0de084819033a2f3ac8 179769209 +72e089bd-81fe-4a43-a716-8a88f07e686b 6e64b058-2a75-4668-a722-2e3abf3acd42.rna_seq.star_splice_junctions.tsv.gz bb227fb29dd9b02f486bbffd8b9b7fad 2707613 CGCI-BLGSP 136a1fde-ecc8-43fe-b2f1-f3eee0bdc23f e9ea3a04-95c5-44b0-8866-c9e2f62a66b9 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 9bed744e-86ef-4666-b28d-a245801314c0 26edb56a928eaa9075548ca1ef70a2e9 2769394 +990f931d-1b1c-4dd8-8376-fe7dc4d72c13 82edd1c7-22c8-4f9d-8ef6-334390bdfa78.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 8a678613-f77d-45d1-9c13-8595e55e8f27 049aec5f-5534-4eea-9cf1-6a11906088a8 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 866a28d3-7f36-42ec-8f44-64ad746ef5c4 6e5690795ff424264402ab9d2661b62b 229 +e7a83a28-c698-417d-923f-1adc0252f1d2 d1208de7-658f-4bfc-b141-5fa4e08ef2f2.wgs.BRASS.raw_structural_variation.bedpe.gz 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Transcriptome a8628a76-2909-4945-b158-8ce86ef3fbdd b126f589df043d29224c409f4dd837af 12411072386 +cc69dd55-853c-493c-84f2-5014a405aae4 693f76b5-6d30-4bbf-85a4-f9e6f43d5f70.rna_seq.chimeric.gdc_realn.bam 5ac7284a9557b95668e1270a48ea8810 131606924 CGCI-BLGSP f90e6333-f59e-4f6b-b7f9-17ba10e4a600 f9627688-8e25-4ede-bde0-8da01ed7528a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 03961ccd-0d79-441c-8df3-2546c2a4d965 c1387a6daccbf6639c3de2ffecda393a 138214389 +8cf922af-49e8-43c1-a612-1ce1e02a868c 39bdbc5f-295e-42ef-924e-3c493c6e71be.rna_seq.chimeric.gdc_realn.bam be0c29f7eb2827d1a78aeee7f645ea65 87487722 CGCI-BLGSP 98540fd8-1bb7-413c-b2d8-857e6e25309f 15010d6f-c931-4fe2-be6c-e11b632f8f93 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 6699bd2b-4996-49aa-92f6-ed477888af80 356b82d4ef6461226753737abaa9b1e2 91954697 +de5ef0f8-898e-4a1a-9d99-b86e0ff74e8d 85268986-e992-42ef-9588-3e218127997f.star_fusion.rna_fusion.bedpe 21138795edbda6dcaae5ec498d892a7e 1589 CGCI-BLGSP 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+112a4802-1b79-4071-a3e8-5514b9d3837b f9ff924b-da72-4ab8-ba13-90429719f28f.arriba.rna_fusion.bedpe 148b7112bb5a9b673e12caf9dcf6ddce 5778 CGCI-BLGSP 136a1fde-ecc8-43fe-b2f1-f3eee0bdc23f e9ea3a04-95c5-44b0-8866-c9e2f62a66b9 Structural Variation Transcript Fusion RNA-Seq Arriba c1c8ea6a-16a2-4986-a57b-4cf82ddf1723 ededbe94382fbd80027e0adb3d13f486 5039 +cd793dc9-f21a-40d8-80c6-3d89b41ff6d5 6e64b058-2a75-4668-a722-2e3abf3acd42.rna_seq.transcriptome.gdc_realn.bam 4261b47b7da28f1bec2874375e70c9c8 10437467917 CGCI-BLGSP 136a1fde-ecc8-43fe-b2f1-f3eee0bdc23f e9ea3a04-95c5-44b0-8866-c9e2f62a66b9 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome c89e3415-7b0b-4727-a24d-fe9419565348 aae602bc96851a2f813c2099e88bbe01 12347323865 +65e1a07e-abe9-4332-8283-83592029668c c3b70beb-83e0-4400-982e-e9ee03b3ac0a.rna_seq.star_splice_junctions.tsv.gz af3e4b682152f3cb00d5d9a58942d265 3032313 CGCI-BLGSP 56105a23-4ced-4511-aa90-b956db97b881 2e684c80-da6f-4c36-8fb4-205a11a9004b Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 431fca6c-9123-4a1c-80c4-c546a2bd9af2 737448d5adf3036ef6b5e4218430775b 3107682 +e5a94f6a-6698-48d7-9f39-cbc5a1be6424 39bdbc5f-295e-42ef-924e-3c493c6e71be.rna_seq.transcriptome.gdc_realn.bam 0309e0966b930a0461648ad1b63bf3dc 11658087738 CGCI-BLGSP 98540fd8-1bb7-413c-b2d8-857e6e25309f 15010d6f-c931-4fe2-be6c-e11b632f8f93 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome bc905696-6f31-43c0-8575-4517c7b19982 fee9f5015eb9ddb619d4638a60561ab7 13965210820 +300d60a8-4362-46ef-a356-2a3dbfe4c320 6fabf35c-4a22-4a6f-bf87-4ab9d67af24b.wgs.BRASS.raw_structural_variation.bedpe.gz b43520edc118f3b77f64c2e75e327828 14087 CGCI-BLGSP 4dc94896-aed1-48af-b1f0-6ddbf91a8cd2 ea982aaf-3b40-424a-9d07-c0369a67d0c6,6a95177f-747d-4431-99d8-82830d4bf266 Somatic Structural Variation Structural Rearrangement WGS BRASS 8e9432fc-caed-4371-839c-0f350696ea30 fc69ccef37e0d1a700a7b1eb95c790b6 49657 +b4a4f528-0fbb-4d54-8f46-96b3888d57fa 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Transcriptome 729a631c-1e33-495e-b426-fdd462e6628c ec1d716561637fcaa58ba6c14a884dc4 11712322667 +2fdd2142-91ec-4f53-8fb7-6b588cbef0fe 125a69d6-5062-415a-8a51-8ba983a0bba2.rna_seq.star_gene_counts.tsv.gz 3eed8a45d52ca5d2898d080afa8084fd 400789 CGCI-BLGSP 75a86324-6a4e-4921-bc3e-375b848f3d34 8c6dbbba-1f3c-48b4-b48c-a3e46286f60f Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7ab0399c-41c4-4a0b-8b2e-dad4fe2406a1 c13afd08322aa246ba0d444630951436 4221087 +4faefed5-1f92-4a73-b95d-e09ffa6dd3ba 83500f05-8f50-4d29-88cd-a739d0bf74fe.star_fusion.rna_fusion.bedpe 19eb94ad72d001cfe0fbd50052ccbb43 458 CGCI-BLGSP a789950d-3cbe-4de1-bba3-00ee3e0e7a46 abe0a243-4500-4444-b31d-b23a28954c85 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion d7bea40d-5f90-445f-92fe-74fabba2f5e2 6e5690795ff424264402ab9d2661b62b 229 +15445ab0-4ce4-4a0a-915e-0e3a72e75706 5e74ef77-948d-4ecc-a1ba-07010631daeb.rna_seq.star_splice_junctions.tsv.gz 8fe7d82186f3a992a5184149f9332d74 2953162 CGCI-BLGSP a7dfd3c9-4b94-4802-97c6-a096b276aeaf ac110d72-7f92-4581-a859-91e34e160825 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 08061de9-d61e-4658-8cd2-e710bc97e2d4 38194af0e498452bf8ce81141b729d23 3009424 +b2dada91-7749-4881-ad36-9c841763dab9 3d6c3cac-ba03-4e9f-b7e4-d24596bf34e5.rna_seq.star_gene_counts.tsv.gz 947da8bb580d7292df575695422ae50c 404741 CGCI-BLGSP 69cf7ff6-fcb3-4177-82a0-5a589073e4e6 60ae79dc-769c-4c0b-a0aa-3fa99176c596 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts f28e0ab4-0564-475f-8abc-763476dae133 f73158c25f5afe3c439ba99d7231526a 4223533 +3fab6838-fe24-4733-ac95-4698860698a4 f940cfa8-4cea-41b1-942e-ab3b462cc370.rna_seq.genomic.gdc_realn.bam 76ab20057095286c5078e3c8a9f96e70 11644401859 CGCI-BLGSP c2010e3f-26f4-408f-95f2-9c06a43bee88 662c9e01-2a4f-4431-83b1-0dfb3c21b335 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 48350b07-d090-4217-ac48-57107aabebfe b8b4cacf45100d3b4842242994a88e94 12616520323 +bd94aae2-0e9e-41cd-9389-51d957ec26cc 329e077b-3aa5-44f5-a9c7-33ed4af9bac8.rna_seq.star_splice_junctions.tsv.gz 73515c50c872b19c809d872bb0e3802d 3240545 CGCI-BLGSP 2721630e-8b64-4e64-8177-49f0fa84cfeb dcabed3f-05ec-43a7-b4e3-eb6ce820e87e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 9b969a03-6437-4224-9cb7-67843f3890cb 597e9cddceee7e956b0f27a3f05943a1 3320641 +2ae335db-3cfe-4252-81eb-441ce91fb0dc 60d15789-cbe6-4e53-bd12-bb262de18bc9.rna_seq.genomic.gdc_realn.bam 65582223e637a35f1f4f3895399bb76d 15505045122 CGCI-BLGSP 1a81e2c4-b637-4028-ab28-4c64bc8bab76 9871641f-0dd2-4358-88d0-5ecd57a61665 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 40ac106e-df7e-4cc5-b0be-5b9a29286cd4 0d3e69aad73f5ff213eb6fa31ee92e26 17009434421 +6cbf4f7b-7ceb-4d7c-98e8-11c52198b1e2 80bbadf6-ffac-4650-a7da-cd6f0e0915bb.rna_seq.transcriptome.gdc_realn.bam 1634826c429970a2e7b3959f09564ea3 12863753324 CGCI-BLGSP cddc3633-5aa1-4a61-87c6-4620b6ac4adc 2ffbf27b-fc7d-42bd-9ac3-d13e9b20ea71 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 6c50acd9-bde6-41ed-a929-12c8d9046e47 cd1af8812b201f2eaa96e1b8633d7a61 15638621549 +c6afa61b-8f2e-4f7c-b6d0-d0b47dd1374d cef2ff84-8d89-4368-a083-315247ef0c48.arriba.rna_fusion.bedpe 97e8a2c191aec8fd0f205ad0c0d95b27 5375 CGCI-BLGSP 60acb146-43b3-44a3-9791-79284dae285e 2defb97f-3d9d-4624-8447-5d6b9e92e7df Structural Variation Transcript Fusion RNA-Seq Arriba 0e03e682-f523-45e2-81c5-23aa9e3524bd cad507f20e23a47ab6718b720e05b78a 4886 +d839c293-7c35-4a72-b9cb-4541ad82e34f b2d68e5c-daf1-4a9a-a034-6929b7fcf542.star_fusion.rna_fusion.bedpe 6ecb1cead71bcc612d81ef62c330a258 973 CGCI-BLGSP 89989611-e08b-4731-912c-952c248a9b5e 2d3712d6-6abb-4003-bc7f-d0a3a145e1a5 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 548c5790-9949-4dba-b2bb-ecc7f736aa37 68a72acc31466cc5b6e0cd7b08fdaceb 883 +d559492e-cad0-450a-860b-c5b2405fc27e 12fbd2c8-c818-4083-aaf6-1f7e65233199.arriba.rna_fusion.bedpe 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Quantification RNA-Seq STAR - Counts a4478562-1705-426d-b069-189fcd02558e 700292a2e6e60c9f5f15072322916927 3127343 +34f6b799-0ba6-45ab-b29e-2747871588d3 4c0b87e5-ee6a-4d1b-89e3-0e4af13bea34.wgs.ASCAT.gene_level.copy_number_variation.tsv e2e913778eba45836306af6778488b96 3482761 CGCI-BLGSP 4a460794-5919-4e36-aa5b-67eb318884bb eed9662a-0633-4512-974c-006f8f5306f3,35cfe5e3-4a50-4d2f-90f4-f157f2b3e5e6 Copy Number Variation Gene Level Copy Number WGS AscatNGS 5818b72e-c290-4944-9e34-87944e312dae dd91b57d6ea7407468f6ab18d561a79e 3442757 +d57e6f2c-6dde-4733-b170-5ca98120fa8e fce5f34c-4d08-4ac9-81e9-e6cac336f02a.rna_seq.transcriptome.gdc_realn.bam ae912fe09efeccbea4fc99988f86a6b2 8121217975 CGCI-BLGSP 39ded2c0-56b5-4561-aa3f-7d417a32a131 072c72e7-7c1e-4db1-a519-3dea4a1b8fd9 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome bc98c8a2-3d0f-4635-9f2c-4e2640250830 488e7435abe56de4ec20474db2ccd6d8 9794384933 +185c4942-9e89-4eb6-8174-65c52bb715c7 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RNA-Seq Arriba d517dceb-3224-466d-b343-4864e2d93c8b dd11e902493cff6d800ebc1685e87154 6552 +b064134b-2c48-4c1e-97e7-b72f25bc1fca bc05a337-8904-4f6b-8083-c527641067d3.arriba.rna_fusion.bedpe 2d78f7c81dcaec8aa4bd118879cdce7e 2823 CGCI-BLGSP 49b5173b-fc55-4ae5-8b72-964f2173395d cc40c6e2-8ffb-4b3c-9da5-2d9edb7eef62 Structural Variation Transcript Fusion RNA-Seq Arriba 004c9290-e78b-4a15-b025-3993804f8edc e2539a275fef68068f9bae90288ea6d5 1831 +96781fde-f16f-427c-b642-adb2643dfd92 379409bd-a918-4479-8635-9aee6bd8e4e1.rna_seq.chimeric.gdc_realn.bam bdfcd57e4cc647e21ffef8d066c35e69 121119071 CGCI-BLGSP 90e9183f-7210-4922-a653-21c86e488887 a244ceda-46a6-4461-8506-778e4ec75e2b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric bf2d7600-306d-4630-81b7-2d50942264f1 c8ec63a9ccbcaeff2b0820d95fe98676 128003280 +05e87856-53d6-4815-ae45-ea23e33bdfef 0c6ccd67-2fd2-45d9-a147-d1b6eb6a0b52.wgs.ASCAT.gene_level.copy_number_variation.tsv 7f3da9cd07da18611a5d767c9354a971 3482767 CGCI-BLGSP 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a036e55142c0b3cc62c4090bc320cafa 3441227 +7c820711-1a1a-4ec8-b141-1d0f35755336 18520c8f-ff4c-4d4d-b447-33710eeca6c9.wgs.ASCAT.gene_level.copy_number_variation.tsv fb7a54ce358f3864c90546f49055f62f 3482776 CGCI-BLGSP 7dcc3723-aed6-4d2f-ad8b-afa443634139 77d24aa2-1d6b-4f17-a36a-25ba31590482,7babe5c4-59a5-4341-9661-82d3235e3c52 Copy Number Variation Gene Level Copy Number WGS AscatNGS afd4c733-ce8c-47d5-9e28-cc1b5f63ca1d 6b0923b2632c213e4fbe2d43417e9831 3442775 +6a1e90fa-fba4-438f-8d89-02ca0a8c2ec0 775df6a1-fe6e-437a-8c82-0141c4567739.arriba.rna_fusion.bedpe 63684ceb35f66c9c03caf403859d1ab2 2791 CGCI-BLGSP 2d9d88c8-d827-4bc8-88c6-75e0d0c3f988 515c31a3-2b95-4159-942c-bcb8ab8c8820 Structural Variation Transcript Fusion RNA-Seq Arriba b9579a1b-7f63-42c5-b658-9a9137943f1f c12f24a47eac328dd9967bf32899765d 2002 +eeea1c70-b4d7-47fb-bd41-6c64373afd07 e1284265-986a-400f-8025-1da6d6a37871.wgs.BRASS.raw_structural_variation.bedpe.gz a4b52c991c772c95d753204cdd8ac81a 6412 CGCI-BLGSP 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+1d126f15-0804-4699-bd40-1900c60245b7 9a0ac5b0-6744-474f-947b-77c666ed3d73.rna_seq.genomic.gdc_realn.bam 36eabcfbfb0900d5cf32b76de9139f08 11303137840 CGCI-BLGSP ceeec59b-7f6a-4769-b75b-41405c41e177 8967be7c-33f0-4127-96af-4ed4cd98303e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 8e717a81-26b7-4bbe-b219-0a501e110e0b b5beb552c046f28c4ade0a7ea6cb6919 12097002668 +e5260b24-da49-40ea-8225-91a0f5335224 29f449c8-ad7f-4376-a683-1ad75fa31709.rna_seq.star_gene_counts.tsv.gz 21483da5d1d7f16c682ca89eacc808f8 410537 CGCI-BLGSP c96f21de-3dd6-47ed-a796-6270c1817dd7 353174d3-4bd6-4e08-8234-013da78fc871 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts d21c4dbb-344e-4915-984d-9b56ba8b7daa e671fba8dea15dd9a7b7b022bf66933d 4227558 +6826c22a-0a20-4005-ae3f-92af7c0505ba 352716fd-204d-4c01-bbf1-013a667ad12a.rna_seq.chimeric.gdc_realn.bam e3a6d692b2ff916f29a43798ead46ede 72795393 CGCI-BLGSP 39f9996d-b217-4222-98ea-47c210d49e93 0c672ada-5bf8-4549-82f9-c9b8cb747aba Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 7c0ffc04-9737-463f-a6fd-09de5b9c0640 fb58ee1d73cb99c5010c71de01c5a1a6 75422310 +b7cd0c46-15f9-4b9c-8f75-64c25231ec3d 5ca3f400-4ac4-45d7-9049-4281f2a69113.rna_seq.star_splice_junctions.tsv.gz 37b6b1d5fac77782420e5d3531edfeb2 3159458 CGCI-BLGSP bd25db19-92dd-4d8e-8b07-4dba8095cfcb fffaf700-0acd-49ee-95cf-5b295772242d Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts b40f3c14-f41c-4036-9881-1b81b0f0aa40 ddd2ef9081ea7336c7c84ac01149f32b 3268127 +84e535ac-f3df-4319-9d43-27ebdf16c7fc 0186c448-fb61-4429-b9db-b8feb72f4709.rna_seq.chimeric.gdc_realn.bam e8c2d7eb30ffc6ee76fb4549d8bdc42a 323095280 CGCI-BLGSP 75664f55-936b-42cc-b0ed-f219112c06f2 ccbfd547-c8e6-44d1-a013-69ff6428e655 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b0ae6633-8a61-4a70-a4fa-6cb26d9c2bdf 49401b3bb200193b5aae7152d9683a2f 335964389 +bc9f0605-32c0-4a4a-81b2-d0f39a512080 b3d16f53-5681-49a1-9ba0-1c5ad6d3b301.rna_seq.transcriptome.gdc_realn.bam 557a145d83a996e26863d65b0949ad57 8951853428 CGCI-BLGSP af918a1b-56ac-4ebc-af60-b0823023c185 aac8c165-4613-4ff1-a6a0-48229c398010 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome f4f39c58-c60d-476a-85f8-e825164ee352 6acc92a88dcc9ebdbace05309e04b404 11329061323 +cc478bfe-668d-4c93-be61-b926d3eadc14 e5354a59-9d68-448f-ab12-ddca4b459650.rna_seq.transcriptome.gdc_realn.bam 588ff4972f1cb97697f819b1a51dec7a 11343997966 CGCI-BLGSP 58576f61-cf0d-4542-9f88-257ee412af7f cad655ea-5320-483f-b35f-a28d64d9210b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 7c12c145-5f39-4d71-88e9-d2e396c00ed1 84b2a5e5f8402087c0e8f8f372a31f8d 13223224306 +c40f4896-888d-4a7e-8964-72f52bec1b1c f940cfa8-4cea-41b1-942e-ab3b462cc370.rna_seq.transcriptome.gdc_realn.bam 7191118b010d06b24d75be777849b7e4 12545341746 CGCI-BLGSP c2010e3f-26f4-408f-95f2-9c06a43bee88 662c9e01-2a4f-4431-83b1-0dfb3c21b335 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 3461aced-5fa0-4089-95e7-4bdb4303e136 944b2df4aa84ce1f3db4ce84ecc32ad7 15065913430 +1d69b24f-aee6-4a6a-a53b-b3a7a597a7f0 56c2f382-5952-4426-bdd6-79b0980b05c4.rna_seq.star_splice_junctions.tsv.gz 14ead65cc9afc1f426ddaa5369f9e8a5 2942558 CGCI-BLGSP 8ef78bfd-48cd-433b-a3ff-b8c4e755406e 92fc379f-38c8-4ad6-ba50-9de64d555ba8 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 465c82e0-20a9-44f7-ac25-5813038ac7d9 3e1303a838a7a1973491e977670efd64 3007681 +f30a12f9-6bfa-4320-8efd-f204328875ea fb4a7bad-5cb3-40c9-a5b3-9ab24219ef14.wgs.BRASS.raw_structural_variation.bedpe.gz 51e6870718c6a105999d40d718b5826c 9425 CGCI-BLGSP 3dc70167-c921-4cfe-b784-20d22817532d 8abf9772-ed2d-4124-a1e5-b03178072bdd,979f1f41-0e6b-453b-b0f6-1eb3fd677fe1 Somatic Structural Variation Structural Rearrangement WGS BRASS d393c28b-25b7-4282-be27-b00d08295c38 5029d134bed225e62f92925bea7a638a 31845 +e407a228-b955-4111-87da-c25d83c876ff d2032126-8de4-437a-9489-6cf34348a137.wgs.BRASS.raw_structural_variation.bedpe.gz 5bfa0ac01f9806dbfcb65d9753e184ad 9933 CGCI-BLGSP d0f47e8d-df1e-48e6-a127-6ffdcf7be450 68e608ee-d8f8-4816-b46d-c8cbed8f534e,608d30ec-36a9-4877-bb3e-f21d9e807a1c Somatic Structural Variation Structural Rearrangement WGS BRASS c171f7fa-e84a-424c-89b2-c0117686cf92 5faf305588fed4f2836a169899a59628 35647 +400b5b18-f6c2-44a8-91c8-1f4cbdb63c1e 684017ba-4056-40c6-b3a5-affaa84da167.rna_seq.star_splice_junctions.tsv.gz 4ad291c8dea444066f59ff819948dec8 3360935 CGCI-BLGSP edf2e5ba-5702-4f96-97f7-124d70bb16aa e28bbfbf-8c88-4667-8970-6954f3db51cc Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts d15439b6-b7e5-4810-8282-e31d383dea0d 53434d58a5941a69f272f423eea8edbe 3476075 +4933f4f3-9f3a-4b5f-b717-d45df1481e3f 19c8bf8e-a115-4747-96b5-351cd3a78de7.rna_seq.star_splice_junctions.tsv.gz d2cb399dfeda62f7653e9e3781a271eb 2821144 CGCI-BLGSP a789950d-3cbe-4de1-bba3-00ee3e0e7a46 abe0a243-4500-4444-b31d-b23a28954c85 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5edc296f-d975-4510-8e05-7d45e94250b5 85a0b7f8b4305b034145ae44c5e3c964 2897099 +8abe9aff-f260-4b78-a28e-4500ee638315 77bb7e67-3468-494a-9f34-b139d7767bdf.rna_seq.star_splice_junctions.tsv.gz 3ad2d18dd46ca8ec43c0dd8ee2fc8c92 2771792 CGCI-BLGSP 8a678613-f77d-45d1-9c13-8595e55e8f27 049aec5f-5534-4eea-9cf1-6a11906088a8 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e4501e04-d33b-49c9-9757-1d69911fc112 a05a9a45cd3d633dbbe90aac6438e562 2839039 +9d7b39cf-6406-4aab-bc94-38db5128acdd 2a3f6588-b301-4c8f-955c-c4607000b36a.rna_seq.genomic.gdc_realn.bam 5664a8a2596a1e91a5f94dc610a566ef 13117810882 CGCI-BLGSP 48823727-d7d5-4efa-b374-17e3cfffad91 79528e46-4e76-449c-a35c-25a97ae31f8e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome f70731b0-342a-43d5-8006-caf68bb8309a 3a47bc8e8f15b5d036792ce0fd8e9109 14046574056 +f835c0af-5f9a-484b-99a8-bac78ee8feb7 758b57b1-42fa-48a1-9be4-12d9970bb367.star_fusion.rna_fusion.bedpe 9af80bb6a40dd86ced96efa32f6327f4 1256 CGCI-BLGSP 8c9c36bd-ca35-4158-ae79-b317d3a61128 94205a3b-72ee-476c-9f30-8e52b9f66418 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 3cc5016a-f0d4-4772-a678-59715f0ba2df a7d96ba117da253fcab6d3bc168e607b 1316 +5c627611-257d-4b02-bd09-65a38e342d36 7cbdb45d-e8f9-4030-a60f-61c7e51cd354.rna_seq.genomic.gdc_realn.bam f3d2aff3e449faafdbbe2dc9540f86ca 22101695497 CGCI-BLGSP 3cfb178a-c476-4c0f-968e-55c57239e7c7 b213a7b6-e60e-4edd-8f6c-87f22fc44ac5 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 2c4f553d-0d41-41d6-b42f-def34cd62079 0a281b8a6d1ac2b77aa62e0cebe66587 30446312929 +e1d41d95-5303-42b2-aa4f-dc0970e39702 362a1ae3-1344-445c-8c05-5b36c9c123c3.rna_seq.transcriptome.gdc_realn.bam 08f0b733cf23b21a316d85632a0c43bf 12643589914 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 2ee24626-72ed-4070-b034-92f88e7659c3 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 74d7f71c-3401-4298-b69e-a4e8c4b40722 adf97cc1314de9b69243f13436c0ea8c 14892720481 +219ff938-134c-46bd-8561-1d8529e70741 26678a84-2794-431d-9e43-30a4e6fdc783.rna_seq.star_splice_junctions.tsv.gz 4ac69402e63f05a693cfa1b72de530e3 3148785 CGCI-BLGSP a7547cd6-ffc3-4ea3-a123-c80c75ff85f5 2052973b-2dd1-4f1d-8ff1-7ca7bbaf228b Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 58172d77-a671-48d4-a3fd-16c15e05bbae de0f4fc4e0d8af557aeb4ce157145aa9 3242075 +325d451c-764b-46ad-b7aa-c3cfa6b877d0 1f1aaf5e-ae93-4e4d-a862-58e1fbb613d4.rna_seq.genomic.gdc_realn.bam 36cf2addc920d2ceba48149c27e6e535 10550127135 CGCI-BLGSP 49391d47-19dd-42b5-b57d-87a29b59b419 74f69b50-a95c-408c-86c3-b7e37771d0ac Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a606aa61-e67e-441d-9bf6-f0d41aa52f05 5de9a0fd1fe4226523995b7f8d23ee10 11411556797 +82738a02-e0fe-43e8-9063-2602f245d5b0 f1209f58-327d-4389-b776-fe50d7ced5f6.wgs.BRASS.raw_structural_variation.bedpe.gz 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Variation Gene Level Copy Number WGS AscatNGS 5b4ef68f-9977-4d92-8511-9a6aa19576c6 5406eac31b72cbf0a571f07d52af920f 3442763 +e024ecad-d700-4f32-b09b-8837ca642536 fff086ea-be3c-457d-a2a4-6cf63ef127d9.arriba.rna_fusion.bedpe 0b4999cb69de29a760856626c3421e73 7942 CGCI-BLGSP e8a5b8dd-cf75-4d13-88d6-018af64a0fbb 30d2ec35-3db2-489f-b270-eca924d552c0 Structural Variation Transcript Fusion RNA-Seq Arriba 50c53c50-4c44-40fc-9b82-eda812c010c7 2f22a8d8644ad7ac28e716414adde126 6624 +62e4b25f-a5bc-4e55-9063-c3d285ca7894 ab2ddd77-9ca4-4e8a-95c9-fad532661172.rna_seq.genomic.gdc_realn.bam bcf6229439c15f27764ce6d5c8d488c5 11703261839 CGCI-BLGSP 49b5173b-fc55-4ae5-8b72-964f2173395d cc40c6e2-8ffb-4b3c-9da5-2d9edb7eef62 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome f915796b-778a-42e5-9161-11deaf62b0d4 4a00343518a59ca1188a9c7aa5b9ade1 12919988831 +05d872dd-8baf-48c9-b4d4-5329a45af8bf 5043606a-ece0-4c52-acb0-32087429b361.rna_seq.star_gene_counts.tsv.gz 347e7c6ab51f14fb362c5053a4d6e5b5 409817 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+be04cf12-916b-4275-9dcc-c8874b0c978d d02d636f-7ce7-451b-8df3-36a4bf655b3f.wgs.ASCAT.gene_level.copy_number_variation.tsv 11c50fdc443465deef26bf3bf0012163 3482791 CGCI-BLGSP e8a5b8dd-cf75-4d13-88d6-018af64a0fbb 0400251a-f396-414d-8a03-99d748196d8c,b2e2c589-c138-43d6-a53a-f0a0407e3304 Copy Number Variation Gene Level Copy Number WGS AscatNGS 9de5bd77-286c-4052-8087-f206c188b69e 6dc5d4b332c76841258fc08bc0f09dad 3442784 +1208a256-d2db-4f19-9c90-de92631e97ed 32afa270-2c49-4634-be92-d215ffb6fc59.rna_seq.transcriptome.gdc_realn.bam 77dc4210bc3339e0bfb1c95f3cb1bf6c 11380797915 CGCI-BLGSP 39dce88d-112c-4a3d-b2d2-11e0616594d8 46a48950-f657-4a52-8b40-436aebc4defc Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome f5315100-66d5-4d8c-b0fc-4f0531e45e16 1ba896609a7457e19895e99f9dd8740e 17020261477 +11be427b-c253-4f88-a70c-048de0095adb 02eea485-625d-412b-b45a-458d87b1a866.wgs.BRASS.raw_structural_variation.bedpe.gz f211a046528ae7b90729c37ed88b6c0e 10991 CGCI-BLGSP 213e9f9d-7340-460c-93a3-edd559b42009 34df5fa1-a9fd-4a0d-99fd-34a056c164e2,bc184aff-ea8f-4797-b965-8b1f2da31103 Somatic Structural Variation Structural Rearrangement WGS BRASS 5d7b3521-d4f0-4457-ba5e-4da7c747b61e 9a2d858654ab0d95d1693edffb8be8ea 39289 +f5338196-feba-49f6-a057-949267229c5c a30cf0e7-1e83-45d7-9591-f99fca72fe84.wgs.BRASS.raw_structural_variation.bedpe.gz 0da8328c49b844e8bbb4e83c30d65cf8 9205 CGCI-BLGSP 9faf1ba6-1cb1-4195-954f-12919f0aedc9 b7df9cbc-96b7-4cee-b8c4-20b7b6deb817,803ea3f6-3657-46f4-b494-bce43f19a3c6 Somatic Structural Variation Structural Rearrangement WGS BRASS 5d476c05-c32c-4f9b-b0ae-dded7737f3d8 6a94ce495482b26b1300058d0a4d94d1 31995 +bcf1ba4b-a7e3-45f4-a431-92598b9ffcaf 69a39039-1f2f-4da5-af55-c2ff362b190c.rna_seq.star_gene_counts.tsv.gz 09f92688046a16c47a6f8559feb6b130 401743 CGCI-BLGSP 4dc94896-aed1-48af-b1f0-6ddbf91a8cd2 891ce72a-f858-4bfd-93ae-d034b38389d8 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 3bab6e88-df7b-4d9f-8b49-d83cbb13a178 0bc2f1660bbc7a678ba8bc45cbf0a5d3 4222724 +6c9a2024-36e3-4ec5-9635-9b2615746a90 5c279b5c-b25a-492c-8a28-6ee83495a507.star_fusion.rna_fusion.bedpe cb57581df6d2af77008af58e8b31c1ef 675 CGCI-BLGSP b22261d6-12e3-464d-99cb-da3ae8ba6ba6 9d34db0e-55a8-47b6-8de6-2522c926a463 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 7ade6f3c-891b-4493-988a-a0453ee98395 7ee60d374ca81da3fbecd05dfd7d195e 707 +1fbce67d-9410-4190-861f-95fbe4fbc364 351712ad-9254-4175-9ac7-f0d24847ac9e.rna_seq.chimeric.gdc_realn.bam c5c255072dc250fe7e9c29479e22808e 110711555 CGCI-BLGSP e0ca8db8-b71b-4a63-96b4-96d368cc4fd6 9be49a9b-548e-4214-b553-156bc083f9dc Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c1383136-8e5f-4fc4-ae6d-c77967900751 0316d173d2704c42d58336a912eaf959 116094384 +c8e27af3-af37-4907-b1ab-dc279afabeaf 0c6483cf-9bde-47fb-8e44-4982826bbfad.arriba.rna_fusion.bedpe fc52154b524ea4fc3e1449798058f450 5181 CGCI-BLGSP 8c9c36bd-ca35-4158-ae79-b317d3a61128 94205a3b-72ee-476c-9f30-8e52b9f66418 Structural Variation Transcript Fusion RNA-Seq Arriba 38e3bb86-9ab8-43a8-b5a9-e8b1b9dc5c49 0775cf574c2dcb3e9673209a708bd2f9 4981 +9461308b-c5f9-4487-a471-a2046f0bea95 b2165d6b-2026-4c67-96f8-b8e31337cf0a.wgs.ASCAT.gene_level.copy_number_variation.tsv bbb5e28dc23359b74e33241cacb8e9ee 3482662 CGCI-BLGSP 39118490-7870-41f5-8b56-d0ee38fa8bbe 4c8eb5ae-543b-4427-aa33-b69f837dd581,bb62c290-3b2a-494b-9701-ded04138648e Copy Number Variation Gene Level Copy Number WGS AscatNGS 4d06a2c8-8ed3-4dab-a629-f4d36e7ec94a b984e36cac86e280071d347fcc2a2ca8 3442673 +d4996568-21cb-4f2f-8a8f-cf05241c51ce 35663093-9322-431f-8799-746ec1be253a.rna_seq.transcriptome.gdc_realn.bam e3362ea67ea684ac82231823f46219d7 11819171157 CGCI-BLGSP 7dcc3723-aed6-4d2f-ad8b-afa443634139 e091e258-4d2e-4bae-a56f-d35a051044dd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 71d40ea9-d36c-4b42-ba14-e98b076002df b0282069a27eb16421117962f3a89683 13805348171 +e3ea8296-64a1-49f1-978a-9ada68a784c3 5cc5c4a6-266f-49d0-a192-9053e6fb9d6a.rna_seq.star_splice_junctions.tsv.gz cd3d9a10673c8f5fc9d9b531210dd267 2964831 CGCI-BLGSP b22261d6-12e3-464d-99cb-da3ae8ba6ba6 9d34db0e-55a8-47b6-8de6-2522c926a463 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts bec7192b-e57a-4ae0-af3f-2d19a190ab36 88b78be5536a46b4d0e57af8b627ab79 3059558 +4f40c3c4-78da-4a79-b3a7-9298b3664d84 26678a84-2794-431d-9e43-30a4e6fdc783.rna_seq.genomic.gdc_realn.bam c7a6988af72964d1ca20718838af1da1 12405763496 CGCI-BLGSP a7547cd6-ffc3-4ea3-a123-c80c75ff85f5 2052973b-2dd1-4f1d-8ff1-7ca7bbaf228b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a1660fe5-1eb7-4eef-b62e-6883f5ce35ae f20a7b95af57e2e35e952483b2a52a13 13570494373 +c908ca68-934e-4b8f-8de6-c4bcb7712a01 84b0a6bb-18df-428b-915b-f7e884751db3.rna_seq.star_gene_counts.tsv.gz 999b61ebb05eaa69b0b97abd09bbce14 411962 CGCI-BLGSP 0ceb3081-4c6f-4fd9-9535-5accddf76bc4 bbcefef2-c5b5-4c88-9058-dd4ae2200d41 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts a78248f7-21c8-4bde-ac30-1a14d0fbd7e1 6930c2de0f751cd5b4a935be713fbcab 4231512 +17d4f65e-f243-46be-80cf-c860f69f57ec 2c4d5be8-1106-41bc-bb10-70ce62b2072c.star_fusion.rna_fusion.bedpe 08be3b346d29f0c2c8b403a43b12baf2 1101 CGCI-BLGSP c2282c90-795d-4c90-9c4b-51e340f98ac4 fcf6c07b-c1a4-4f0f-8691-5e35c111d3b1 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion f9aa360a-ee11-43a1-8345-79f3533f5f24 6e5690795ff424264402ab9d2661b62b 229 +c1e90329-ff70-4c71-b120-936ea99913c9 5043606a-ece0-4c52-acb0-32087429b361.rna_seq.transcriptome.gdc_realn.bam 44eb9390ce298c589d787126d42a02b6 11703259297 CGCI-BLGSP c2282c90-795d-4c90-9c4b-51e340f98ac4 fcf6c07b-c1a4-4f0f-8691-5e35c111d3b1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 99d87759-aacd-497c-8fa9-39a597f9f3ae 6f1804250c1588911583ad86d9f48df9 13799360894 +9685c96c-7432-416e-b521-9c5b4aa54617 c6935568-24de-4859-a11a-88a43494ffea.rna_seq.star_splice_junctions.tsv.gz 665871dba7042cd99cfa5e335dd1d04f 2814149 CGCI-BLGSP ef5d356c-89c9-48b1-a567-519aa478f166 b92cc867-6f90-46e9-92f5-8100a119e349 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 75090865-0149-4122-af38-4655ac8756ac 3504dc5365428bca47ff27229936ff07 2892677 +850601e4-7983-4fba-9925-44e619186fbc ca1450bc-5be0-4f17-b2a7-62fd3888336a.rna_seq.genomic.gdc_realn.bam f59a4022c80b8b7a0f14d4a9dff626e5 11300844366 CGCI-BLGSP d4524555-0c72-4c58-9203-2223e1c1c211 8cad1bc8-8275-4443-b6f5-74a45e133011 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 88374c0b-ca52-4057-ae63-d0009c0126fc 3e9c2dbe2f0e69b1c5ef4b41649b9737 12394070854 +0050c356-cf2b-4bba-8759-6dc3a7a9e864 8235d7c0-284d-4b65-b272-5a62e4fa6dae.rna_seq.star_gene_counts.tsv.gz 44812fdeeece00e9ebbcb5999b656da2 415534 CGCI-BLGSP 1baeae6c-057e-4f47-9f8d-5d42aee5d3fc 503e33b8-a5b0-44f5-ba00-8eff720e3808 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 12ef4064-92ec-4070-b3d0-f7e577064d8a dcd75f3ecb95f608102b3bb7c385cae2 4233976 +c580f8a9-a37d-42e2-a2f7-68d42b76637c 6e86852f-e6d5-47ef-b882-d712eaed45bc.rna_seq.star_splice_junctions.tsv.gz fd5ba6384cf0b6331b0b56d1cecbe505 3136914 CGCI-BLGSP eb6e891a-b8ab-4261-808a-d543d1dc07d7 e2393e0e-5506-4017-8960-6df5d3248e0e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5a475481-1857-4109-9d08-cdd4e9694ed2 4618021949bc7ce155e4040f3a13f447 3208654 +7dab63f2-5627-4d94-8515-69ac8cc24cd1 45a8567e-3124-4039-9f75-7e8d8e96659f.wgs.BRASS.raw_structural_variation.bedpe.gz caadfb1aa73f2f286c55c1f86609e66b 2251 CGCI-BLGSP d991215a-fd4f-434d-a17a-cf106aa72edf f26de9c7-c6c0-40d8-b48c-c6ae3130c52b,bd1a98f8-9657-42e6-bba5-d5418b26d4bd Somatic Structural Variation Structural Rearrangement WGS BRASS a5f49262-c7cb-48fa-91f9-cef81de479ab f5da0c46ff08bdea7820b9a89d9a081f 6646 +0325b886-1565-4910-9ba4-e325cc57bbc3 ce8460bb-6fc8-47ff-8694-1db8bfbd7144.rna_seq.genomic.gdc_realn.bam 98c31d6959213fcad47eaa97dfaf0629 12720243540 CGCI-BLGSP 5b4325c0-a7f5-436f-a7f3-630358e3ba2e bccbe421-db78-4cab-bc2d-ea31d7068582 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome ded83ddd-b353-424c-b029-d3e29d1d192e e23f0e6ad0d3ba7f30a834690a314ef1 14505818989 +08c200f1-b2ff-45ea-8b20-c0534474c416 6236b0ef-6d23-4883-af4c-3f9639574079.rna_seq.star_splice_junctions.tsv.gz 945c57df2efe75e7a1343b555f508168 3225991 CGCI-BLGSP 557ad893-cb31-4fd6-bdfb-7f7930787dec a2ec82e8-7c6c-4f2b-a80b-595b6fb24409 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 29b82f40-e7fe-47b7-9962-bbd00d732817 412045724613b2acaa3e1a96ad831f41 3305547 +48f41ff6-502d-4e3e-802b-97739757f8b7 3c166f60-4659-4651-9482-0e78e32e0c08.wgs.ASCAT.gene_level.copy_number_variation.tsv a46ba672f08aa8f09188873eed1fa139 3482758 CGCI-BLGSP e0ca8db8-b71b-4a63-96b4-96d368cc4fd6 cae662b0-3232-473a-8442-dbc6c546ba91,4d1245ff-3429-43bf-9dcb-3775cff816e3 Copy Number Variation Gene Level Copy Number WGS AscatNGS 1eeac122-0f3a-4eb9-aaeb-8e195fffbdf3 24779f5fccb58560113612ba6445dcc1 3442754 +86698842-d059-45f2-8b2e-f1fca6726e8f 9c8ed150-492f-4475-ad45-184590068a11.rna_seq.transcriptome.gdc_realn.bam db75726b71488f0c91ea5739b9c4db5a 17602555360 CGCI-BLGSP d073b5bf-f145-4ce9-b938-527634f164e4 843c0c90-8e87-43fc-8610-10da9ad6e567 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome e7984505-a06c-4685-8beb-d3d4106e1dc7 8c24c696d81a86eb1b287dc094468689 22110485471 +7105e1e5-2d4b-4600-b3ee-44aac4696e76 f7772619-ec67-4314-9b91-a55ce0b4a950.rna_seq.transcriptome.gdc_realn.bam bf1cd327e151a3a08fc0aadab5f925a9 16455220895 CGCI-BLGSP 89989611-e08b-4731-912c-952c248a9b5e 2d3712d6-6abb-4003-bc7f-d0a3a145e1a5 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 45f995c3-2932-4eaa-a563-e9bf17b518da af818e9401cdfcfbe9fb85345e24419e 20026723774 +ddf33b99-db1c-4eb6-bf49-112f509cfef4 362a1ae3-1344-445c-8c05-5b36c9c123c3.rna_seq.star_gene_counts.tsv.gz 475bc1670fecf4a93f3aed0d017bbd3e 405593 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 2ee24626-72ed-4070-b034-92f88e7659c3 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts aaee3820-ddb8-455b-b08c-8debfc59e432 18c425874f6ae3f9ab24577cb323ab10 4225572 +a8223401-2412-4812-8ed7-d9926aa697ee 125a69d6-5062-415a-8a51-8ba983a0bba2.rna_seq.transcriptome.gdc_realn.bam 6b63a937e1d87dfc8c6e602825ee7e6a 11747972536 CGCI-BLGSP 75a86324-6a4e-4921-bc3e-375b848f3d34 8c6dbbba-1f3c-48b4-b48c-a3e46286f60f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2ed509fe-12cf-4003-9e13-7b578ecd3009 21a170a6027bcc64decffb77f945a614 14108417478 +d3ad8ac0-2d80-4628-a116-9054f8c59ae5 329e077b-3aa5-44f5-a9c7-33ed4af9bac8.rna_seq.transcriptome.gdc_realn.bam 89a5f2a8f8f37a90f402c4a14b40626f 15758543807 CGCI-BLGSP 2721630e-8b64-4e64-8177-49f0fa84cfeb dcabed3f-05ec-43a7-b4e3-eb6ce820e87e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b3aea9be-b210-4728-a72e-e111bd1fafcc 639a546eab037372585ffb3b61b48fbe 18887909593 +1996ab25-80a5-4007-b45e-16ce74c6c587 fce5f34c-4d08-4ac9-81e9-e6cac336f02a.rna_seq.star_splice_junctions.tsv.gz cb23ae76a0fe059be21080da4c057473 2647132 CGCI-BLGSP 39ded2c0-56b5-4561-aa3f-7d417a32a131 072c72e7-7c1e-4db1-a519-3dea4a1b8fd9 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts b545d6d6-95f7-4846-9c41-f37e80358468 5270598def5b0862c5b6e38926d73ad5 2711464 +c0d8f837-6e2a-47aa-a270-8342fbaeea17 77bb7e67-3468-494a-9f34-b139d7767bdf.rna_seq.transcriptome.gdc_realn.bam 8a0fdc4118ca3c9166f74fbd6925f166 12953655394 CGCI-BLGSP 8a678613-f77d-45d1-9c13-8595e55e8f27 049aec5f-5534-4eea-9cf1-6a11906088a8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome fcf37902-b8d2-4c33-aa59-54b8595f78a5 c7936d2a287c30826fbb506a194f5fd0 15610178580 +45c84d26-5137-4c50-9c74-33f9099eacdc 3841dc77-132e-4073-93e9-c71bd5a5819f.rna_seq.transcriptome.gdc_realn.bam 895a7e00b883866ff9bf18f299a44c9f 15031257068 CGCI-BLGSP 0024c94c-88ff-49d9-8dc4-bf77f832d85e 174dacb5-1f2b-4bf7-9ca9-9032a7cdb4ef Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 58805abb-d414-4348-990d-65ec15291b3a 2d8f5c38c3aee237ba7d52e746243705 18004795767 +01698675-9269-4926-88f4-139b51fbb3df 16e638e5-d192-44df-ae58-6936b40406b8.rna_seq.genomic.gdc_realn.bam a2d7b971009b38d5ed47a49015efed23 13410616085 CGCI-BLGSP 486fa825-324f-4011-b43c-f6454702e0d6 01a6744f-6d5d-47ab-9455-30327866164f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 91304d15-53c8-4a29-8e0f-9e6e371cf909 4339019326749f0c9cf3d3c37590fb55 14747780880 +d7484875-a4e5-450d-9f20-40ac13937ab3 16f86676-8b5c-42cd-ac6e-9024cee0e3c1.rna_seq.chimeric.gdc_realn.bam 7cd417526c30da977d25f2e5a3ded293 94039399 CGCI-BLGSP b59a2c3c-7085-49c5-909a-c8504b1ae2a5 f66b1acc-8129-4b33-b06f-e3937a157c14 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric a940eb7a-6b71-46b2-b662-7c2b7deef6ab 148a5abfd28d44bf5aef54b0b9f401ba 99140908 +2cdbdd4b-b635-4172-ab06-6f1518b16313 26678a84-2794-431d-9e43-30a4e6fdc783.rna_seq.chimeric.gdc_realn.bam 561688483b53d3d1e838c43b6e1d56dc 102895735 CGCI-BLGSP a7547cd6-ffc3-4ea3-a123-c80c75ff85f5 2052973b-2dd1-4f1d-8ff1-7ca7bbaf228b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 91ba0731-5a11-456f-98fb-9eb856bcf734 781aa1e78f26c5677d97457aec38d076 109077429 +6808d9d9-f45a-422e-8bd8-1c8272220001 5656a116-2e23-436c-8341-3eae83035998.rna_seq.star_gene_counts.tsv.gz a250641946e97e4e1ac289f8fe929d40 404139 CGCI-BLGSP 0f4cddb3-c60e-4d95-b90a-3e26756a7bfc 35e80027-b59d-4cf6-92a1-162f2f79ce82 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7b89d5fa-00e7-4632-87ed-d9918c8e2bff e846fe47dfd2737d300b94c905a840d1 4226056 +0d84e397-50b1-46e9-ad41-301f260197d6 10e693d1-4ebd-4b3b-9781-f3ac72f24908.wgs.BRASS.raw_structural_variation.bedpe.gz 3c791af59bea803637075f1bf05f6955 12854 CGCI-BLGSP 39dce88d-112c-4a3d-b2d2-11e0616594d8 6fdd85b6-8185-416a-ab8b-d45f37c523ed,e3542ca3-2bec-43d8-a124-ae66d7b5e7c4 Somatic Structural Variation Structural Rearrangement WGS BRASS c5ee3038-bcdb-4902-b4f1-5fa54a29edc2 80ecb9265cd4b88f789766a2118c702a 48667 +c0a46ce7-3845-4414-b5ef-97e4cd40127c 8681b858-9dd1-46c8-ab9b-831ddb9e5273.rna_seq.star_gene_counts.tsv.gz beffc7d3ca0eb4e764cdbe228d6b3f5e 408412 CGCI-BLGSP a21b8ec0-1c09-48cb-97d1-42ed0096964a ce98ff94-58d1-4cd3-b08e-d98cd37d4afb Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 23f961b1-7993-4337-879b-5a7184874b2b fe61b1ab488cfe2516e93acfb3667561 4230127 +ab765404-1e74-422e-8b0a-c16b3f437681 16f86676-8b5c-42cd-ac6e-9024cee0e3c1.rna_seq.star_gene_counts.tsv.gz a3c90424e01a136557b6e0a16aa72fb6 395337 CGCI-BLGSP b59a2c3c-7085-49c5-909a-c8504b1ae2a5 f66b1acc-8129-4b33-b06f-e3937a157c14 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts b7353b1c-eaa6-4e84-850d-73eec91ef78e 000b74c9701936c4f263b8bfa6f823f7 4217276 +6c240552-3c68-4ba7-a9b0-29eca160aa19 e1ac94bb-edfe-4785-8ea0-7919f374b0b3.rna_seq.star_splice_junctions.tsv.gz db8d3df0af804fb46cc02baceb50a4d5 3239098 CGCI-BLGSP f4a0bef2-c397-4149-830f-8d5f62e1b5e8 39eeb322-1c7a-4859-8c3e-848e0f83233f Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f872d199-f089-40b1-99fd-2a5d328bc3ee a8d354ed7b762ff2d1952584396c924d 3328076 +db5cf3ac-e354-4f2c-9355-8f1b881fc60f ca1450bc-5be0-4f17-b2a7-62fd3888336a.rna_seq.chimeric.gdc_realn.bam 94c1de62f15ac643b9b6f48662d6b631 89246736 CGCI-BLGSP d4524555-0c72-4c58-9203-2223e1c1c211 8cad1bc8-8275-4443-b6f5-74a45e133011 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e1b40dae-39c2-4667-82ef-3a99661082bf a5437de1fed4ebcc067e6196b4968b83 94081211 +ac7fc276-f372-48f9-9443-abd0d4905930 6520b5f0-c551-4423-9835-fa2a10b94453.rna_seq.genomic.gdc_realn.bam aaaa3149c67f58d1591ef610a9b19d5a 11252316565 CGCI-BLGSP 571e6d8a-1e84-4f99-8b0f-e55dd126426a 2bc66ae4-12b5-4230-8d97-74461598f17e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 50e70ef9-24f0-4811-9f23-0a5d9aafaec4 37802f90d295f3abed8c2f40c1b85781 11863750343 +9203679d-b0cb-4eaf-9b55-9752bf6a8a6a ab2ddd77-9ca4-4e8a-95c9-fad532661172.rna_seq.star_splice_junctions.tsv.gz b046c07aa0386d8ffb6fa70de4285f07 3161219 CGCI-BLGSP 49b5173b-fc55-4ae5-8b72-964f2173395d cc40c6e2-8ffb-4b3c-9da5-2d9edb7eef62 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e64c5e77-ad75-4cd9-b07b-bd1cf460151a 8cf1875e6668532bd18e2103d327ebff 3256420 +dfd77125-4b21-44a6-bf6b-e7380eafbc4d a5fc7a8d-0faa-427b-a28c-afa98bf09922.arriba.rna_fusion.bedpe d0c1d7280adf86acbd2e9128cf0601de 3784 CGCI-BLGSP c2282c90-795d-4c90-9c4b-51e340f98ac4 fcf6c07b-c1a4-4f0f-8691-5e35c111d3b1 Structural Variation Transcript Fusion RNA-Seq Arriba 9be8f610-cfd6-454a-9d63-03f62cbd7024 b8c3cfaf97a5b6508717ba48d37e8d0e 1632 +f4fe4a09-8246-4862-b653-01c62b2b8bd1 5b5681ba-d659-4ef8-948d-c4f70f86519a.wgs.ASCAT.gene_level.copy_number_variation.tsv 3c9cbb8d53feeb66700f1e9c445b0f33 3481168 CGCI-BLGSP 39f9996d-b217-4222-98ea-47c210d49e93 627a2e7a-47a6-4c13-b349-32e302030013,b1af34ad-f7a2-4af1-af20-a289418f271e Copy Number Variation Gene Level Copy Number WGS AscatNGS aee45333-15bd-4a6c-9efa-5687f3fde6ab 573c58f659a8187329da3320af40a84e 3441245 +b73ac5a0-7cbb-4ffb-ac96-3d08ccfe7108 00b79053-d3ee-4f6a-acdf-b5f836e12f80.rna_seq.transcriptome.gdc_realn.bam cc52fe003dc3dca493961a931aad07f7 12300351389 CGCI-BLGSP 4a460794-5919-4e36-aa5b-67eb318884bb 86029bcf-efc2-4701-8834-2a635997a292 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 4a2dc7cf-bab8-4a8b-99fa-a62bd807009e 95e1c5e4b5c7428677fb7992bc1fb963 14651620491 +506332f8-b030-4a75-b342-e69d090f9908 a07ebe99-d21c-4b2f-9f12-11ddcb56701e.rna_seq.star_gene_counts.tsv.gz 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CGCI-BLGSP ee385ea4-54db-4033-b46a-8c397ed4aea9 8454651f-596a-4851-9055-ebd6e32527a7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome b1a9e6fe-e550-4aaf-81f5-12cb635af36d 117a73d70966bce637e3a694b47e3b4e 26335634926 +4caeede1-d399-4508-957d-3b15fb65392b 65895f07-54a9-453d-9d31-39140063a65b.arriba.rna_fusion.bedpe c45a03a63443017a9298876e0e1d7d83 5569 CGCI-BLGSP 0ceb3081-4c6f-4fd9-9535-5accddf76bc4 bbcefef2-c5b5-4c88-9058-dd4ae2200d41 Structural Variation Transcript Fusion RNA-Seq Arriba a9b8594d-4587-4802-83c6-0530e2b35e9b 558e403ca3803ef8ce1a2d615935e888 5077 +806199cd-b734-4822-b0a4-4afa40cade00 d213c5f1-6d82-45fc-b4bb-19667cb2b170.rna_seq.star_gene_counts.tsv.gz f9df136ce4f36235afa00db3fdbed659 398229 CGCI-BLGSP 681ff2e8-6073-4dab-a398-1f2203c2d7f5 8cc05c59-cd01-4998-a1dc-30d8e13c2956 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts a49f3c07-c574-417c-87f7-ce76c6241d79 40e2669784ee395eaa07757bcc1152ee 4216837 +7f0597a6-3a25-463d-aea9-f76a28a14e2b 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2d9d9b48-419d-4082-827b-d1bff8e6f216 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion e0ef17ba-d954-4abd-944f-d8b0241c6826 0a81296fd0d869ed2987a70ea67b60b3 1548 +55b51e9d-181f-4f87-823b-793dfd423d53 e9f6a146-7067-47be-bc37-c964b6d709e6.rna_seq.transcriptome.gdc_realn.bam 77ab9443eaeb08402d6810811305ad3a 15509898440 CGCI-BLGSP ee385ea4-54db-4033-b46a-8c397ed4aea9 8454651f-596a-4851-9055-ebd6e32527a7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 0b4ea6bb-d2f6-447d-8ff2-82c40e7558c5 d5a21a7891b0202c74f58f8209987f18 18327932355 +ce0acb82-2d2d-461c-b0c0-37798aaf0792 3d6c3cac-ba03-4e9f-b7e4-d24596bf34e5.rna_seq.star_splice_junctions.tsv.gz ed84ecf8adf8e98f2b1b8df55314f62f 3346048 CGCI-BLGSP 69cf7ff6-fcb3-4177-82a0-5a589073e4e6 60ae79dc-769c-4c0b-a0aa-3fa99176c596 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 3a3351c7-5044-4196-8ad2-e8c95f41e34b 0070d1b252a2c8468448a18e78fd215f 3430914 +ea94d8a3-a5cd-410a-a5de-182402ad4b64 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Structural Variation Transcript Fusion RNA-Seq STAR-Fusion c829b40d-71e1-451e-bad8-9c738243e639 6e5690795ff424264402ab9d2661b62b 229 +08cce608-1055-496d-97d4-537c1325a507 8897275e-35bf-4693-9d6d-c567633ab739.rna_seq.chimeric.gdc_realn.bam d382a66e149f0ac8f5bd8639cd5d27cd 160127895 CGCI-BLGSP 92194f18-046a-4222-9409-679b8872e6bf 4be4fb19-b505-4de7-b26b-a4fc582b3b8a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 8834c094-17b0-400e-b1b6-e04e1ca142a2 f201c35f1acbcfbd4427214290b93c53 170048689 +61285241-c5cd-4c24-a6a8-2a9e97e89b68 ce45402f-e51b-42c7-8822-bc8cb0298955.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 06c07e2d-a04d-4099-a29f-948e40558dd1 2e9ae889-acac-4f29-aa7a-a6584ba571e8 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 32b720eb-f1a0-488c-9e77-2e3d3891f58f 6e5690795ff424264402ab9d2661b62b 229 +b9849c9c-3d27-4197-954e-e1a525f8dbbf b3d16f53-5681-49a1-9ba0-1c5ad6d3b301.rna_seq.star_gene_counts.tsv.gz 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cb971984-dd8d-44df-919c-de8c4c1db983 e63f1b2c0bc10abb20b904d8a0d6ba6a 213831512 +6b966f15-8c2c-4651-8ae2-14645babfaec 566142d5-1ce1-4c3b-8654-7a0888c42f30.arriba.rna_fusion.bedpe daaf7f682745d868eda05151a3a84b4c 3638 CGCI-BLGSP f90e6333-f59e-4f6b-b7f9-17ba10e4a600 f9627688-8e25-4ede-bde0-8da01ed7528a Structural Variation Transcript Fusion RNA-Seq Arriba c5fb0d3f-4cb7-44ad-b0ed-cc86406c07f9 fadedf547279a130f848c01a34109876 3036 +418fa310-2b3e-4e8e-85e2-d89928477d5a 1d14c6d0-dd7f-46c8-9648-f74485dcdbc6.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 3cfb178a-c476-4c0f-968e-55c57239e7c7 b213a7b6-e60e-4edd-8f6c-87f22fc44ac5 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion c3702601-e11b-4035-a899-6b48363e37ec 6e5690795ff424264402ab9d2661b62b 229 +ef467520-a3cf-4eb0-8e95-6f0edaa056f4 fc2bd1d8-e3a3-4fed-a7a6-62f6dad72c09.rna_seq.star_gene_counts.tsv.gz b9c7f57e344c63376d2ef29d99e5df57 425394 CGCI-BLGSP b06f7bf0-45bb-4aca-8f22-72d8a4f73f99 658beec9-2428-42b6-9663-fdc58c15c602 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 79e65651-475c-4f05-9414-f0fdbd0b66ad 2447ea5286e32a24df4674b2d4dae0c3 4245683 +82f1966c-7662-4b61-87ca-e1c003b5a5a5 39bde99f-e97c-4f13-af83-5cd7dded015a.rna_seq.star_gene_counts.tsv.gz 484a8388f6b61202cda04fb8541d97a9 398372 CGCI-BLGSP e51981e9-e358-4b91-93b1-403b0d434328 f9190789-f39c-46f4-86be-701a16b5108d Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 85e59fa8-9ebd-4c37-a687-e13864666495 b2860687d3089dfa9eb0f406a8c1f910 4218307 +cdd178ab-4332-4e81-b578-cb65fe1f6439 737ea3bb-ec46-4707-99a1-bf3f61052aaa.rna_seq.star_gene_counts.tsv.gz 3ecb066bed440c16236a6d3f6fbddacd 395216 CGCI-BLGSP bcb4326c-3c7f-48e8-837a-b43bb2535a0e 784a65a6-e398-4c51-9744-c475933bf478 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 23c9c7d0-0aa3-453f-bd64-b93249927962 0e6851db2da2662c8aba280fe9e76e9f 4215126 +e9dae0eb-68a3-4e97-982b-9973b99fd555 329e077b-3aa5-44f5-a9c7-33ed4af9bac8.rna_seq.genomic.gdc_realn.bam 64d6d74995d685ef61ac8dc8151be3d0 11000469268 CGCI-BLGSP 2721630e-8b64-4e64-8177-49f0fa84cfeb dcabed3f-05ec-43a7-b4e3-eb6ce820e87e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 23110282-9beb-4d3f-9f9f-4538b4b61e2e 147fcc610af9bced1cbba0424d868a9b 12058074927 +a2d0a8a3-753a-42c3-85e7-8db0245786de c554ed70-9e88-4392-8641-28bbb83362dc.rna_seq.transcriptome.gdc_realn.bam eb2e73dd375af9266be3cc6fb0d9ad6e 16843238292 CGCI-BLGSP 13c615c0-74b2-4b41-9a05-b8a71eca0685 88b60fb0-18f1-413c-860a-f057bb371d47 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 7fc24f9c-7f36-4a02-a00c-c1396ef95c93 b7403ee5f206a045bcf4ab5f5bd6268e 20043341890 +b7b17c9d-06c7-4af7-aa2b-50ea92d5aafe 551d6887-ca61-4365-8411-2deb635e9a81.rna_seq.chimeric.gdc_realn.bam 286971a8404c47bff0ec95992a8b4445 317029284 CGCI-BLGSP d991215a-fd4f-434d-a17a-cf106aa72edf 9fab0517-1d81-4178-a09a-a3d7f8f1f0e9 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b2d6e1d8-b572-4558-a78f-0bf0fbcc73f5 775295edb9924e9fe868e26bea6b22a3 326613733 +f8810aee-8c41-4844-b286-9e3012f6ac4d e6095c1d-7f6b-40f9-9196-0e5295ab449e.rna_seq.genomic.gdc_realn.bam f5863426de5a5e76e25ab0b6de6a5cbc 10375381515 CGCI-BLGSP 2d3e842c-e596-4e30-ad13-525b0cff690f 69862ab4-2a6f-4d39-bbd1-3170f16d32ce Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome b1352243-8f78-4c7d-aac9-83cb22c8495d 6293b8aea1346e9e786d19ccd82b0c6d 11347341568 +9ce23c1e-2355-4f36-8dfa-abaee181c773 db252b7a-4595-4947-b9ce-d8ddb719550c.rna_seq.chimeric.gdc_realn.bam 05880f2cf6cad4b56960587e3ecc5cf9 75295774 CGCI-BLGSP 0ee808be-13bc-4d15-a519-e2b7e960e809 1529cc13-192c-4969-bb1d-c695f166fd2f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 648b0ce4-09a1-49e4-a217-02a1c16dffcf 3b28a222bb48b66c862866a4e0437212 78186314 +04ea5621-7390-4a7a-b986-4ec8c984de98 693f76b5-6d30-4bbf-85a4-f9e6f43d5f70.rna_seq.star_gene_counts.tsv.gz 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a904528d-1f51-4602-a983-76cb4920fc27 db97ee369a866794780eac57d9685511 3441368 +d3ea89e6-cc7f-44f7-8c46-eab4feb9e6b0 77bb7e67-3468-494a-9f34-b139d7767bdf.rna_seq.chimeric.gdc_realn.bam 7ed40f4305267c91d94498dedd910495 132762706 CGCI-BLGSP 8a678613-f77d-45d1-9c13-8595e55e8f27 049aec5f-5534-4eea-9cf1-6a11906088a8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 9b875baf-0736-4323-a633-19d4c8ef24ec ddf949d8d3c6ca1e5124d19cc419e19c 139947118 +945aba11-6b40-46c8-8e3d-e57e1b720e9b 7079247e-e36c-41da-a6b0-d88d1028aff3.rna_seq.star_gene_counts.tsv.gz 2b3ff57929cfe9e02a8754a9ed23de9a 406523 CGCI-BLGSP 1835faa5-5758-401d-9007-17b1abaa070a 30d86c6f-e16f-430d-8051-40dda78f0cea Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts bdaf2215-ecba-4481-82c3-2f35e365b601 c7393414c8fee1bbf3a9ed5d3c37ee18 4226821 +55610ee9-aca4-47ad-b916-80ab95856851 8897275e-35bf-4693-9d6d-c567633ab739.rna_seq.star_gene_counts.tsv.gz 2020cc3d76a808e736e0d4013b42efa2 412385 CGCI-BLGSP 92194f18-046a-4222-9409-679b8872e6bf 4be4fb19-b505-4de7-b26b-a4fc582b3b8a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 08e745c5-a786-4b18-aae3-486d9e1c9da0 077cd36128fa8b0d4fcfe4b297682b64 4230879 +6c87274e-d685-4a9b-aa11-d227a7fb226f 295d4254-9cc0-470d-b118-2201b17aea2b.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 39dce88d-112c-4a3d-b2d2-11e0616594d8 46a48950-f657-4a52-8b40-436aebc4defc Structural Variation Transcript Fusion RNA-Seq STAR-Fusion a1d9501e-715c-4fae-bc6a-c9740f8b1f89 6e5690795ff424264402ab9d2661b62b 229 +1892a213-9440-4ea1-99b5-1e0ab5d11d36 8b4c12c4-8cc9-425a-b905-141e2f800c82.arriba.rna_fusion.bedpe 1519e650b043b83d052b42573009f300 7217 CGCI-BLGSP a349d361-885a-427d-967e-cacf830bc829 d5b61e46-dcc8-4bb8-af82-28b0837e6200 Structural Variation Transcript Fusion RNA-Seq Arriba fc54a69d-dbc6-49a1-8d3b-b65f2dc6f3f2 b059db2632cf08bbf5dd2f949dae1710 6660 +ee74486b-c43f-4acc-a982-b8af61a02017 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2-Pass Chimeric 5681a207-7f81-4b52-8435-3f38a938889c 179d876d08764e5db9db68b6b8d78a3f 135025823 +eabfc670-ddf3-4d2f-830d-830087accb63 0186c448-fb61-4429-b9db-b8feb72f4709.rna_seq.transcriptome.gdc_realn.bam 506aaafaff5989b599b5b7a25cd0ee7e 14400345086 CGCI-BLGSP 75664f55-936b-42cc-b0ed-f219112c06f2 ccbfd547-c8e6-44d1-a013-69ff6428e655 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 8dd73f93-5497-449e-89ad-e664be97bdf5 a641460b5ba25ca1470a7e06cdbff16e 17639136688 +5c2d25b3-e369-4554-9750-3f4868f47e35 02eea485-625d-412b-b45a-458d87b1a866.wgs.ASCAT.gene_level.copy_number_variation.tsv a9bd447663e3097cbb1593192124747e 3482752 CGCI-BLGSP 213e9f9d-7340-460c-93a3-edd559b42009 34df5fa1-a9fd-4a0d-99fd-34a056c164e2,bc184aff-ea8f-4797-b965-8b1f2da31103 Copy Number Variation Gene Level Copy Number WGS AscatNGS 91585617-6bf5-4ee6-aea0-d08effe1b7c5 90e5b880a948064cda811f44c92f3399 3442745 +398b0119-f508-4636-9a8e-cef444ee719c 8ef85e07-56cd-4588-ae08-7d7e7d46c58c.rna_seq.transcriptome.gdc_realn.bam e2f876e9eb572d58a93a831b4c7487a3 13576940613 CGCI-BLGSP 6c957218-bef4-48c6-9c8d-0352dd8d6077 c345daff-b4a7-43b4-98dc-406cd3ecd37b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 4173c02e-ae30-43c6-a27a-9a4ee2ccf6dd f85922d92783b5608e1be51fe107eaa8 17005849762 +009aa927-53aa-4a66-9ead-1b576967f89e c4ecb0d7-a009-400c-899f-4e820d6e7cb6.wgs.ASCAT.gene_level.copy_number_variation.tsv e09fe0de194e33abd718a66ada27496a 3482758 CGCI-BLGSP 0ee808be-13bc-4d15-a519-e2b7e960e809 3a8ddbdc-f477-4704-8f17-2637723b0cdb,d3502b23-9cc5-4199-835d-eaec008b49ea Copy Number Variation Gene Level Copy Number WGS AscatNGS 4061aada-a284-4ba0-84dd-b547a8edf2f0 fe6295507494cc3882be72ce0b57e886 3442751 +29edf114-22a3-4c03-9688-c5b43bdd3cab 9c399209-a9a2-41de-887d-ea30949fd78d.rna_seq.star_gene_counts.tsv.gz 67b3a753f1d81d5d04ef3b38346745cf 409750 CGCI-BLGSP fcd39a3f-169a-463f-8153-17ebc1b218a8 4db256e1-290a-4c7a-8852-c4f2658a2869 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 9d467434-e9d3-4bfc-bf40-39933ece6198 d8a03fc112448a46f3fddd1cd9af9b1a 4232146 +6fd27dd0-74c2-4479-8d41-24f354880acc 362a1ae3-1344-445c-8c05-5b36c9c123c3.rna_seq.chimeric.gdc_realn.bam 7f0aceae36507bb70e78587f42316a6a 89277387 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 2ee24626-72ed-4070-b034-92f88e7659c3 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 5e93d8eb-3178-4151-a45e-0415f40f7da2 c1a7cc044e7d3dbd8d8f4be9bd1402ab 92790345 +07679053-24f9-4c83-b128-7b4c38b58bbd 0186c448-fb61-4429-b9db-b8feb72f4709.rna_seq.genomic.gdc_realn.bam e8a33a606611330ee11d8b640950d950 20088660589 CGCI-BLGSP 75664f55-936b-42cc-b0ed-f219112c06f2 ccbfd547-c8e6-44d1-a013-69ff6428e655 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 43fe8553-d896-4b47-a17b-5fd8873793b9 f1b5c3881d0d31babcab371aebdb37f1 22853599895 +5c4998b3-d0d5-4f04-9a90-befe7f75348d 8681b858-9dd1-46c8-ab9b-831ddb9e5273.rna_seq.genomic.gdc_realn.bam 892d8099b1e6f7d85764ddb7a435a658 13342639119 CGCI-BLGSP a21b8ec0-1c09-48cb-97d1-42ed0096964a ce98ff94-58d1-4cd3-b08e-d98cd37d4afb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 8b7c4862-289b-482e-8c98-195da1837bf0 ecda8991047880fae9b3bfe57d2fb3af 14451888307 +14534f03-ea77-440a-9c06-c5341db9d3b7 f0ee0712-8bad-4a66-a231-8478a2021d68.rna_seq.star_gene_counts.tsv.gz 6ac70485238a362f12e068b552f48189 417806 CGCI-BLGSP 3dc70167-c921-4cfe-b784-20d22817532d 0e2e0e31-bfc8-4753-8c7e-fb64c5c36553 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 02228a43-3ae3-4581-ad8a-a66a887bb583 4bf1bec8f5667e12270a0bcda9bc3989 4238125 +c62a0369-96f9-4bb6-ad98-927e9cacf4f5 adaa31b1-0313-4317-8b9a-923a5870538d.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 2ef3e472-4a43-48a5-917f-c336194c0373 2c08a179-af12-4e94-9145-08633e55c0e1 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 84ddbd57-4950-4648-9664-47077a063774 202a871b5331368457ba8cf9718937b7 885 +582e7130-3336-4f0f-9c62-2531e1f402fc 6e86852f-e6d5-47ef-b882-d712eaed45bc.rna_seq.transcriptome.gdc_realn.bam 202d6c97239865408706f7dd836e8df8 9990232293 CGCI-BLGSP eb6e891a-b8ab-4261-808a-d543d1dc07d7 e2393e0e-5506-4017-8960-6df5d3248e0e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 57f73f49-9a1b-42e3-a2db-d3784c69e252 cbd259fea998693d0738617241b0ea05 11869844358 +bc7dacff-7e44-42e0-8687-a6b3b154ca65 cc46e3b4-c4a3-49ad-93b5-e0f8cc3bf3c2.rna_seq.genomic.gdc_realn.bam 036333fa4d37d9c02817eabe9af6f162 12090442803 CGCI-BLGSP 8eb3f8de-84ee-49cd-ae33-5cdc3cbebf3d 0fd505be-a785-424e-9a45-02d31e014793 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome b6ba345c-7acb-4732-a5c9-d0b3d748ca87 e59e0defc6dcfe26c9073cede31e7507 13075771310 +61a04cf6-919e-4e3a-a2d2-2214779f458b 41d792ec-2b62-424d-9cca-9c2129c68168.star_fusion.rna_fusion.bedpe 61fb26f20e06a50f2e853b811c00af5b 507 CGCI-BLGSP 9faf1ba6-1cb1-4195-954f-12919f0aedc9 57d71bd1-1c21-4b56-b781-a600b24a03f7 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 02777654-6db3-4c99-9d56-06046f36e3be 6e5690795ff424264402ab9d2661b62b 229 +b2b85d0c-f715-46b3-8ffb-e9ab4ac5df97 edc35ba3-8c13-4bbe-b728-100ab3ddb597.arriba.rna_fusion.bedpe 7090726efe479d02050e709e1917929a 4875 CGCI-BLGSP ceeec59b-7f6a-4769-b75b-41405c41e177 8967be7c-33f0-4127-96af-4ed4cd98303e Structural Variation Transcript Fusion RNA-Seq Arriba ef39db69-6437-4a9f-a76b-e867bbb44828 ff55768d07a50977e6e2a4e8dcbb6f46 5203 +ce440aaf-f6bd-4608-8370-889292a8fae7 fc55d867-a627-4c87-b50f-fca4d76ddbe1.arriba.rna_fusion.bedpe 7a8f084f5f74223f701f63bf0077111a 4313 CGCI-BLGSP 8a678613-f77d-45d1-9c13-8595e55e8f27 049aec5f-5534-4eea-9cf1-6a11906088a8 Structural Variation Transcript Fusion RNA-Seq Arriba 18035892-e4ae-4c1f-8743-27f4883a1548 9d0a09b2858e68c2b9f7fd27e88261ec 3709 +6d785504-8bea-4f5e-bde5-4ebd5d6e6a96 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b22f49f9-0ef0-4d4d-8a6d-34391cca02e0,8a43d359-134d-426b-b338-1eaf0456de7e Copy Number Variation Gene Level Copy Number WGS AscatNGS a754bec2-3817-4e89-87e4-112a1ae0c5ef 2ebcd35ecb35efd335e773541b006e82 3442760 +acd21d20-de68-4908-90bf-f456bcd69e8c 3ac3d8ea-3d8e-4ebf-a936-f6f177037ef8.arriba.rna_fusion.bedpe 0fe7b5659beff9ed5b9aa785a99b32c3 7731 CGCI-BLGSP d4524555-0c72-4c58-9203-2223e1c1c211 8cad1bc8-8275-4443-b6f5-74a45e133011 Structural Variation Transcript Fusion RNA-Seq Arriba 30f77848-595c-49e2-b4c1-cd436e1b08e0 1db96e653a669e7bc0b03b40e0911df2 6866 +884fdce0-34f8-4a9d-a9f7-d1919dcc6a6f 5e74ef77-948d-4ecc-a1ba-07010631daeb.rna_seq.transcriptome.gdc_realn.bam aaa2071ce644be0e994539bd645269b0 9508537450 CGCI-BLGSP a7dfd3c9-4b94-4802-97c6-a096b276aeaf ac110d72-7f92-4581-a859-91e34e160825 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2c33909b-1e89-4986-802e-adaf6a4d5155 a4b65d6a27f378c94584872f199e9488 11102711545 +eddaa7b4-8d6d-47fc-a332-ba17de2d9b7c 2a3f6588-b301-4c8f-955c-c4607000b36a.rna_seq.chimeric.gdc_realn.bam bc5fc372550eee84da8cc18c1c2346d7 156647947 CGCI-BLGSP 48823727-d7d5-4efa-b374-17e3cfffad91 79528e46-4e76-449c-a35c-25a97ae31f8e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric dc54b42e-5976-4a40-ace4-d7f9fd315e02 849afe411c489e7d3789b622245f39df 163238403 +10ed3d55-960b-4e73-85bd-e119541a46b2 e1ac94bb-edfe-4785-8ea0-7919f374b0b3.rna_seq.star_gene_counts.tsv.gz 7604582470fbe3380afb732d7845616b 410604 CGCI-BLGSP f4a0bef2-c397-4149-830f-8d5f62e1b5e8 39eeb322-1c7a-4859-8c3e-848e0f83233f Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 4d0e6390-4585-413d-8c7e-446890c61b12 37c9266b6e27fdf1de44ff86b563e487 4226873 +2aa13267-1819-4b9f-a426-470a18221437 122ac1b4-5181-49bc-9a37-773abb21772b.wgs.BRASS.raw_structural_variation.bedpe.gz f81991d8ad9dbb3bd4daea1f20fac8a3 11968 CGCI-BLGSP bcb4326c-3c7f-48e8-837a-b43bb2535a0e 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83e5f3b6cd486774376c2f2ffab0d948 2941609 +43ca71e7-2317-4118-890c-3b0e66df0114 8effa2dd-dde4-48ea-8c52-fbe799f1a83f.rna_seq.chimeric.gdc_realn.bam a5986544847eca8c4c882b9c759c04fe 118827907 CGCI-BLGSP f1e5c114-3957-4667-88bf-f7821c75e43f 65122907-b42f-4265-bacb-007f96424e38 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric fc761692-541d-4437-9c55-22674f3994d5 63f663b3785dd587e3b5fc7e237a7960 122966286 +f75c52a8-eac1-47d1-bbcb-0db441d404e4 d5d42073-bfc6-4f5e-b350-180bb27a308f.rna_seq.genomic.gdc_realn.bam 6c108b6ec52979a4b1658e8a01e16846 10144069001 CGCI-BLGSP 7c0891c3-7ddd-460b-a8e7-b33a63844ed1 14ddc614-f974-40ae-99d7-5827f7a6ae6c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome fc881df6-41fd-4b7c-ac86-6efe8d38d24d 2d9baa50e8fed622ca518a4ca9ff1d85 10972535974 +241980cf-9e55-4920-a8ff-a9453bbaa83e 211b710c-7f11-4330-aca0-7e8557e99eeb.rna_seq.genomic.gdc_realn.bam c023d9f4c78417056e2284f1b789c5d8 18055377848 CGCI-BLGSP c9e0f3c5-f996-435d-8d2a-d32420aaaf9b 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RNA-Seq STAR 2-Pass Transcriptome 0cec5071-3011-4433-9aab-fa63d87f3d8b 649b275e522cee1e619391be7d2c8b7a 15700781170 +2039dc40-3bbd-4a0d-80c0-796fd88132d5 4237f8ef-1d72-4a00-8d98-fa2229832198.rna_seq.genomic.gdc_realn.bam 6ef54bc60bdbdd17426205e8896808ef 12426956622 CGCI-BLGSP 9faf1ba6-1cb1-4195-954f-12919f0aedc9 57d71bd1-1c21-4b56-b781-a600b24a03f7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome d9366ef9-76a5-4797-a4cc-541647de1fb4 87b74b688413dc168f69510cafd3f0c4 13369035447 +a8cef441-75df-4052-9f5d-efd8878a0955 77219c47-eac0-4254-94bf-b9a6f5dd6dec.arriba.rna_fusion.bedpe 96261d198186378a56553a7bffdb7889 2330 CGCI-BLGSP 8eb3f8de-84ee-49cd-ae33-5cdc3cbebf3d 0fd505be-a785-424e-9a45-02d31e014793 Structural Variation Transcript Fusion RNA-Seq Arriba 3465b8d4-13fb-42bd-b011-f7063db226df 2d3965a56411fb7a76b45dca6b223ad4 2326 +6c11b032-7b58-4b7a-96cc-5228d9ed666c 6c651267-da4c-4bc6-8cf1-0ced245d2c61.rna_seq.transcriptome.gdc_realn.bam 6ca84f791651dd587011dc37047dacf3 15006938319 CGCI-BLGSP c3f876f4-2d3a-4d60-b6c4-019f94010330 d97c5d68-2b6b-4a8d-b76f-f8d921685625 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome d1459519-1a7c-49a9-b30e-70f9992110af 3638ac9be60c2e0e51e6e5903919fdce 17705833304 +518f795b-7e6a-4c03-ad64-223a0e95d67c 6236b0ef-6d23-4883-af4c-3f9639574079.rna_seq.transcriptome.gdc_realn.bam f3b1309c2fd79ea54eab045ce699c4cd 11274720310 CGCI-BLGSP 557ad893-cb31-4fd6-bdfb-7f7930787dec a2ec82e8-7c6c-4f2b-a80b-595b6fb24409 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 460e593e-e13e-4e76-a714-c100a1b35775 64be54dbe8a1520b22c595ab2075f616 13411038875 +d0bba5be-4265-4099-9992-b25916edbccc 5aac12bf-60bb-4767-bf72-8ed31ad94b8e.arriba.rna_fusion.bedpe 1ce67830b5df1b7dfdea62a8d08a18c0 9579 CGCI-BLGSP b22261d6-12e3-464d-99cb-da3ae8ba6ba6 9d34db0e-55a8-47b6-8de6-2522c926a463 Structural Variation Transcript Fusion RNA-Seq Arriba c07a23a4-c4da-4e63-9f60-435ee20965e3 636f7da627debcb64291d25744b00835 8309 +c2dfd0fb-002a-4b0f-b1c3-d74e7f2adcfa c8143bd9-0b2e-4ff1-a9da-f0ff1f3ff97c.rna_seq.transcriptome.gdc_realn.bam 5a987c9018dbb3055278b510f0f9b958 16154484411 CGCI-BLGSP f9ffbc74-e1c1-4579-8465-cb2b96a1200a 4f8933d2-6f2b-4ec5-9415-c647d2c56193 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome dcabcc72-f270-4d95-a392-7eb76587bdb5 a66870a600cfebc5615546ed894fe3a3 19787693425 +df673d13-bbe0-42e3-bf75-41ef95038c5f 6a1b5ba5-514b-4041-8940-b126e3bfaaf8.rna_seq.transcriptome.gdc_realn.bam 63686ace7dda98d04318331bcefa3a87 8840418673 CGCI-BLGSP dbfd839d-5c86-48ad-bdeb-d83d81584356 66414f98-5f89-440e-a2c7-eeedf298eae9 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 1f9db2c1-7728-435b-9656-e1be782f85b1 3a373a714c354ee504440f49fc5d70f2 10644804052 +175b2a0d-2c14-477d-a073-9a0af72fc317 598883e4-59de-4ca5-98f6-f5187f0bd8a5.star_fusion.rna_fusion.bedpe 197ec39b1e550e42ac18989f76b28b3f 473 CGCI-BLGSP 39118490-7870-41f5-8b56-d0ee38fa8bbe 51efac8b-56ad-4952-b710-56d6f486b7ba Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 528efd5a-dfc8-4d65-9920-66221a5b0c3c 6e5690795ff424264402ab9d2661b62b 229 +4c0690d5-cd53-4698-a4a4-7c141f7ba815 29f449c8-ad7f-4376-a683-1ad75fa31709.rna_seq.genomic.gdc_realn.bam bf217783cffbcc1460ba77d695b09a83 19197337253 CGCI-BLGSP c96f21de-3dd6-47ed-a796-6270c1817dd7 353174d3-4bd6-4e08-8234-013da78fc871 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 7fac98eb-8cde-4cf7-be38-30c8357f72fc 1d03853f0390941567a8976d31366f74 21004738685 +b845ce20-92d4-4a2e-b6f0-9fa2ac9d32b7 4d232b67-bfbe-4006-b665-879039d2c932.wgs.ASCAT.gene_level.copy_number_variation.tsv edbaf6696eee988fc73d5f00029bf9b3 3482761 CGCI-BLGSP a349d361-885a-427d-967e-cacf830bc829 57fb53fd-966b-4a7e-a033-2f99e759a720,a9882958-7d76-4fc1-b0d4-2617dbe2a1d3 Copy Number Variation Gene Level Copy Number WGS AscatNGS e826ad58-b589-4a00-8d2e-d109c9a03c8e f460f3b44f44a71d6399cf2375362a15 3442754 +8f46b191-b1d3-4aeb-ac98-1ab06f883ed6 6dc7b4b9-8209-47ee-8b94-48815ab7e5b2.rna_seq.transcriptome.gdc_realn.bam 7d1327fb5fa03c98e0ad0ad8dd6fbe65 13111237589 CGCI-BLGSP 32ca8921-9f22-4854-a451-b98f10513f20 c65baac8-2a69-4654-8e62-6d1f113ffcdd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 03bc9f56-37af-4595-a620-99d30f4ae126 ecc17b0b2b3c9be0f73383fb2daf9198 15923207948 +440c58cb-42d1-463c-ae85-4193009d71b1 6336f906-f26e-4551-9950-9eb5d3aded71.wgs.BRASS.raw_structural_variation.bedpe.gz aeada2402d975317c3fec8cdaa7a719e 9786 CGCI-BLGSP c3f876f4-2d3a-4d60-b6c4-019f94010330 ed570a86-0714-45a7-aec0-f197e962ce59,139b8f7c-96fd-455a-b6fc-e1082fce1e37 Somatic Structural Variation Structural Rearrangement WGS BRASS 6c52bbb3-8d67-433b-ad28-8f4d3cc659b9 56d39a32ef64ac7b4d83bd745a68e563 34462 +925daeb2-c9ef-44b0-b2e9-0cf009eb09a9 35663093-9322-431f-8799-746ec1be253a.rna_seq.star_splice_junctions.tsv.gz 6de0450f20c93e6e13c3df00dbcb607e 3223235 CGCI-BLGSP 7dcc3723-aed6-4d2f-ad8b-afa443634139 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1ac1fe2f-82a7-4b0a-ae4b-0dfb63b5fc1d a8325d45c115fd921a3966ee451181f7 1742 +143dfe39-22a4-4695-89ff-485cb943fc27 a07ebe99-d21c-4b2f-9f12-11ddcb56701e.rna_seq.genomic.gdc_realn.bam 1666be278577d4b452f5e3671ff4f352 5719093089 CGCI-BLGSP e90aedbb-8398-41e3-9bfb-df17f91c1eb8 258fb876-8fa2-4c9d-b8a0-b2ad7ac27962 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome ccf16459-4bda-408f-a977-e73a94fa2bd6 0310a02e9192874ea68a4d41a95c0175 6017688378 +cd5050f3-1398-44c1-b612-f7d352b5a56b e2c2f95c-3f1d-4fd6-8faa-9f9d73054eff.rna_seq.chimeric.gdc_realn.bam 58036b326b750f5a67ce8fed87db4748 134857854 CGCI-BLGSP ce4274a3-7c59-4392-aa8c-14f4d2c134fd dabc4596-656f-4132-a65f-d9bdb0ce432e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c23b009f-7904-4d11-b1a4-274f7c574a49 ad4b7057398d07df1b7d28f71fbbbdb2 141823687 +55fba0a2-6920-4671-87b9-8df72711ef98 626f800d-63fe-497e-b5c1-d45ad837c82c.wgs.ASCAT.gene_level.copy_number_variation.tsv 51cc41e9e45572130329074786be3294 3482752 CGCI-BLGSP 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bf9aba1035b6e76519a52fd1b0deae9e 3170851 +dcb949e4-5c0a-46b5-8ed0-288b1742940e 351712ad-9254-4175-9ac7-f0d24847ac9e.rna_seq.star_gene_counts.tsv.gz def17ebe4439f37f09b160c3e8f9e055 414700 CGCI-BLGSP e0ca8db8-b71b-4a63-96b4-96d368cc4fd6 9be49a9b-548e-4214-b553-156bc083f9dc Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 87f9a64a-15be-404a-82d3-2110af817c06 9a0719e03b4ce307ed78215c45b7c982 4235804 +f3294e99-1be6-4b80-a9e0-b4d796e23338 94624811-7716-4ae8-bc12-d36129bee6e2.wgs.BRASS.raw_structural_variation.bedpe.gz 9f32479028b4b7dead51f240058d9284 10399 CGCI-BLGSP c2282c90-795d-4c90-9c4b-51e340f98ac4 44178db9-61fc-46df-b0a0-b15ed4b9b757,fc14b753-ac6d-43b4-9521-a56f47f9c109 Somatic Structural Variation Structural Rearrangement WGS BRASS 29a11b74-cbdf-4b2d-8710-3ca9d880fcd6 506fece60d904754f69cef443434c2ac 36543 +50e44335-a7be-4d27-8e41-c31afbcd32b1 6c651267-da4c-4bc6-8cf1-0ced245d2c61.rna_seq.star_splice_junctions.tsv.gz 88987a9167a957f3442f8361c821666e 3508227 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6ec4d872-e00b-47a5-9cd7-b095e09f8e4e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 7c9a81ce-4575-416b-96fb-99840d5a2ebf ca64d3cc326f86697bb9aeae54f161f8 3125426 +24298293-0c39-49ca-81b0-c9d8d22b26c7 c5a5a7cd-969d-42f6-bb58-2e438566fe59.rna_seq.chimeric.gdc_realn.bam cc80226777832e17bd130d7530222a0e 322815143 CGCI-BLGSP 7277e644-f3da-414a-9821-8037cc99ef9f 0632bc4c-43a7-4651-b18b-c813b214190a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c6a88e11-123c-4ddb-ae4a-4038388bae22 145dea7ea1eb94df17fd0861680b2bf4 334993145 +df86e3ee-5ea6-4261-9759-2e630a0ee59f 674e747f-4ae6-4fcb-af7f-1ebbd05f2820.wgs.ASCAT.gene_level.copy_number_variation.tsv b820c84f178661916f285786f924fdc0 3481153 CGCI-BLGSP fcd39a3f-169a-463f-8153-17ebc1b218a8 7eaec814-8ca5-475f-8f84-a1285277adb9,731c7b44-04ac-4f34-a6e7-faa389c4fc03 Copy Number Variation Gene Level Copy Number WGS AscatNGS 0407ce8b-79d7-4295-9f31-25edf398fc48 b06b4b691eb2ef4a036dbb44a8f97099 3441230 +1b1c903c-102c-418e-a3d4-da29d9be1306 693f76b5-6d30-4bbf-85a4-f9e6f43d5f70.rna_seq.genomic.gdc_realn.bam 7caf488d419328b479c6ca335488305d 10082130767 CGCI-BLGSP f90e6333-f59e-4f6b-b7f9-17ba10e4a600 f9627688-8e25-4ede-bde0-8da01ed7528a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome eb2c07ac-021b-42e0-9982-116ad83024d7 ec843c34d6812a856234d899ed463019 10901818716 +b145bb70-859d-410b-8062-ce46679e7536 c554ed70-9e88-4392-8641-28bbb83362dc.rna_seq.chimeric.gdc_realn.bam f0a8a4fcab0a63a369f537740c66e916 108092186 CGCI-BLGSP 13c615c0-74b2-4b41-9a05-b8a71eca0685 88b60fb0-18f1-413c-860a-f057bb371d47 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 11185c31-cfa1-4cf5-8efb-b3609b6365e7 883460c990cc31b49d08b7a5a7a84e21 113486503 +e513aa0f-2e87-45e5-910a-bc9cb482114f 6dbfe951-5262-44b2-8f31-837b6315f36c.arriba.rna_fusion.bedpe dabf1613b4e1fb594229eaf68b324a21 3034 CGCI-BLGSP af918a1b-56ac-4ebc-af60-b0823023c185 aac8c165-4613-4ff1-a6a0-48229c398010 Structural Variation Transcript Fusion RNA-Seq Arriba 4d582454-07fb-432e-8068-040001d66dd2 fbaa84ce7d25abf6843e5ccebe19a060 1671 +11ae8545-b5ae-4649-8f75-403ee5dd5671 c5a5a7cd-969d-42f6-bb58-2e438566fe59.rna_seq.genomic.gdc_realn.bam f4e836767970fa576a0e341bdcad87d5 21928571647 CGCI-BLGSP 7277e644-f3da-414a-9821-8037cc99ef9f 0632bc4c-43a7-4651-b18b-c813b214190a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 22cef349-3b91-491b-9630-bdee4614b3f4 025cbb33c43cc1114508dff1f23afb06 24564914463 +3706d969-86a7-4d1d-b11d-2f6ea2036a26 7cbdb45d-e8f9-4030-a60f-61c7e51cd354.rna_seq.chimeric.gdc_realn.bam 9e50cd40d2bb92b9c977d9fe6ac09a88 260546515 CGCI-BLGSP 3cfb178a-c476-4c0f-968e-55c57239e7c7 b213a7b6-e60e-4edd-8f6c-87f22fc44ac5 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 50bc3542-3c84-48b1-ad3d-ea91b364474b 4c8f0192012724c5ec07a36f08d29e63 282012406 +54b9b0bb-58a1-4105-a891-11fe2f13030f 12e7075e-b2e0-4b2d-bd09-93776aa4f8e0.rna_seq.chimeric.gdc_realn.bam e74009ac91518cb1c1e1f04df0c6fc36 207858770 CGCI-BLGSP 2843599b-b36f-460b-8563-2e022974103f 2d9d9b48-419d-4082-827b-d1bff8e6f216 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b15603c9-6b30-4e1b-ad4d-3dfe970b2a1c ee14a1eae0bab6f5e0bfb1c25ee37210 221539699 +cac82c2b-6f9f-442e-829a-65f8519e8fe2 8a3db64a-0530-434a-9ec7-ff4e43a6c08a.arriba.rna_fusion.bedpe 4d457bed1c985ff2e196f86d8bfdab01 2744 CGCI-BLGSP d04504c8-766f-4829-9d11-cc32f3052f63 5cb27d44-2c43-40c8-a294-f952ba67f0ad Structural Variation Transcript Fusion RNA-Seq Arriba ab472556-5463-40af-807e-9fa253b50558 9536fbf692fa56102fc76aaf6cc405e2 1631 +952cab5a-f241-4a15-9e42-3a3f3da537e9 f7772619-ec67-4314-9b91-a55ce0b4a950.rna_seq.chimeric.gdc_realn.bam 6a49209b7f156e4e2bc82686635ad1de 335261245 CGCI-BLGSP 89989611-e08b-4731-912c-952c248a9b5e 2d3712d6-6abb-4003-bc7f-d0a3a145e1a5 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 54f89816-8efe-4ce5-bf2f-a065c1d5f4f5 a58144961fa6ba702505d642c5b5026a 348328153 +c746457e-1779-4889-ae0b-fccc4df96a89 19c8bf8e-a115-4747-96b5-351cd3a78de7.rna_seq.star_gene_counts.tsv.gz e2899e064f494f67c81f0779edf3a828 403109 CGCI-BLGSP a789950d-3cbe-4de1-bba3-00ee3e0e7a46 abe0a243-4500-4444-b31d-b23a28954c85 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 003c1a27-24fc-41f3-8de8-9ce029c60adb f8b6c1ad840516260457bc68d882dcfa 4224063 +dee438fc-ca98-43bd-bc3e-a723e9b81745 a6321322-5625-4136-b9c6-4a47faaafbec.rna_seq.genomic.gdc_realn.bam 72b57ee7a3dee71ae7db5d77a62b1e1f 15546169733 CGCI-BLGSP 7e0e68c6-4055-485c-8d34-651e803af78c 664580da-73ba-4af9-abc2-4f406999a1dd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome c15f924a-8e6c-4dcf-86e8-59e5bcca96eb ee3364f197c316e7d4ad9218d5226284 22446988276 +0942a610-85fd-432a-86dd-dcaa62511c3b 8681b858-9dd1-46c8-ab9b-831ddb9e5273.rna_seq.transcriptome.gdc_realn.bam 84af64c0512c01198640e64cf7e863a2 12219890231 CGCI-BLGSP a21b8ec0-1c09-48cb-97d1-42ed0096964a ce98ff94-58d1-4cd3-b08e-d98cd37d4afb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome d5bd1a5b-fe7f-4b22-886f-f400cbff1acb 8e0a2daa0c62637d9f57cde13c6de0e8 14763507681 +6d9a3adc-297c-4a8e-852e-4e5d3715cb0b 1fcf97b1-18b2-49d7-9fbb-e54c5cfa28be.star_fusion.rna_fusion.bedpe 6c8207e82695f47b4b3f05e9eae262e7 505 CGCI-BLGSP fcfdb847-5081-4086-8d32-25a281097390 2352a75e-96e2-4067-afc6-1d855f7312a8 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 78749463-9272-4fbe-b7aa-f6859d0ec397 6e5690795ff424264402ab9d2661b62b 229 +c5458d0b-bb57-4ce2-a317-2c912031e509 9efc49ae-2b74-4ec0-8db1-7385951f14cf.wgs.BRASS.raw_structural_variation.bedpe.gz db50d65a980a0174bc3de722de950df7 13010 CGCI-BLGSP d4524555-0c72-4c58-9203-2223e1c1c211 f41f129b-f020-46fd-8d4b-117c11188029,af5c6c1d-f921-4b5f-b3e1-9a52935f52a0 Somatic Structural Variation Structural Rearrangement WGS BRASS 3855d1b8-01ee-4c95-8be6-7e9b844c76f0 d9010445b695c8d00e832b9abbb0a6f1 44805 +dbd40476-f4eb-410e-b17f-9507aea639ce 4237f8ef-1d72-4a00-8d98-fa2229832198.rna_seq.chimeric.gdc_realn.bam 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6e5690795ff424264402ab9d2661b62b 229 +92935c6b-06d5-49da-b956-55cec6aa8927 8235d7c0-284d-4b65-b272-5a62e4fa6dae.rna_seq.star_splice_junctions.tsv.gz b8a93be66c3f96d09b789aebbb0b8fba 3550084 CGCI-BLGSP 1baeae6c-057e-4f47-9f8d-5d42aee5d3fc 503e33b8-a5b0-44f5-ba00-8eff720e3808 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 6078af25-3806-491b-b44f-6ab55d2d06dd bba4a6c29d97d096122a536cc17af490 3631428 +53595cdf-968c-46cc-bff7-8c230c62a10e 1124a66f-f394-4e29-850b-20767da0a266.wgs.BRASS.raw_structural_variation.bedpe.gz 42f89b7323aeba51a1a2f3b1fba15bda 10102 CGCI-BLGSP 90e9183f-7210-4922-a653-21c86e488887 eac92fdd-3814-4b3b-8f5c-7ce0915424df,512001d2-2c85-47df-ac2c-a5f6601b772d Somatic Structural Variation Structural Rearrangement WGS BRASS 6f98ae36-3e06-468e-ab09-24b49029dfad 81c2b2009f3d997d572ead9dfc8d1933 35273 +9c58ec1d-c65b-49a8-8e70-81f778f9b4a6 e6d84c70-15d0-44de-a7de-8280f5468abe.arriba.rna_fusion.bedpe cf79cdaddba5ed3291b327c1aa69b630 5097 CGCI-BLGSP 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2bc66ae4-12b5-4230-8d97-74461598f17e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c44f0d25-636b-4445-b06e-ef320da8a76f 0a9f208999b3717cba2eed1148c701cf 169102839 +e3313b1d-1253-4f37-85e8-c1f3495dbb65 06562a2d-a3c5-4f00-8efb-ab3dfa09242a.rna_seq.star_splice_junctions.tsv.gz abf873abdb6fb22c6e893a0f44f18044 3029286 CGCI-BLGSP 06c07e2d-a04d-4099-a29f-948e40558dd1 2e9ae889-acac-4f29-aa7a-a6584ba571e8 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts c7163c58-2760-47e4-8049-40a45c54771a 97f601f51eac336722d61d1928b811fb 3103525 +777ddca0-3768-48e4-bd11-436b0ee9bfe6 5b5681ba-d659-4ef8-948d-c4f70f86519a.wgs.BRASS.raw_structural_variation.bedpe.gz 38e7b147fcdc14e496565e3250bbc548 10611 CGCI-BLGSP 39f9996d-b217-4222-98ea-47c210d49e93 627a2e7a-47a6-4c13-b349-32e302030013,b1af34ad-f7a2-4af1-af20-a289418f271e Somatic Structural Variation Structural Rearrangement WGS BRASS c79eeb7f-4d73-406b-9e79-b17272a36d0b 04793f5fd8c5cf70e6f97b6965cee43e 36142 +be07084a-1922-473c-90f2-5c8186528b31 18dc9cea-6085-4890-b18b-549ad7068978.wgs.ASCAT.gene_level.copy_number_variation.tsv 5e0db1f45b32cd24d5fefde8bce44bb4 3482782 CGCI-BLGSP 2d9d88c8-d827-4bc8-88c6-75e0d0c3f988 a304ee5e-4e15-4a6a-8f4c-95c746a10fef,1e1a632f-4f87-46f3-994b-0c25a6bae1e9 Copy Number Variation Gene Level Copy Number WGS AscatNGS 2e6f875c-c23d-4064-8894-fcb57d69a4d0 742728f730cf76538fcf340ed19c87be 3442772 +dba4a784-91fe-41e8-863e-7636bffdc786 4df9936b-a399-4eed-b17c-a89811248d14.arriba.rna_fusion.bedpe 94c1e5e2a900c08ff29dc62ee4a2cdae 8029 CGCI-BLGSP 2e21d338-6ec3-423e-9f7f-8b61fe428c3b 4bde5ce8-b94d-4609-b0d2-5f8d8422f289 Structural Variation Transcript Fusion RNA-Seq Arriba d8b9ae99-4e75-49e4-8368-85c7855b1625 35aa9bfc0463b582c43be596c04a7ef9 6374 +33a3d5ae-205c-4f89-9761-4dbef43f990b b252b8b6-a0fe-4259-8a81-30ec8c72c89d.rna_seq.transcriptome.gdc_realn.bam fad6f2be9ef15f8f28f5ca1dcf4a3899 10116543732 CGCI-BLGSP fcfdb847-5081-4086-8d32-25a281097390 2352a75e-96e2-4067-afc6-1d855f7312a8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome bed19116-8e1f-4355-b4ed-7a03cfb5443d a3f2e5bfd8a225ea9404b0138dfcd4b7 12427591305 +b157a30c-709c-4bb0-9533-650c5f0ff3e5 4d232b67-bfbe-4006-b665-879039d2c932.wgs.BRASS.raw_structural_variation.bedpe.gz badda8a28474e41aebcbb0488a7e2636 13593 CGCI-BLGSP a349d361-885a-427d-967e-cacf830bc829 57fb53fd-966b-4a7e-a033-2f99e759a720,a9882958-7d76-4fc1-b0d4-2617dbe2a1d3 Somatic Structural Variation Structural Rearrangement WGS BRASS dba7666d-b3dc-4d48-bfa8-e7d5695fc2f0 72a5659483f83f87fb315829fa77c9b3 46600 +01d6d415-5cb0-40c5-9132-efc7903688df 2a3f6588-b301-4c8f-955c-c4607000b36a.rna_seq.transcriptome.gdc_realn.bam 4f29ec43f6c77b9be262e695062dd3bf 13336097540 CGCI-BLGSP 48823727-d7d5-4efa-b374-17e3cfffad91 79528e46-4e76-449c-a35c-25a97ae31f8e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 1a9e89b8-b33f-444b-8864-75cd8f159bca 49b111e23c91f0caf31c5b0fa9078fae 15863177072 +3a64bde1-e185-43f6-ac8d-9e353c9e90bb 3d6c3cac-ba03-4e9f-b7e4-d24596bf34e5.rna_seq.genomic.gdc_realn.bam 757434688eed6d251d7fb12c3d1dfff8 13977434474 CGCI-BLGSP 69cf7ff6-fcb3-4177-82a0-5a589073e4e6 60ae79dc-769c-4c0b-a0aa-3fa99176c596 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome cf32ca13-ca49-4a60-952b-2d0062e86cc4 8e46ddd3187c552c4547326153f206d9 15311411530 +bffabdee-a7d2-4c8a-8c5f-51ec978e50d2 f433ab2e-0646-4549-a7dc-1078223831d1.arriba.rna_fusion.bedpe b3e12307d4e3bf17633af65267b3cfe8 5174 CGCI-BLGSP 681ff2e8-6073-4dab-a398-1f2203c2d7f5 8cc05c59-cd01-4998-a1dc-30d8e13c2956 Structural Variation Transcript Fusion RNA-Seq Arriba ee242d45-f9ae-481d-a4c7-1c53721a5ad1 b0c4e48acca831d77468a6b245762bca 5145 +6bbd9093-535a-41c3-9d94-3c4b086e2c28 b84fc850-bce1-40d4-962e-46a738da48d0.rna_seq.star_splice_junctions.tsv.gz 949afa98fc4e39685df84a7268f7217a 3089687 CGCI-BLGSP 4b3049a4-2d42-4f9f-be26-bcb02b3aef04 06b696dc-ec61-4a82-ab41-e35255ba07d1 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 945ff8b8-54c7-4e01-b350-59fc05711504 556c04302b8a5a7b86464d6bfb6a40ae 3161899 +3cb9c015-52d3-4318-9da1-db83d8f76d80 f0ee0712-8bad-4a66-a231-8478a2021d68.rna_seq.genomic.gdc_realn.bam 07e21f98a11879f69b80c554a4e509da 14352163720 CGCI-BLGSP 3dc70167-c921-4cfe-b784-20d22817532d 0e2e0e31-bfc8-4753-8c7e-fb64c5c36553 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a4a321ef-6187-4fca-8e02-db9fe8f06432 8e47118e5b5b41894f5217b03e916451 15747072893 +d3c2186a-bc93-46f7-b4b6-405826f26638 362a1ae3-1344-445c-8c05-5b36c9c123c3.rna_seq.genomic.gdc_realn.bam 2b5c55ed11ea6e2f6d863a72bd1b0a65 10866825997 CGCI-BLGSP 5eae99a5-85e1-4a49-ad71-7b9c78e7fe67 2ee24626-72ed-4070-b034-92f88e7659c3 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 8d8d55d6-7d98-4823-9140-3a0ddeec33ce 8f7093af6b166477a2ddd906fdd0d438 11637472105 +3a92c80c-490e-4783-8685-b970688ac8b6 b35364b2-90f1-4627-8735-e9ddc8e2ac2a.star_fusion.rna_fusion.bedpe 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STAR 2-Pass Chimeric 6ca672b5-3269-4574-aeda-ec98d71f0fd2 4846147bf9e081daac34258fba2de998 155503064 +23c5e333-e17f-4fc8-b550-3f7f1f7cacbb 84b0a6bb-18df-428b-915b-f7e884751db3.rna_seq.genomic.gdc_realn.bam f17d1c983d74da6057014766ac284260 19016539010 CGCI-BLGSP 0ceb3081-4c6f-4fd9-9535-5accddf76bc4 bbcefef2-c5b5-4c88-9058-dd4ae2200d41 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 992ef81a-861e-4ca1-a9cc-b3f68fe06777 90c86373cb54ed7889c80833f0244b69 21293547906 +1abf3a20-12c4-4e1d-a04f-91a09b20e558 fd6bc18c-72b5-43ca-adea-cb9f688347a4.star_fusion.rna_fusion.bedpe d359bc16cb1b7b857ea080c20bb1b3a5 743 CGCI-BLGSP 2a587474-c6c3-4322-b1ad-a11f2d205bb4 79288db5-aa59-4656-9955-d59272d4f7d7 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion ada46cad-8b2c-4e41-ae76-f26f572ef2c3 47f5424ad252dee2593f395a00773e7b 665 +0eabc3f8-342f-4e76-8646-f6dd9ca6c28b 6e64b058-2a75-4668-a722-2e3abf3acd42.rna_seq.chimeric.gdc_realn.bam a10a045076b657dae51e59be80d1bf52 114661241 CGCI-BLGSP 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0632bc4c-43a7-4651-b18b-c813b214190a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 308d2d45-8454-455a-b2e3-2b67d50eeb63 4ad57328f9b309b9e1286ea672cf7ff3 4237656 +d3ed1533-fcca-4010-8f08-39d5f10fc67d 6f27310f-b158-444a-8eb9-bae58c68be53.wgs.BRASS.raw_structural_variation.bedpe.gz 8bf1f6cab55d731adc049c3606eed03d 8122 CGCI-BLGSP 32f687ba-28e5-4efd-9e27-5835f6416fb4 a41f282b-1254-4377-bfe5-d77d1b36bf40,6c019f23-8fca-4685-a5e9-3a376da65500 Somatic Structural Variation Structural Rearrangement WGS BRASS 90fa5137-a9bd-499e-addb-ec4d74a886e7 93228bc5d17b81bd9f6bafd5d6d9ccc5 29027 +013b8865-4457-4b0f-a1ec-117651ceb7f9 379409bd-a918-4479-8635-9aee6bd8e4e1.rna_seq.transcriptome.gdc_realn.bam f0c887318f086f2ec7e81799ca576d46 16684739861 CGCI-BLGSP 90e9183f-7210-4922-a653-21c86e488887 a244ceda-46a6-4461-8506-778e4ec75e2b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome abd10077-ba57-45e2-99fe-5ad9e09f1362 18ea14b3ad7c0d57b1360794307b1f76 20111851254 +fc1224fa-f9cd-4d38-b9ce-cf0fcccc4058 211b710c-7f11-4330-aca0-7e8557e99eeb.rna_seq.star_gene_counts.tsv.gz a40fb7043f3dd60fc8989e9454b50d04 414025 CGCI-BLGSP c9e0f3c5-f996-435d-8d2a-d32420aaaf9b 9450c716-a971-41f9-8d90-b8bab953de39 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 6f743522-3e6b-4416-aafd-3130434893db 785d713949234dce96f41337b34db5f8 4234891 +e1bdbaf9-eadc-4f4d-a085-b8a54ce676e3 6e5ca9f1-5079-42b4-9d8d-c84e1f99ea96.arriba.rna_fusion.bedpe 47c25222018a48ce5b170a8e16306cbc 1883 CGCI-BLGSP 5fadbb10-de7f-482f-8460-54d513b5de89 38d43672-4e34-477b-a2dc-9fe1f8cd450e Structural Variation Transcript Fusion RNA-Seq Arriba 3c597aad-b0d0-4741-98ff-5d230dbb954d 396e0c4c3750ccb935942e2b9e481e10 2324 +226a9288-5bde-4676-a020-3fa6171cb5b8 93d95528-00b9-4c45-9525-24a55d6a4cd0.rna_seq.star_gene_counts.tsv.gz 35f4f5f223c169d73615bb7aed2095f9 401834 CGCI-BLGSP c334fa41-78ea-41ab-97e7-44db7fa8b460 de0f94cf-4f71-4d6e-982c-440365d880ad Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 9cdb8743-5ca3-46d7-9ac8-8dd008b80cc2 d7df9330e8bfa7f66c3b92b0a0d5a5d0 4219103 +2f708618-4234-49f8-81e2-4d81fc781c1a 6a1b5ba5-514b-4041-8940-b126e3bfaaf8.rna_seq.star_gene_counts.tsv.gz 85fb3ccc09f257e3fe3402849ae7d054 406389 CGCI-BLGSP dbfd839d-5c86-48ad-bdeb-d83d81584356 66414f98-5f89-440e-a2c7-eeedf298eae9 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 4f58395f-78fd-4d31-b58f-237b4435d297 67cbc33eeb3876195a03a364a15078cd 4228801 +3c7fa229-8811-4ce8-a396-328339826c12 e24b4649-8857-4fef-b986-6fa1f8c18b41.rna_seq.star_splice_junctions.tsv.gz 81257d0634cc45fbbcf948f3dbfb315e 3101965 CGCI-BLGSP 853704eb-f49e-4509-82dc-47a85c7335f2 082efedc-0c4d-4331-ab3b-20a9cfb77a79 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5e1d82ea-7cc2-4b8d-a87e-5229e762699f 7bf8b028b8f043f9250b101f9246dd53 3186046 +e5a01ae6-7f1b-4b9c-81dd-bd222d4fae81 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RNA-Seq Arriba f4d3c416-7019-42c8-9fee-679365518598 bd3ce8c5e0bc1c18dc39f6b3d63e36b6 3214 +ecffb57c-867f-48c9-8359-9993d061301f f676f0f5-1792-4aea-bd0b-05d476607607.rna_seq.star_gene_counts.tsv.gz 3bd51dd2970c3698ce1630d43ef82f65 397028 CGCI-BLGSP d04504c8-766f-4829-9d11-cc32f3052f63 5cb27d44-2c43-40c8-a294-f952ba67f0ad Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts b9e0315e-c0ed-4d6d-9f92-385f870210c4 70ded31259751f8a917b4ff649a3fbab 4220350 +7aee31da-2e28-4d15-909a-b3e357b307f5 00e124b3-7823-477b-bc20-45e523b9297b.star_fusion.rna_fusion.bedpe 32ddf65dd80e44e85ef25c2767ea4931 507 CGCI-BLGSP 49b5173b-fc55-4ae5-8b72-964f2173395d cc40c6e2-8ffb-4b3c-9da5-2d9edb7eef62 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 9195a80a-7421-4026-a503-6e4bce15a772 85965caadc137fc652a16025f6053c5e 445 +41acbc4c-357e-4c4e-94f1-f097b542aa3c 0bf60a0a-68d2-4d52-bbed-883d0539f6b7.wgs.ASCAT.gene_level.copy_number_variation.tsv 2555512108509b38c6014d29d7aa549c 3482776 CGCI-BLGSP 8c9c36bd-ca35-4158-ae79-b317d3a61128 3d8d874f-e424-420b-bb51-c9f442b77e72,60191e10-b052-4463-8670-dd669b9e2057 Copy Number Variation Gene Level Copy Number WGS AscatNGS 6414e4b6-6874-4939-9cb3-2cbe568be649 b1d932d0586731590f487a00790f2f81 3442772 +a8ab03c6-b1b2-44f9-a060-76766ed77312 da411c50-1ecf-4e36-a46f-d23e857065e7.arriba.rna_fusion.bedpe 301ad743293a98ee6523d0f6c3ee1929 2481 CGCI-BLGSP 75664f55-936b-42cc-b0ed-f219112c06f2 ccbfd547-c8e6-44d1-a013-69ff6428e655 Structural Variation Transcript Fusion RNA-Seq Arriba 70204b63-357e-46d1-8be4-f6bb8fc24b29 a8d7253d595589338e1e1b792fdd7ba9 2603 +c222b58c-16fd-45f2-917c-c90a2c5f55e3 d2032126-8de4-437a-9489-6cf34348a137.wgs.ASCAT.gene_level.copy_number_variation.tsv f229308ee6bef55565b8cd2a571d78c4 3482632 CGCI-BLGSP d0f47e8d-df1e-48e6-a127-6ffdcf7be450 68e608ee-d8f8-4816-b46d-c8cbed8f534e,608d30ec-36a9-4877-bb3e-f21d9e807a1c Copy Number Variation Gene Level Copy Number WGS AscatNGS d0e65503-a3ab-46e4-8eff-29c741a6b727 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32afa270-2c49-4634-be92-d215ffb6fc59.rna_seq.star_splice_junctions.tsv.gz a115f06b76cd34676da93a44bf4cf4eb 3194218 CGCI-BLGSP 39dce88d-112c-4a3d-b2d2-11e0616594d8 46a48950-f657-4a52-8b40-436aebc4defc Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 17845d00-c874-4820-9a05-239d309f3ae2 abc8079e441bc0967090ad4991548249 3488980 +18ce91dc-aab9-4e71-8cae-d447693e3e5f 06562a2d-a3c5-4f00-8efb-ab3dfa09242a.rna_seq.genomic.gdc_realn.bam 7a038a7f4e415df4b35ef2bdfa81a4e1 12480417323 CGCI-BLGSP 06c07e2d-a04d-4099-a29f-948e40558dd1 2e9ae889-acac-4f29-aa7a-a6584ba571e8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 3a8e7db2-66bd-4865-8c99-ce4c3923d80d f8146cb2ea4242f7c9a4280bf3a003f5 13309838619 +21ab287e-a022-4b47-ab92-bbd9e2cc792f 35663093-9322-431f-8799-746ec1be253a.rna_seq.star_gene_counts.tsv.gz 122c271fb7bd96134ac39d8b17992f8e 406877 CGCI-BLGSP 7dcc3723-aed6-4d2f-ad8b-afa443634139 e091e258-4d2e-4bae-a56f-d35a051044dd Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 0a495f8f-8348-4405-b54f-1cdcfb80e0e0 d9be390467a85a29d84d2ec75dcca5f1 4226388 +b8151248-46ae-4859-9bcf-27848f350816 8effa2dd-dde4-48ea-8c52-fbe799f1a83f.rna_seq.star_gene_counts.tsv.gz c1a3f143034841a84732f8a52413d658 400399 CGCI-BLGSP f1e5c114-3957-4667-88bf-f7821c75e43f 65122907-b42f-4265-bacb-007f96424e38 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts d7a19e74-2690-456a-8c66-67c079db7da8 70ce1e1ff21fe6c5edc2f208bf81a165 4220045 +43233e87-cd7e-485d-8821-ae34025b58c1 64740673-3511-4b90-b796-30dd470bfca4.rna_seq.genomic.gdc_realn.bam e962e8ec023fe906e9d74ae32a355462 14672657970 CGCI-BLGSP 886e1609-e89c-4d5e-ab9d-4f9ae18c937a b6a72a45-38ce-419b-be45-3b4808047c72 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome f1712ed1-dda7-4d33-88de-452ab7705751 dedfcce696f9e2852c8b357aa870fa6d 15990757117 +d27404d8-d96a-44a9-b723-58289619f4ec 669901be-877a-4b3f-bfa3-a45df0d38263.arriba.rna_fusion.bedpe 1b0a3fbc68862be23e02ae05ca990daa 4924 CGCI-BLGSP ee385ea4-54db-4033-b46a-8c397ed4aea9 8454651f-596a-4851-9055-ebd6e32527a7 Structural Variation Transcript Fusion RNA-Seq Arriba c6d48112-c9c2-4694-9cfe-a4f52b1f28fc 7b5381fd5a570fd1010a2f78fd183412 4690 +caae5b86-c11b-4ece-b981-facfe0e97a17 ce8460bb-6fc8-47ff-8694-1db8bfbd7144.rna_seq.star_gene_counts.tsv.gz 6d5d156d787991f418fc0e610ba1038b 403049 CGCI-BLGSP 5b4325c0-a7f5-436f-a7f3-630358e3ba2e bccbe421-db78-4cab-bc2d-ea31d7068582 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7250b6b0-66e4-41b0-824a-780f325a107c 2e1ecda83a640994920992fa6b199c01 4225159 +29cde3ac-79d3-43fb-8e6f-4db3ef4717a9 737ea3bb-ec46-4707-99a1-bf3f61052aaa.rna_seq.transcriptome.gdc_realn.bam 5230b401e99212fa79bea39b3814c2aa 10753917514 CGCI-BLGSP bcb4326c-3c7f-48e8-837a-b43bb2535a0e 784a65a6-e398-4c51-9744-c475933bf478 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 76895bfb-d620-4ae2-8d6d-b21da2648c41 8a603ead5a8fe7ba3c613b00a9b63670 12744296849 +093437b2-ea82-411c-b153-50c40686ac13 e5354a59-9d68-448f-ab12-ddca4b459650.rna_seq.star_splice_junctions.tsv.gz 7713ba0f2d231068088656af8a41af14 3100680 CGCI-BLGSP 58576f61-cf0d-4542-9f88-257ee412af7f cad655ea-5320-483f-b35f-a28d64d9210b Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts ffcf94b8-6ec5-48bf-9b01-dedc6e9a5d10 db46b167e1c187eb2cbe6dc912d2b5ce 3167260 +e109b8f9-a6d0-4873-8850-c965a8a0ff83 16f86676-8b5c-42cd-ac6e-9024cee0e3c1.rna_seq.star_splice_junctions.tsv.gz 65c469e70f89b5c27bcc7e1a79bf880a 2962039 CGCI-BLGSP b59a2c3c-7085-49c5-909a-c8504b1ae2a5 f66b1acc-8129-4b33-b06f-e3937a157c14 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 6ac61ca3-c8ce-410a-94e8-553f48121fcf 2975ab807c4a96d2aeaf63afe526ab68 3041423 +ff16cccb-1fd0-4be0-8382-c674e94b5e35 551d6887-ca61-4365-8411-2deb635e9a81.rna_seq.transcriptome.gdc_realn.bam 210bc41a61b70530ee3b0c9c1c0e7e30 14603715007 CGCI-BLGSP d991215a-fd4f-434d-a17a-cf106aa72edf 9fab0517-1d81-4178-a09a-a3d7f8f1f0e9 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 23ade44d-9cf2-4af6-bce1-d4840d90c415 2a23beb5dd224cac33ebd48a5b178f7d 17465289081 +9a48141c-b329-45f1-b572-aa704902ac66 329e077b-3aa5-44f5-a9c7-33ed4af9bac8.rna_seq.chimeric.gdc_realn.bam 812ed10b65928d855fe3ddde286c482e 105831116 CGCI-BLGSP 2721630e-8b64-4e64-8177-49f0fa84cfeb dcabed3f-05ec-43a7-b4e3-eb6ce820e87e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric f07f32f4-b7ae-4a84-83cd-2b61fd9fffc4 09ccbb4329feaa584da00ae96d6b2304 111344223 +8a99026c-64ee-46f1-9863-648a807b6ea2 bb64d188-11ed-4eb7-afff-1ba6bf5ab53f.wgs.BRASS.raw_structural_variation.bedpe.gz 8e78eba54439d996ce17e2087442a070 10544 CGCI-BLGSP 1835faa5-5758-401d-9007-17b1abaa070a 7b04a648-80de-43e1-b2b3-836108de20ca,8f8e821e-e860-4190-a208-53efe218bd72 Somatic Structural Variation Structural Rearrangement WGS BRASS ec684beb-bf6d-463b-8ac7-eacb7b79460e 2210ddbcf929a8857c420928dedff5af 36492 +b9e10520-a8b9-40e4-aaa8-128a3927c0eb f9e0ca1b-e175-4e35-9877-45fe0d025277.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP e0ca8db8-b71b-4a63-96b4-96d368cc4fd6 9be49a9b-548e-4214-b553-156bc083f9dc Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 3eec1b44-d30e-4c68-ae84-f826cb3de181 6e5690795ff424264402ab9d2661b62b 229 +133ff57b-8e28-45c1-82af-be4e011cbda1 e1284265-986a-400f-8025-1da6d6a37871.wgs.ASCAT.gene_level.copy_number_variation.tsv c4ac280bb17fb0d9e4040896fc4b2380 3482794 CGCI-BLGSP 13c615c0-74b2-4b41-9a05-b8a71eca0685 bd12565d-2c9a-42c9-8d3e-9083c3052f47,2c4e97bd-67f1-45c9-8013-cffa427196b3 Copy Number Variation Gene Level Copy Number WGS AscatNGS 1a483a89-4e17-4a92-a08f-b17961b94a01 2135b3b95bc8310fb6dac1f2c60cf382 3442787 +7d73a1f5-e24a-472b-9221-13ac248a0176 8ef85e07-56cd-4588-ae08-7d7e7d46c58c.rna_seq.genomic.gdc_realn.bam 3a3ebb8ebd451945c742f0ce77ea414c 14667766427 CGCI-BLGSP 6c957218-bef4-48c6-9c8d-0352dd8d6077 c345daff-b4a7-43b4-98dc-406cd3ecd37b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome af8ffce3-7536-4f77-b6fd-064634e11bad d874025a19e558f6c715c28994a70086 16370617867 +7d61e841-3247-4707-b2ef-5ed83cc40cfc 79edd0a3-1879-4944-9486-4b3e9710514f.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-BLGSP 359381c1-34bb-4b8a-ba43-f06bce194341 e52905dc-0faf-4828-a893-945d32d46805 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion ddd8ce4d-5897-4ae0-993d-ce37eecc0bbc 6e5690795ff424264402ab9d2661b62b 229 +2335ecc8-f6be-4777-9bb3-8c3c257fb66a 3e45c90e-3e32-4d62-ba4a-a23fb166ebdc.wgs.ASCAT.gene_level.copy_number_variation.tsv 110769769f3e2f64e5eedc182403dc28 3482770 CGCI-BLGSP 48823727-d7d5-4efa-b374-17e3cfffad91 92c574dc-47eb-4cc6-b71d-8d6d13be4c32,c91ceab1-43d4-4fbb-b311-bb5b714c22aa Copy Number Variation Gene Level Copy Number WGS AscatNGS 8984d1d7-4cb7-4d58-9fbc-bcac922bd46f a4ebacae2b182799dacf023fb089d99b 3442769 +e09db3bb-2cd5-4404-875e-8b26b3b9a972 cc46e3b4-c4a3-49ad-93b5-e0f8cc3bf3c2.rna_seq.star_gene_counts.tsv.gz 58970a59e0f0ec71a1787d848a4f0ec6 404374 CGCI-BLGSP 8eb3f8de-84ee-49cd-ae33-5cdc3cbebf3d 0fd505be-a785-424e-9a45-02d31e014793 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts c59c3474-308f-404c-99e0-d9f1b3e2dd30 8cffa6149a59b6beb70072e141b1f226 4226002 +e4642057-d99a-4cae-af28-19fb4135131b 9d9af23a-2399-42af-a4e3-215f48a8a057.rna_seq.chimeric.gdc_realn.bam 63c4a7ffa5f5251dfb6760093333e258 126781775 CGCI-BLGSP b5befdad-1ff2-408f-ac0f-8af149b7d606 c5871626-85e7-4718-a779-ea4e3738f041 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 05beac25-9861-4195-8c2d-d9ae812865b1 e79061f079716ff79753c4a6f4d812ba 135413512 +b373f349-3998-49ff-8fa1-cea85ca00d1b 1f1aaf5e-ae93-4e4d-a862-58e1fbb613d4.rna_seq.star_splice_junctions.tsv.gz eb252f3c1691ee68852e0ec21d532681 2749449 CGCI-BLGSP 49391d47-19dd-42b5-b57d-87a29b59b419 74f69b50-a95c-408c-86c3-b7e37771d0ac Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts de8e7345-2ed3-4de1-b33e-17f1e2a74eb2 d881f542f44ed829cdede7021b94a16a 2816788 +1ee2f9fd-1968-4f3b-a3f4-ad2c66cd2083 cc46e3b4-c4a3-49ad-93b5-e0f8cc3bf3c2.rna_seq.star_splice_junctions.tsv.gz 9709ce3a46b5fd5e8805429187864776 2947684 CGCI-BLGSP 8eb3f8de-84ee-49cd-ae33-5cdc3cbebf3d 0fd505be-a785-424e-9a45-02d31e014793 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 94e80956-d9d0-4bd7-b0b5-5dabd8860134 6f05b265695f5997c5bcb3a92e0a6131 3022621 +a2d82537-ddc4-4d07-920d-63bb1e62a045 35663093-9322-431f-8799-746ec1be253a.rna_seq.chimeric.gdc_realn.bam 236ec24655a21e4395bc1d2de34cbf65 89240922 CGCI-BLGSP 7dcc3723-aed6-4d2f-ad8b-afa443634139 e091e258-4d2e-4bae-a56f-d35a051044dd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 82485529-7a4a-4c99-866f-a799acd64330 3f1a251db7bc3c900e3427a117575d19 92300704 +5a752f22-1be5-4cd5-afdf-09ef601b6601 693f76b5-6d30-4bbf-85a4-f9e6f43d5f70.rna_seq.star_splice_junctions.tsv.gz 1148bb7f23a08163406677a8aa553749 2764196 CGCI-BLGSP f90e6333-f59e-4f6b-b7f9-17ba10e4a600 f9627688-8e25-4ede-bde0-8da01ed7528a Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 31bab6ec-175b-4b01-bc30-ef8edfe42a81 bd65d54fc1150ee7e58b6de33f3c93bd 2835711 +15861577-1771-43c4-82c1-bab2fedec679 926b7844-bfea-43bf-9ea5-11ccdcddace6.star_fusion.rna_fusion.bedpe 24284a055a87b8a6948504462d9e17e7 495 CGCI-BLGSP 7e0e68c6-4055-485c-8d34-651e803af78c 664580da-73ba-4af9-abc2-4f406999a1dd Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 5cdef048-17b7-464b-965e-794e970a2397 6e5690795ff424264402ab9d2661b62b 229 +80c8db65-81ae-4cf4-81e7-5e0f514fcdc0 adefcf80-c82b-4853-a26a-858212f12984.rna_seq.star_gene_counts.tsv.gz cad6a777fa7ad690ccb8fd96b9124624 389723 CGCI-BLGSP 359381c1-34bb-4b8a-ba43-f06bce194341 e52905dc-0faf-4828-a893-945d32d46805 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1cbe924d-db57-4516-80be-0887aa03938c 9fecbe982d04d589b851e77298bb419e 4208295 +1d9b7e5d-99d4-42b6-8570-f0a182d95e69 9dd150a4-ec31-4ee6-96f7-63dd2c7e86ab.wgs.BRASS.raw_structural_variation.bedpe.gz 52ae40d9372e9f0e25d882adbab0e4c7 15125 CGCI-BLGSP 7e0e68c6-4055-485c-8d34-651e803af78c b22f49f9-0ef0-4d4d-8a6d-34391cca02e0,8a43d359-134d-426b-b338-1eaf0456de7e Somatic Structural Variation Structural Rearrangement WGS BRASS bd9e453c-ca82-48c3-8172-0d7d14cbd39d 8286c53fcb2062367fcfe7d89b25c5c6 55160 +a5265b62-04b9-4eab-a812-a9d0156ae170 179056b3-a66d-4bd6-a513-795948e0f5be.rna_seq.star_gene_counts.tsv.gz 747e4b076fa49d015439de7be601021f 408321 CGCI-BLGSP 32f687ba-28e5-4efd-9e27-5835f6416fb4 0783dc52-8dcf-46f7-9e1a-93252e11efda Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts e84e24a8-9fe8-4c2e-95e4-68fedf271a4d 947ff28251e0ae8db9b03bed5886d613 4228922 +7d528d35-3461-49ee-833c-46c79f002cb2 1f9ccc1b-8935-48c1-9e03-6ed992f31b5e.star_fusion.rna_fusion.bedpe 99d5bad3793b541276098063a897de30 1961 CGCI-BLGSP bd25db19-92dd-4d8e-8b07-4dba8095cfcb fffaf700-0acd-49ee-95cf-5b295772242d Structural Variation Transcript Fusion RNA-Seq STAR-Fusion f4488dc6-4581-4c0d-bc5a-37c70ed21b59 f1a52f0d63a3ada0755f9004a1520239 1220 +0be1245f-46b5-49cd-be97-8a05cb634bf2 e24b4649-8857-4fef-b986-6fa1f8c18b41.rna_seq.chimeric.gdc_realn.bam caac604b9faef43ccbbdde5d17e88935 102947910 CGCI-BLGSP 853704eb-f49e-4509-82dc-47a85c7335f2 082efedc-0c4d-4331-ab3b-20a9cfb77a79 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 848bfb33-a8d4-4db3-a343-40d33a14fd50 a39f6b5d0702df6bc1253f9fd968eca8 108412322 +b905e5be-bc93-42fc-8f0c-ed17377d51a1 d213c5f1-6d82-45fc-b4bb-19667cb2b170.rna_seq.star_splice_junctions.tsv.gz c50549c8dae665de6814977c5592fcc9 2895119 CGCI-BLGSP 681ff2e8-6073-4dab-a398-1f2203c2d7f5 8cc05c59-cd01-4998-a1dc-30d8e13c2956 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts d637b1b7-3b2b-43be-8cb7-393e9a8bf159 117e20db0c1f5c952f0c4dfdbb79975b 2977540 +ed1c63d6-0204-4c34-ad95-234f027f72da a27817ca-38e8-4c86-a40a-ff63b2757e4e.arriba.rna_fusion.bedpe 3e87e757c6bb177e02d686a2d5c98b54 4620 CGCI-BLGSP b06f7bf0-45bb-4aca-8f22-72d8a4f73f99 658beec9-2428-42b6-9663-fdc58c15c602 Structural Variation Transcript Fusion RNA-Seq Arriba 0e2c1e31-2507-42f6-a7a7-61d2d6fe5531 f1a42219136cc81298d1dc577928de77 2543 +2fc5f040-e20c-4d66-a19e-c5dc01351ed5 1124a66f-f394-4e29-850b-20767da0a266.wgs.ASCAT.gene_level.copy_number_variation.tsv 3fd12ad8648cf83d5ac61281847674a8 3482632 CGCI-BLGSP 90e9183f-7210-4922-a653-21c86e488887 eac92fdd-3814-4b3b-8f5c-7ce0915424df,512001d2-2c85-47df-ac2c-a5f6601b772d Copy Number Variation Gene Level Copy Number WGS AscatNGS 2ff029f0-f68f-495f-8081-f66679c4dd10 b3a20533881fedbd1549ee54913336f7 3442640 +20f54dee-aaf7-45d2-bf1e-e3f51b98f9bd 39bde99f-e97c-4f13-af83-5cd7dded015a.rna_seq.genomic.gdc_realn.bam 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Profiling Gene Expression Quantification RNA-Seq STAR - Counts 3ac0556a-d75b-4a65-be7d-e6efaa654abf 25be89a35424067fc33963c0050617c4 4221812 +7442fd21-cc89-4fb3-abd6-de7ff54711d7 e0edc0f8-5aa5-4468-bd6a-e5a3d4954650.arriba.rna_fusion.bedpe dce95b02af680d56c762e0967ce62c9c 4793 CGCI-HTMCP-CC 72b76ae7-ed7f-476c-b5e7-8dc1b5dd046a 0930e1d4-94ad-4c47-b8d1-2bd47e54221d Structural Variation Transcript Fusion RNA-Seq Arriba 00c702b0-ba9d-4968-ba95-48ed75b9dc19 82469df3a66b5023fadc135f04485591 3158 +f926f7f8-b3e3-45c7-9228-ea760f6580d3 57425d5c-a1a1-449c-8f17-7839b62a85a9.wgs.ASCAT.gene_level.copy_number_variation.tsv 24f074cb222f2788947164eb498b384b 3481177 CGCI-HTMCP-CC 54d01763-63d0-43a7-85f2-d447c6d9950e 98e3ab7d-4f91-45bc-b3cb-573b33848b6e,02294197-832c-42ea-9946-d4daf733ebc6 Copy Number Variation Gene Level Copy Number WGS AscatNGS d03b43cc-9e2c-47dd-8c8b-e705b87e5178 aa1921718032e0bda6983134be6f37b3 3441235 +f984e737-a0c1-46df-8d6c-997dda730dd3 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Quantification RNA-Seq STAR - Counts 602a7d32-71a7-4261-9f49-3bcfa337f2d1 a33f85724483f1298e06850a255b8bd2 4234784 +03650475-cba4-4fbf-9210-1e22359853b1 7364f25d-4334-4803-82a6-febb7d63433c.targeted_sequencing.MuSE.somatic_annotation.vcf.gz a51815177e0a375802f1eaac34741241 89401 CGCI-HTMCP-CC b4a85dc0-8269-47c8-a235-2ad7d1e69c62 c4e51a80-7ca2-41ae-9ddc-832049c779c5,83a2680d-7967-4939-b53f-bee3bed7fda5 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation e4e51cd1-4e45-487b-ba5f-ca7d873e1847 77cb5c42e9119c8356c6794cf6f74196 93409 +33db5bc9-2cdd-4b49-a79c-9ccefd6a4ae9 de52086a-f3a2-4cc8-8ff6-7e30e2d13bb4.wgs.BRASS.raw_structural_variation.bedpe.gz 2411e44b2de26833a72e83ca24ded4fb 13908 CGCI-HTMCP-CC ab45050e-2965-4d33-bff4-cd7a067ddd3d 030764fa-53e5-4322-8287-594f9c01d7af,78ab3cd8-5e8a-4a46-bf85-7f80cb80e2e4 Somatic Structural Variation Structural Rearrangement WGS BRASS 6d9f0c62-2706-4c3f-9ce3-4de2218d7faa 09de3b1e2bd5171c94f325c111d4fbe0 50715 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925a3e3b-cc66-4e6f-8aeb-de9f11ae1442 91b8db412dac5d308c9d99e8a0a3b9fc 4217415 +15c1f0b0-c4ce-4862-b0a5-99e2fbcfb3b9 4625e531-2704-4c1f-aaa9-6908cbee0ffc.rna_seq.transcriptome.gdc_realn.bam 0cf0e4466cbd35ef40a75966ecc4cc1f 23127101802 CGCI-HTMCP-CC 981300da-9136-402a-88df-2c76b1e3ad87 64428b84-2e75-4610-9c81-27e379074b4c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 584b531c-494c-4769-88fc-b4c288aa3afb d57fdac80c5c0b617c13d2c31d42c082 27308286312 +e5523815-b935-4069-8d30-ebafafaf3161 c0aaf925-6d39-48e6-b075-504c16bae388.wgs.BRASS.raw_structural_variation.bedpe.gz bf9506bd2e8f861c72926afc85144a2f 21224 CGCI-HTMCP-CC 70fa9c5d-42f7-4410-a72d-c33c292fe4f6 5ba6811d-1b0c-46a8-b385-af715ab2f2e0,d6e7d0e5-9947-415d-891b-9670d6b069dc Somatic Structural Variation Structural Rearrangement WGS BRASS df621ce6-d313-4c21-ab85-b9e60262e32e a69c169831785fb55d47701c42de6b78 74746 +2128e6bf-205b-46eb-8e6f-5ece370f24f9 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1729782 +872cfebe-b239-450e-b8f5-0f86806a818a 8161bf77-9598-4cc7-ad69-f2cb74047d12.targeted_sequencing.MuSE.somatic_annotation.vcf.gz ba79a570cce3e9fdd28236e5b7a0496d 100737 CGCI-HTMCP-CC b27381ed-ae11-4f72-bd90-3f5c567de192 c5f5d96a-ffa8-48bc-89fd-2cd4ad9bdfa9,6098863c-886c-4ce6-944d-e4641e2c6303 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation c1a37678-4ec3-4a46-bf48-8c2d1e3aa159 bbe5b05403942b9a3e17bce1ee6fb3e8 109441 +7bf7c62a-e4cc-401c-90b1-e7d2a6496f96 21529b66-def6-4090-a198-0ca3dc2686b5.star_fusion.rna_fusion.bedpe 06ffbd8cbe42eed68d7963cc9b60b784 4149 CGCI-HTMCP-CC 59673b19-2e14-441f-9624-626ed0a3530b f8c00f0e-87a1-4e8b-88f4-ab62551d6160 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 2c173fc8-db7b-4987-94b8-bce63279ae21 e05caa93aebe5c3d12126e1cb3b58fb6 677 +487f6a92-ad62-46ac-902a-49d62c993b79 63133b1a-06aa-42c6-a0eb-24427f0e70bd.targeted_sequencing.aliquot_ensemble_raw.maf.gz 45668ad2e30238c469f77596d835a640 95443 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Reads RNA-Seq STAR 2-Pass Transcriptome 9ed5f013-4f2b-4fc8-a8e5-c5ed45509f30 5a601e39a5e60e285a73cf92175ba45d 39392504718 +1d65959e-b4bd-4964-8710-1cd4926ec7be b097ae86-6491-49b7-9d93-d9570e3d7a58.targeted_sequencing.Pindel.somatic_annotation.vcf.gz c5aefb0925701de0a97f55826f537dc8 69347 CGCI-HTMCP-CC 146bd9db-1645-4950-bd18-de30d0db2487 a64490ad-fc6a-445f-8a8b-cfe86e0f9274,b12b77a7-d93c-4580-9f57-12bd1d83d962 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation 93ee830b-e21a-4825-8c2f-5e1db3d7be39 6d503dbe85ae2d2a7575eb3b588fce57 72638 +0b3a581f-f134-4220-90bd-7f185ee60e33 edabdcf3-354d-4d4d-8a79-ded2af5ceb38.wgs.BRASS.raw_structural_variation.bedpe.gz 63e3e3aa6b1aa63d5ce67be25c0d97a3 19406 CGCI-HTMCP-CC 10b32c37-0e82-47e8-8ff8-91a14971737f d8a638bd-9610-418e-837b-49ab7b712f94,21544981-322c-4159-a8d2-74eb428f1a49 Somatic Structural Variation Structural Rearrangement WGS BRASS ee5c7cec-aa3d-4116-90f5-eb2c11d057de 4884f6ce50233a36497a909616af1fab 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Variation Transcript Fusion RNA-Seq Arriba c1de3c26-1037-4cdf-82bf-4995d4411eb3 3d0616a2ba9b0cbb2bbbf1c679299913 2318 +12809aa8-9a7f-4404-bb75-ad46bf5942b4 df1987c0-c09e-4740-bf28-4eddcb866b29.rna_seq.transcriptome.gdc_realn.bam d8e5ef9e7697644d127229f8b5b6b9e4 3945474803 CGCI-HTMCP-CC b9a4f274-5e12-4ae1-ac64-83a3c9be74c1 d32c931e-8c50-4de6-94e8-a2b37e510334 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 3a1c79be-b97b-4cc8-9849-6262469a49b6 c8bc4331375451c0f9f3eb8e747a484b 5607751601 +e9cd9d74-ca04-4ed2-b48c-415d571cf777 e076efe8-9661-4146-9f58-4d0a6519105e.wgs.BRASS.raw_structural_variation.bedpe.gz 61d5e506b0fc608b25873eb6a426cba7 153531 CGCI-HTMCP-CC e291f138-8517-4add-b647-d96647835168 0d146fb2-8818-48b8-a3d6-785ee491d488,505b82e9-4ab4-4f2c-9c4b-a894a38af89c Somatic Structural Variation Structural Rearrangement WGS BRASS bcad31f8-3c87-4111-86d8-8a3d3851dd0e 72ecb5cfd6f7b5fd8a5a5086f68d2754 523876 +cb2efba1-1d52-4d35-8ad9-960e87e8151e 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aad82efc-be1a-4a90-9e0a-9507b34b351d 808839a6c26a47e8f60b3f7b74c8e61c 1773 +4cbf2f6e-6fbe-4ecc-beb3-54173d4da92b 59b26ee3-7d88-4f09-8948-0dd6e2dab43a.rna_seq.star_gene_counts.tsv.gz 586bb307c374920a3e65171408143768 401495 CGCI-HTMCP-CC 458cbd14-a7ce-4d65-9caf-680c4c66e024 d508adc1-a844-4d6a-99fd-39eb3cfaa829 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7577a503-9e7d-4a7e-8105-978696834dbc b9926d579ff46faf8ecc76ecea724fba 4219465 +93d8579e-0550-491b-963d-e6b1b840c6e0 391c0f2c-50c0-42b2-8b8e-fd21c64c368b.targeted_sequencing.MuSE.aliquot.maf.gz b5bb69fb7bd81df732214b35f5227fa0 99866 CGCI-HTMCP-CC b4f0df8a-ecc1-4274-b8dd-4984aa66cdf8 e4ab7314-c1ed-4ba7-90cc-7b7343d978df,ca5b4090-d807-44ae-aa28-37eb87d51c9b Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 3097f8e3-988a-42cd-802a-16c9095c05ea 78616bdb8fc04696d174c34e0a3d0882 117000 +405f2868-1fc5-447f-8d21-27c8ac859e52 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Junction Quantification RNA-Seq STAR - Counts 7ef11b14-b234-432a-ac16-c4d77311d0fa d5c51440d3479b7cd1891a9d358b0445 3661440 +a38235ba-c21e-4ad0-a527-d51a0d93e3b8 d1ed8e4e-e91c-471f-ac51-2e6ec14f6cc1.star_fusion.rna_fusion.bedpe d14a2ca41ca6f2f495ca803f3351632a 5678 CGCI-HTMCP-CC f429c531-358b-413d-ba3e-50ea945e68cf a0f6d9e8-9af9-4f33-abf9-ff95f654bb83 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion c64d2ed9-6c59-4802-a06b-b22cd37433cf 6a5c3d5a5f8437b01db7c294a41988b7 648 +4891fc95-66e9-4f86-bca3-d351bb5940b6 2c669a3e-39f4-412a-b37e-6f13b5095043.rna_seq.genomic.gdc_realn.bam c67b583d77294e92c43dc8453a043d05 11898624377 CGCI-HTMCP-CC 8c2a5be8-0ae1-4b68-9692-ec607ae873e6 a527c3f7-0b43-4004-a972-3ee14af5c8de Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome e350fed4-e707-47ea-8257-29eb1966000d e5248df7dd83b9fd7704f52f44270fe1 12835825454 +9c18f493-7ae6-40ee-8566-2400ed47f18e 3b851531-a4a6-4259-b376-bf62d9400e60.wgs.ASCAT.gene_level.copy_number_variation.tsv 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RNA-Seq STAR - Counts a796fbed-207f-4258-80a9-1020e46349b8 ad6350d5584a0b9769a2bb0e3d4a2534 3881108 +331e129b-4988-40a1-afa3-d848523cc25c 2aa00e3f-9c0c-44d8-afd3-addc36283183.targeted_sequencing.VarScan2.aliquot.maf.gz d54ba74c696912002943e10166937389 154337 CGCI-HTMCP-CC 50103b4b-87eb-4d59-a85a-2bf998bafb16 4b0ee102-3043-458f-a5e7-99c69eb41b3f,25d29092-8b57-4eea-9a36-2940fc12f264 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 00877e7f-f6cf-40a8-b68d-f8d398d25c46 b496c8bfe0aa09465b2ede57c72edb6a 188158 +8cd1bed1-5f4d-427a-89fc-6bac1305dcec d30b8db3-53dd-412d-8ca5-6907a35e8ccd.wgs.BRASS.raw_structural_variation.bedpe.gz e4a257e5296042ca76e613de35b59ba5 43530 CGCI-HTMCP-CC 1350f0b3-06bc-42dd-90e4-bed1af31c176 06e4965e-5a63-4d10-a231-20178266d5d5,7feaa191-35ca-4fae-8b0e-68cce864c9d9 Somatic Structural Variation Structural Rearrangement WGS BRASS ae402fd3-f023-421e-ac28-00fc1eff433c 88fad4e354520f2abeff99238f2279bd 145807 +d9d39eaf-a05c-4b6f-bb27-84406a0dd5b1 631a2f07-7077-4879-b890-063726471ec3.wgs.ASCAT.gene_level.copy_number_variation.tsv 488b4b506799eae250f3572c59444e0e 3481123 CGCI-HTMCP-CC b0b16c19-23cd-4774-9337-cac369119913 1505eb0d-dd38-4c2b-8974-2702344b7a78,eb51180d-a57e-4f27-b73d-5c882cbdb156 Copy Number Variation Gene Level Copy Number WGS AscatNGS eac664e4-79e9-4963-963f-743a4432c50c 4bef163bfb962e13813a3af72a4355a6 3441197 +5f4610db-896f-4b73-865c-dabf15b5f8a8 7f5bc0ef-078b-4447-a5ca-8ca33dd93a6c.targeted_sequencing.aliquot_ensemble_raw.maf.gz 55cf552e86e024d32c0b7d38091301e7 75075 CGCI-HTMCP-CC 50103b4b-87eb-4d59-a85a-2bf998bafb16 4b0ee102-3043-458f-a5e7-99c69eb41b3f,25d29092-8b57-4eea-9a36-2940fc12f264 Simple Nucleotide Variation Aggregated Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking d08863bf-0b4a-46b1-b23d-6af821e4792f f24f453bfc506054e7b2a3f8f995061e 94755 +98b2066d-a1ac-4427-bcc6-779b50dbe7c2 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2ed9a1ff-2822-473f-9e5c-093af94b0021 0c648932d1c280b8db07a524c68a71c5 230781166 +002632dc-38e5-460b-beaa-214e01fb9496 1cd54810-d274-4596-9090-a27fe3cc0bee.rna_seq.chimeric.gdc_realn.bam 777f8c30f653eebaa5443f57fc3d3f15 138480424 CGCI-HTMCP-CC f02c03f9-530b-4952-b3a4-ac53469a7769 2ef04eac-cfa9-43ec-a98e-b56403984aca Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 8356f10f-4ba4-4bf3-9c76-da20a4bff580 307ec237c3a2d69db9c3fe6ae8fbac4c 144700547 +87a07b40-d0c4-4c9b-bc29-9bffa9a7293c bbf8c0b1-2ca0-4258-99d9-6c2aa211ab2b.rna_seq.chimeric.gdc_realn.bam e4b3b44fef494f6c0eb2b878124b5a60 80776303 CGCI-HTMCP-CC 933c5e03-277d-45ca-aa61-db964e69f7c1 8744c453-ff90-47a8-9ddd-d670b0348166 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 1addc589-3d98-463c-a7a9-3d6d8315255a ea176009b41224b6aed1996d634b14d3 85949992 +68268670-2298-4816-9315-daadd62881d1 3193f118-c2f7-4935-9479-c8ec76a4f81f.targeted_sequencing.SomaticSniper.aliquot.maf.gz 574292ad31b8f25a5aabcd5b953c4812 282818 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dc9d95c1db3db2a7b3be04e9bc05e14d 5171 +06869eff-f670-46dd-9644-752dcac1f1f8 d86fb254-1b54-4067-9e25-19d44fb1b190.targeted_sequencing.Pindel.somatic_annotation.vcf.gz ab876bb81cf257cd5eb381f701cf4147 26232 CGCI-HTMCP-CC 4368300e-5527-41b6-b1e7-8d98fff3803d ed45d6c4-7ff4-46cf-a6a1-de5e66224f1f,464122cf-ed77-4390-8876-d625ee178fda Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation 8870f2cf-6362-4451-bf62-5049bf1fbb98 de0ba1d5f9e007e6ed0e876af06f79fe 26252 +5edc778a-cc58-4aae-8758-6c1aa02eca1b 8d50893a-082e-49bb-bf7e-b81e5e543bed.targeted_sequencing.aliquot_ensemble_raw.maf.gz 7dc243fe694b27d390b8b226d57f45e0 41131 CGCI-HTMCP-CC ca0b76f4-7196-44a2-990d-7d71c976148e 0ef6e6ab-1156-45e7-a347-9ef96d81e5a6,d29fe0e7-4e6c-4809-a934-071df69e475a Simple Nucleotide Variation Aggregated Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking 8e237c37-63d1-4ca9-9c33-2419319d5753 59674107ad7f06712c2ca1a07a3d65be 53902 +091d4e27-6bf7-44fd-889f-95a45c86165a 4d4ebe93-17a4-454b-ad18-d0c4c1a53ee5.targeted_sequencing.VarScan2.aliquot.maf.gz f960837f6c64567c2dc089a001bcc18a 264385 CGCI-HTMCP-CC e7c4ec49-f1d4-47fb-b827-77f08dadea1c 767d3e01-b514-4df3-a68b-e165b3de7866,3b7cd79e-b2b4-42ad-bba8-6e505b132d34 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 169593eb-e59d-46a6-8449-510fcc0280af a40003088a00b97a6ea201326ff79ddb 329314 +834c28fd-24c7-4f9d-aac6-2b665890ebf1 58ca2882-328b-4d33-b375-fd42d7640024.wgs.BRASS.raw_structural_variation.bedpe.gz c50b3086b307c62b70f9ee68d6f6aafb 32504 CGCI-HTMCP-CC 889648ef-3225-4e95-a47c-82a9def072c4 cc995aba-7b13-4a86-970c-da622a5cd63f,a3b9d4d9-b516-4553-89f8-af6379e670e2 Somatic Structural Variation Structural Rearrangement WGS BRASS 5bf5b5d6-b519-4bbf-a68e-153a1e7511bd b7c68e08d7ddc727401d3fed628d2a92 119084 +486d1a56-6d23-4f0c-a41c-4fdda009d22d e3cf0595-cba9-4158-9983-80c3c0e91288.arriba.rna_fusion.bedpe 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RNA-Seq STAR - Counts eb291f86-1e14-48fd-9ce4-b7572ca926f8 ba869ff88b492fd056e78c34f4afa7c1 4244910 +a98ce1ef-d190-4a11-ac1a-162a4245c7b5 40205884-e3c8-4cb6-9370-f7fc221aea7d.arriba.rna_fusion.bedpe 931c274453634ead017a84ecb208fada 5653 CGCI-HTMCP-CC e799df87-488e-440c-96ec-4ca9e90a92ca 98689e0a-27ce-4389-a42c-d3a0014af93d Structural Variation Transcript Fusion RNA-Seq Arriba 72849df9-f516-4464-8407-ccd6f664e4de a10e1f613bde5edf19d0cdcd921b3a36 3577 +7764b5de-9f49-4b5d-be6a-ef55767b07db 7d5ce19e-9961-4b00-ae86-e08359fc1dfc.rna_seq.star_splice_junctions.tsv.gz 81539087e59bdb7aa97deadcc36354f3 3032211 CGCI-HTMCP-CC 7064054a-aaae-400e-b1cb-e37b27233af0 fa47c6d3-4903-4961-b7b1-1e5759a672b2 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 58263872-db99-4059-af89-87475b680c90 7c60de7147cd4c5817fde86b372e9c70 3098165 +b2f71ec9-2047-463f-9381-0ecedf178954 e62df973-80fb-4fd2-af97-7f991006b34c.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 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Annotation 6fda100c-b3d1-4fab-8a44-2478918aa1ce 98a1dbe0236331031cbe31165fc11834 460096 +15b42b18-1035-4445-8869-250167f955f9 fed69d32-d010-4d56-8a98-9719886d5d7b.rna_seq.chimeric.gdc_realn.bam 48f45bc49557bbdb2a93fd2232de46a1 144633651 CGCI-HTMCP-CC e809c820-4623-4a88-8718-ea402b041a41 051035da-91d4-4b00-842e-92ef5958c76d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e69f6b5f-cdd3-47ad-a5df-cd11ed09f055 aeed83976c2392535b2d01417f997490 156460693 +61142d13-06e6-4d5f-af75-342e711438af 7f734b66-eeab-4ef9-8178-b5591e5c2425.rna_seq.transcriptome.gdc_realn.bam 960c2e9306cebed991c915fd9be3db5c 3992609731 CGCI-HTMCP-CC 7064054a-aaae-400e-b1cb-e37b27233af0 3a3e18cb-1129-4d72-af70-a9c1d08f7f1c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 4bf9dd44-1780-4cfd-b76f-245888f5fd04 4da56c28f9b182e817a9604a8fada08b 5765914305 +3c35f78d-406e-4753-a864-7283f899e6b1 3e4aa8aa-215a-4f19-895d-93b21550eb3d.targeted_sequencing.aliquot_ensemble_masked.maf.gz 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df4a4d4f-16a4-4073-9769-99d323b3271d 6b46dc550276870f1653e1b91524cb43 2243 +9cdca996-2cc6-43f0-81ec-426b9f0a6a06 d53ec761-1d93-40e0-ac40-78d2bc9e4770.rna_seq.genomic.gdc_realn.bam 82984417db319cdc3ce1dec7e1218151 10783512469 CGCI-HTMCP-CC 9e3c05ba-ba46-4e96-bdff-660ca34d6a4c b0d4da0d-b1b4-4701-aed6-9331856c119e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome c0410ebc-75c7-43ee-a642-8101055af232 29e697e5c0e74e48b79631471cf1deb3 12051502082 +cc95389d-58da-4e2f-a68c-b009a22eb06f 96dc0c54-2bf4-419e-8e30-8df7008d9c22.wgs.BRASS.raw_structural_variation.bedpe.gz 5ff84a1ee257744ce1b097c4780ea135 75669 CGCI-HTMCP-CC c55be3b0-0da7-4923-a832-23301947fa3f 61339331-bee3-4f20-a6f0-2f488042e809,7d9d24ca-ae9a-467a-a3dd-6c5bc76a54e3 Somatic Structural Variation Structural Rearrangement WGS BRASS 70cbe621-d3de-40d5-b3eb-63574ea72ead d43a366c62547ee6806d3a692613e3e1 251727 +42edd5b8-3a0c-46ef-9866-4ca28e0b2a1d a65838b7-4ca5-4322-a5a5-ca32ea977685.rna_seq.transcriptome.gdc_realn.bam 185e472e8d9c1c3f0cdb4382924460db 16066999232 CGCI-HTMCP-CC 89c3d38f-8eda-4f62-bb9d-8d3b818c969f 68d84bea-e20d-4c04-8958-b94860a2315a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 279f7b71-cece-42a9-9957-1f90a61be43b 89faa464f284adc63a8d970219a35162 18906930003 +7ee3c14e-33d8-4fd7-8038-7cc73e3f9f79 4110e247-5759-4702-87dd-0e1cddf5293f.targeted_sequencing.MuSE.aliquot.maf.gz 8b63dbb0f7050b9f73a236b82545bea9 76325 CGCI-HTMCP-CC 008d3744-e7f0-41a5-a419-702960cf1ccb 01bd2ddd-1bb3-451a-b6b2-7fe30cfd7f5a,902d99c9-ddb8-495a-8cda-cdd358668af6 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 215e0d32-16da-4e74-8e22-3a0af1d5ba06 bfa4fe50d679df08f90a82d105cb09a2 87879 +30912f15-7eb9-406a-a0ff-ec85d826b013 fee86580-a4e9-4f72-8cc8-37a2751582e4.targeted_sequencing.VarScan2.somatic_annotation.vcf.gz 77407e51e00593146037921887c6807c 174835 CGCI-HTMCP-CC 31cdde3b-2dd9-4511-b701-99fb328755bf 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Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 4d9929cf-ab6b-4ebf-931d-163d3c45bdd7 7e7935d504734e8fff4bdc25141b66bf 1257931 +cfac6f3f-dda4-49bf-9a56-e9b7447716e6 ccc7110b-8606-459c-9e61-e71c706100c8.rna_seq.star_splice_junctions.tsv.gz 1dd5d6c1140aa40d12f9284eeef6e042 3582046 CGCI-HTMCP-CC 52c67707-cab5-4f59-8c12-7e08d0746794 212a220b-3fe9-4fc7-9eb4-2295d298a77b Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts a8bc20bd-4553-47b0-89d2-aaf3046902aa b75ad45bb7a767938a02f8fcfe33f937 3670762 +5dcc78c0-be8d-40ce-8527-49c5ddec2d22 ea3134f5-b326-4665-a363-64141cb4839a.arriba.rna_fusion.bedpe e46e1242e988a7211b5011a0a067cb86 4132 CGCI-HTMCP-CC 10b32c37-0e82-47e8-8ff8-91a14971737f 1e85a77f-3169-4dfa-8bfd-25dd8ca42076 Structural Variation Transcript Fusion RNA-Seq Arriba e897a45c-2027-4f81-8c0a-1c9457a78f64 1d7aaeb6d260ff5f2b8c5d410c719d51 3022 +ddd7e23c-e906-4d8b-9fb2-c609f7ab2ec2 531acfb3-5361-4b82-ad2a-3961b49832b9.arriba.rna_fusion.bedpe 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Structural Variation Structural Rearrangement WGS BRASS f48ea45c-ad09-4315-96b7-ae9638cd98f1 414dc51f9241df9696df167df6de19d8 89231 +4e0eda2a-4a08-402e-b854-d9f4de2665ed 2f629d4b-2c79-4e87-9807-5717177b3993.rna_seq.star_gene_counts.tsv.gz 46337b79ffd0ffc38c4108a7d7231670 416315 CGCI-HTMCP-CC f33eb114-1258-4fde-be0c-4a245f58e1ce 5cc1c82f-0d8a-4da3-a2b0-9c21acb54b52 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts b0ce23cd-fd00-41f9-91b0-3d210429f641 817ce9afbff35c356970379f9a0315d6 4238244 +ad34852d-19cf-4c2c-a6b7-eeeaa1c62b4a 83c5f64a-67ad-4b3e-91aa-1d80323df81c.rna_seq.star_splice_junctions.tsv.gz 04adf2469eb55f3f745121736d52c2e8 3576871 CGCI-HTMCP-CC 9e3c05ba-ba46-4e96-bdff-660ca34d6a4c bca27116-63cf-4b2a-9671-312ebcb9cec1 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 28603ac5-021e-4dbe-9395-2728b493f27b 4f50751801b60a500e108face4b6ccff 3641758 +fe6630ba-1922-47f1-a8b0-7f2d85e5805f 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48f7276f3a87945346bd6edd5f586f51 7955987791 +7a4670b6-98fd-49f6-952f-a74788b0a053 c71896b0-1440-480e-a0f0-d6aa9816d355.wgs.BRASS.raw_structural_variation.bedpe.gz b8fcdfd70977628a05d9a60f7120682b 15864 CGCI-HTMCP-CC 7324d4a5-804f-46da-9033-30a171f57a39 ad25eda6-3791-4e8d-b629-0b4fa0e26acd,2c41a7a3-6fe4-4164-ac8f-a0c4b0069fbc Somatic Structural Variation Structural Rearrangement WGS BRASS d86e92ca-6441-49d1-a097-1bc279f345cd 69bd008c7cd573f2f41deb3d4aeea589 53984 +efb4e2a2-68df-43c2-9bb7-87cda28e40d2 20893bac-08e3-41fe-a675-1a002b258ce1.rna_seq.genomic.gdc_realn.bam edb7af206c50b07aa932b2dd4bf18144 10600541665 CGCI-HTMCP-CC 7324d4a5-804f-46da-9033-30a171f57a39 ee3615de-1608-4975-bdc5-280b9521bc48 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome ae5d17e1-c21a-4b27-aca6-502b113f2a24 2aac3cc85d8d60eb6c36c95672f6d7e1 11843605709 +d2c91a96-6628-4510-9f40-1c70589650f6 ff76a220-7154-464a-a63c-ffa5ca55d972.wgs.ASCAT.gene_level.copy_number_variation.tsv f4f54139e7990a03f37b0a1065c58523 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Sequencing VarScan2 Annotation a41b1cfa-7029-4b13-b4b0-ddd76c524cfa 8d337a3a60b564c7316597c85d5d23d8 461313 +5f48d505-2428-425d-b257-4a7836189b61 f8bffab8-0efe-4359-944c-fbd1079633e0.wgs.ASCAT.gene_level.copy_number_variation.tsv f253621a30158f157c8ca32084319a92 3481162 CGCI-HTMCP-CC 86c618bc-c163-4fbc-99e8-330ae2f9e262 0ee5173b-263b-49d3-b561-eb72fa5067fb,9944fdb6-0893-4903-9274-3de5975f6266 Copy Number Variation Gene Level Copy Number WGS AscatNGS f66e320e-0de5-4c86-adba-f3479694a2a3 f5d9aabce58e69dad11417b7997e95c4 3441242 +e55f6e1a-3942-41a2-9ba1-d3b8d8efe27e 3a9ee309-5700-45ea-8b1d-0a1504e00119.wgs.BRASS.raw_structural_variation.bedpe.gz 4071b26f71e1eaf5670e176a4b563141 70094 CGCI-HTMCP-CC 9453db51-fff8-4a78-a29c-bb9151e9bd2a 10314658-6496-420c-8c03-75c66b4bdc07,dc5da41d-649c-4e2d-b40e-7c306454b524 Somatic Structural Variation Structural Rearrangement WGS BRASS 7039f411-578b-46ae-a5a0-5a9015bc7ca4 6e215217002833bcb5e5949809f1e7c9 237766 +0b1e5302-fb10-4991-b47d-cbb1ec9e7893 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Splice Junction Quantification RNA-Seq STAR - Counts 8abd7def-aa03-4692-ac7c-8db93017d5a2 c18d9fbb60f0d55a57c231e06920d0d9 3123602 +cbd6efb4-645a-4602-a406-bf34331ea2e3 af0ce0a3-6104-4a26-9314-49ed67162cd3.rna_seq.genomic.gdc_realn.bam 526e4d79acfc52f5e59660b3334fb49a 10414367240 CGCI-HTMCP-CC 4b0fa193-d964-4936-bb28-f21cb967e98a 8d98812a-8d03-42b9-b38e-ed16e323ba09 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 58054175-fada-42e4-81d2-3a4653224525 3ceae21fc637c129010a96fcad7f877b 11439158176 +863dd758-8002-4213-80cf-82bcc2c78455 c03521c4-310c-4c68-845f-7249650dc72b.targeted_sequencing.Pindel.aliquot.maf.gz 7c5be8264c3339804679d58321b45292 39854 CGCI-HTMCP-CC f4c882ce-97d0-4e91-a0f7-87fda1bc69ec 7ea73b09-36ac-48ec-b1d2-650a23d66c74,64922940-24cd-4a63-86d8-1a5ab6d9dd4e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation a736d686-8adb-4481-8bcf-effdd9cd0670 0765db4b213dbea9a712cb7d4f1b91cc 43957 +3c8f9699-6096-4efc-bb98-c6ba0f51a92e 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Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 0fe7e263-27cb-4915-9644-616ae54f69d2 6e5690795ff424264402ab9d2661b62b 229 +2f499031-d274-4e5e-9804-dc0d31e9841a acee06dd-b7f2-4271-86d9-da533aa71bb5.rna_seq.genomic.gdc_realn.bam 5ad4ce7ac211c513d5917a0c9e61d28d 8432474114 CGCI-HTMCP-CC f33eb114-1258-4fde-be0c-4a245f58e1ce 2ab19a78-aafb-473d-95ae-f7ad4d8e743f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 343d5def-7861-440d-9ec1-137d96376f6f 9dd439af4d4b67f3450e33b58a5d8acb 9018999965 +c2589547-afd6-4d54-99d6-2e944b6d1632 75786f93-15a9-4001-b008-132de127f6a5.rna_seq.transcriptome.gdc_realn.bam 2e72239d53fccbf3d84bac356597681f 9246700942 CGCI-HTMCP-CC ab45050e-2965-4d33-bff4-cd7a067ddd3d e8412071-23e1-41f7-b447-502f4f522ece Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 7777211a-7e8e-465c-b73f-bfbfee1e34e4 24a5a26b58c6a3e7a2b0be4201128854 10698509706 +5bbb719d-81fa-4e83-9fbb-544fbe2aa0bb 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SomaticSniper Annotation ea9b89db-5713-4dcb-9044-1fd1361a5ed7 517e017a932a0d40067d88f6c44a3c3f 374328 +dfa59194-f1cf-473f-821a-28939d827dba c853113f-fbae-448f-b85a-ae8b14646276.rna_seq.star_splice_junctions.tsv.gz 2776ed74b256dc0fde7ff52267f29a86 3046111 CGCI-HTMCP-CC c55be3b0-0da7-4923-a832-23301947fa3f 8022097d-87c6-465e-96a2-1129208e714b Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts db35d139-70ff-4e20-bf23-e82c4d08a883 d0fd919bdcad1d30c4600551595e800a 3116142 +79e8b65f-3548-4ab4-bd2a-65477b8cab21 9848f8c3-6920-4feb-90bb-8996eefea63b.rna_seq.genomic.gdc_realn.bam 99804dcdc0695f487e181536d366165a 11239758366 CGCI-HTMCP-CC 1276dea9-9082-494c-8ed4-37a5b2e3a062 06e85d70-7571-4dc9-ae55-6fceef22a741 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 3b7c7c89-5bc2-4656-9732-f7980b872808 58829ee694c738d63d705720d9b67c35 12151031077 +68d56bee-542a-48b8-a5fd-49008254d3bc d1ae08d8-1f85-4202-adaf-a968015eeefe.wgs.ASCAT.gene_level.copy_number_variation.tsv aeecebeeb9bd8cc8fde1a09a8e0d3834 3481144 CGCI-HTMCP-CC 458cbd14-a7ce-4d65-9caf-680c4c66e024 ba18bfe6-abdd-4ade-8580-64799f12614e,68d3b713-8c22-43b2-9074-9cb537abf752 Copy Number Variation Gene Level Copy Number WGS AscatNGS eaf0117c-ba3f-4caf-b407-5a57237a099a 298d01567a59e10c2f5417bcaf830a84 3441221 +59459075-bd09-4ddb-bde0-11d20a515104 38ef6fe0-306b-40de-9662-8f325b3ff5f9.targeted_sequencing.aliquot_ensemble_masked.maf.gz 3950255035f09c3a648f3c1cfba22b90 13021 CGCI-HTMCP-CC b4a85dc0-8269-47c8-a235-2ad7d1e69c62 c4e51a80-7ca2-41ae-9ddc-832049c779c5,83a2680d-7967-4939-b53f-bee3bed7fda5 Simple Nucleotide Variation Masked Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking 55789b17-0b7b-4f40-8b47-ba607ecdefee 5dcf0ac670496e1245c9cca40b10bb11 15873 +9bb68f5b-eba5-4dd9-a270-450035bf70a7 34c1dbae-0e74-4767-b6d8-da6cb743bc27.targeted_sequencing.MuSE.aliquot.maf.gz ca9678419ad6a0c1aadec4e9f93f6916 37308 CGCI-HTMCP-CC 8bc3d276-fa1c-4bbe-8af6-06eb87dde7e4 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+751489e3-5582-4083-995c-2a2411693991 afab6d6b-accf-4b7b-9ef0-7f86a6de9bfe.targeted_sequencing.SomaticSniper.aliquot.maf.gz 2327722c4fa9f24b0c27a4990617b0b8 382104 CGCI-HTMCP-CC 935ca1d3-2445-4f59-95a6-19f3311c1900 20c8d239-15ae-4119-a3f2-279d549a04c2,6f8c51d4-12a7-483e-8f0f-3cbd6f82d249 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation f555af25-ffb5-4c3f-9f89-7ca782f98a90 75f7cfeb637a14e36a43359e81a3d60f 472269 +15cd0865-216d-4b73-a8a4-c3cccb3a8f8a 52040536-b390-40e4-b362-6560e70ce364.wgs.BRASS.raw_structural_variation.bedpe.gz 98f1a2df1583bc1562ffc30d701fda40 27529 CGCI-HTMCP-CC 055ef10b-309e-4105-8379-ef6282d30c3a 56583cde-b22f-46d6-afbf-576cec230c66,4b584bdb-c3fb-4173-ad3e-99d567167667 Somatic Structural Variation Structural Rearrangement WGS BRASS 3ad6fc9f-261c-46d6-ac05-e3f09767e205 bd3821d7f09ebc2a89a2983738c4d353 91989 +1ea8fd8d-9cac-46e3-8e3d-6e9aeea62fe6 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1fa544b2-b74a-461d-ad92-a865a2e1af66 32b139505b13952574f1081cfdda3fd0 247306 +e294a452-c30b-4c39-bb63-9cde55ecd36c 032781ae-c4e5-476e-b051-4f626d13d91a.arriba.rna_fusion.bedpe 29293fcee6bad33fe0e62368a393825a 1774 CGCI-HTMCP-CC f33eb114-1258-4fde-be0c-4a245f58e1ce b7647128-a6ed-4ce4-9f3b-eefcd4bf1122 Structural Variation Transcript Fusion RNA-Seq Arriba 52330351-b3f5-471f-95f3-b3b379104f73 4268be5d2fc18b7a1f09b54f6c35b895 1504 +72ea3cb6-52db-4859-9d37-4645e1a6d626 796cb7ea-fad4-455a-81c2-23464dc4cfe6.targeted_sequencing.SomaticSniper.somatic_annotation.vcf.gz 45bd92def6fc8c6864eee2491add89a8 468803 CGCI-HTMCP-CC dcd1c0b2-e2d8-4537-9553-f3e69407ca82 201c0626-2787-45f8-af2b-3ab5e61840a8,2cde67ba-f110-4b96-8248-9f6bae93cab9 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation a3eda233-bf93-46b0-93d0-5e7c33ad8ded 465fbc0ca0af8f3f3b0c48ae4793d25b 489087 +72da46d3-d7b1-4262-8858-4698f54ec9c8 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4533b0458c3e57def71da1a8aa3b05ad 127278759 CGCI-HTMCP-CC e5e4671c-9a3f-418c-a37f-ef37f95262b1 0505cc2b-6b4b-46e0-9d17-823fa599e220 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ec4fe3c9-c774-403a-8c3e-3ec25405db0a 3e898fb7ea4af9011da6074d41ac3c8d 136792113 +cefc94d0-4567-40fd-985e-5356ca41cc02 6a91fcbc-5064-4dd9-bef7-e207207c7b4b.targeted_sequencing.Pindel.aliquot.maf.gz d88e0b3b8f8c68f03c0766e4eadc331a 46795 CGCI-HTMCP-CC 9d05b62c-6948-4a15-8599-503436349fbc b0e1047b-9579-44b9-a0c0-8afb9070bfc8,96fadb57-9dff-4d23-a3d1-d2a82af46e37 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation e610b937-f368-4259-8954-f8ad8b5012d1 90f7099ce34f8af01b7d192a7210be8e 52235 +4e1575e3-eafa-4545-8cdd-4bca77754acb d38bb0ea-94ca-4dfe-995c-9b25e9280fa0.wgs.ASCAT.gene_level.copy_number_variation.tsv 38dc6baf8d0e0cc201dac263ebf52ad9 3486700 CGCI-HTMCP-CC a7814814-6a54-425f-a7cd-a58b3e510ea1 62e9ab06-4e86-461b-bcd6-be7418bceed8,48a6ea79-e75e-429b-ba14-352019e6d120 Copy Number Variation Gene Level Copy Number WGS AscatNGS 133d6a84-f627-45e9-b74d-e29829ce1d84 2d46441a095ff598f4776b7e98d271e5 3446729 +d43d5cb7-27b8-40d0-824f-91b5bd81b113 739cbc17-984b-47a2-a9b1-0ff794814bd3.wgs.BRASS.raw_structural_variation.bedpe.gz 85c88a4f9398d5b4760543220b23ffc1 89403 CGCI-HTMCP-CC 9f527cfa-5e96-4bec-9566-858cd310733d 066cf459-271f-4985-a70b-35b88764ea38,1593909e-5d8b-46db-bf18-d74cb7f1c5c3 Somatic Structural Variation Structural Rearrangement WGS BRASS 33768105-59fd-481e-b32d-9dfe383fbd0b 9dc8984d96e1691bd613511123bcd004 301518 +537c9805-d5a3-42f5-b5aa-885f2e6259ea 87da8c7d-2da2-42c8-a3aa-69f023313786.targeted_sequencing.Pindel.somatic_annotation.vcf.gz 95761a599681314730bdf1bfac754efb 64235 CGCI-HTMCP-CC 80f4f6eb-e51d-4534-acdb-32a640a7b789 4ecea59e-6673-469e-8aa0-45cc0cbc0707,b5d6cc29-d08e-42ba-8a81-c311b49aa4d9 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation d20a3714-077b-442c-ba81-f4cc8f77ceef 3b1d3328b429fb5f3442a096fe24c1a9 68255 +98831aaf-4eab-4544-b490-05a347760804 45bad639-e043-49b3-9bef-2f6d05f128ae.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-HTMCP-CC 167beb25-035b-432e-8698-c9eb9e2b6b75 054e470f-ee2c-4d7b-ab17-c6be22558084 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 0edbd256-f99c-456d-82ff-b900a89c2391 a9b6c4fe22f3f1920d283c6fb1f04068 505 +73eee195-257d-43e1-96d8-c7f489f794fb 6a94d7ec-d3f2-440d-9c55-a2650ed623b2.targeted_sequencing.MuSE.aliquot.maf.gz 46a01e165cfc689b06d01e2dc838194e 225123 CGCI-HTMCP-CC 00bd58bd-223d-433e-b60a-5bf355f342b1 cd222e50-b1d0-4b7a-8b48-46fce16cabae,287961de-3e23-4e22-bb3d-57f5deedbeae Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation c6d72fcc-da4d-4dae-9b0c-e4e28ccf18b1 9247fab2e31c7bad7caa3b332ab074f2 259341 +a1e96a79-336a-48c8-8856-423bef648d95 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Reads RNA-Seq STAR 2-Pass Chimeric e8307239-c7cf-494b-8444-43ffafc5553d 478920081dc72958d34a404c396bc635 78786127 +a0cd3841-63b6-4c6f-a8c6-3be11fe68036 5deefe76-a320-49f7-9be1-5ab0e5f46216.arriba.rna_fusion.bedpe 412132c605a4415d551ae2dd5d6a9411 2288 CGCI-HTMCP-CC 29754644-2d3d-4e04-830c-4b1c845df651 15e226ff-48a1-48b2-9cd9-23094704ba9b Structural Variation Transcript Fusion RNA-Seq Arriba 5a236720-f947-4f0f-8670-b512aec34928 b23ffe9675bbe63a28e335900bd6aa09 1652 +dc3cc02a-b61f-4753-bb76-531829a089e7 a690a829-09df-4609-81ac-4ee4585b4cd8.rna_seq.star_splice_junctions.tsv.gz f164708736839efcfe4f32e6328f8b7b 4009867 CGCI-HTMCP-CC 444e50c8-c876-4d98-94a6-0a3474e2964b ebb6a3d7-cd36-4a4e-b0b1-c5c6795e69d6 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 4446ebc8-d8c7-481b-b02c-742cecedf27d a91f142aaa2705e820fffc977ab29cc0 4139949 +e4219bc5-beba-4f70-be26-59dba7b17664 8441b866-9a37-42e3-a3d6-abee30a0ab50.rna_seq.transcriptome.gdc_realn.bam 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STAR - Counts 5cc8d691-5510-479f-bb01-554c6ea24cd7 27b88d564833ba7e38388320e1804c52 3404184 +cdb1f028-b2c8-4299-b247-de104ca67b08 64b14f27-05ce-4a19-82ed-9104f18edc48.targeted_sequencing.aliquot_ensemble_raw.maf.gz eb0c9b65a9de4501e88e79ee9f0b4059 58828 CGCI-HTMCP-CC ecaf3572-236e-413d-8fed-1bf5dbb99364 96e73716-f7b3-4c2c-96e5-7e65ee3ccba8,593dcb32-3c31-45df-8a14-39bf5c0ac579 Simple Nucleotide Variation Aggregated Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking 939434c8-fba4-4213-99d1-ae2f8b1f9743 8f8f4214cd02f012f6a30ff54d631a28 75162 +d31ce3f9-9001-4db8-b4d7-2fee4a630fd8 9ce158e4-d4f5-4be8-bd52-5d21f012ee7b.wgs.BRASS.raw_structural_variation.bedpe.gz 449e3865063199af99f0e2f82fbc27c6 20138 CGCI-HTMCP-CC e799df87-488e-440c-96ec-4ca9e90a92ca 2cc8ce05-10ca-4738-8fa8-00e0553e4a3b,7cc636d9-5b1a-40f7-9a20-86944a52c35f Somatic Structural Variation Structural Rearrangement WGS BRASS 3a6ea649-0b41-4a41-be78-a36e890afe50 b60ea17f58163b5143ceafc4ac50208d 68281 +bf23e38f-c82f-47c2-a1d6-4a168a45d515 7c364bb0-21b2-45ec-b601-ec60abf4287c.wgs.BRASS.raw_structural_variation.bedpe.gz 2e26e55a788ef208068ad383cbc76007 74367 CGCI-HTMCP-CC 57b2ae7b-30c3-466d-a25c-fdc49c51a2cc 4710ca61-56ea-4a00-9c60-f8f6a2cf7ede,baa63e83-8217-412a-9b36-71dc06d85266 Somatic Structural Variation Structural Rearrangement WGS BRASS c450f6a2-4285-4885-9289-62159fe0d849 258da00bd278ec11617e00ce8398de89 255522 +c9b6a6a2-4d8a-4986-becc-01477393c985 392ed0c1-b436-4204-b9b2-0925a5e3225d.rna_seq.chimeric.gdc_realn.bam 2e82b2155b812070d281394f7a8b5bc5 120940725 CGCI-HTMCP-CC fbe7d31d-a533-4150-865d-641ad5d219bb d1b2984d-f7b8-4f22-817e-c13f3f31dacb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 2dd9a708-a754-4ebf-9f3b-292c05347f36 d4aeea4ed1ba7dec6ae26249922b0617 130320165 +7542a48e-0ec7-4906-a3a3-c1cec71fdff1 8f92e924-be96-4d72-8c9b-70b35ef0992a.rna_seq.chimeric.gdc_realn.bam 892080637846ba82cd5cb50d021fc04b 157851508 CGCI-HTMCP-CC 9054a4f0-91e7-4823-ad68-3150e8ae3733 83e05bcb-32b5-4b95-a0f0-e1cb641f8ff6 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b4253e33-665d-4475-a9eb-e076f30ed4d2 4b0a309696d5b30457a6ad174bb42bdf 164361148 +a4eeea94-238e-4d39-b01a-38f61fba463c 7d5ce19e-9961-4b00-ae86-e08359fc1dfc.rna_seq.chimeric.gdc_realn.bam 891e4aa36ddb454971b08907cc052658 138221984 CGCI-HTMCP-CC 7064054a-aaae-400e-b1cb-e37b27233af0 fa47c6d3-4903-4961-b7b1-1e5759a672b2 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric bf26e72c-41f9-48d5-9d70-0eac7cc56b07 e78eab8d68ef4c78091c8dbdbc70a035 142839505 +4277aabf-a0bd-47b7-b75b-0209b4dbe7f0 0f3d9e39-af66-438f-899e-b45cd28412f1.star_fusion.rna_fusion.bedpe 485c180b8b84b5ffa48f10d89ecb8f99 693 CGCI-HTMCP-CC 9f527cfa-5e96-4bec-9566-858cd310733d 37ed5c1f-4086-4fd2-8136-8a29e0b1c381 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 4c3f0171-9d3e-4d04-8bcf-a09d103fd96b aa1803236ab633d63f7962909da7124a 445 +2e70ad52-4d57-43db-9e1c-78de99008e70 f081102f-d6ca-4bba-966b-a20cd155d60e.rna_seq.star_gene_counts.tsv.gz 9fc8e1555b5c01b21ddb858fc91d8732 422862 CGCI-HTMCP-CC c64d5576-df00-4772-a3d1-1f8863000750 570b579c-c2c1-4fbf-8cd5-24076be4fd59 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 14648865-d8ba-410e-bd9f-ffcb12cd6e8d e5eb93b45f24fb1d8b22022c1ee94ba4 4242441 +f0886502-3302-4f4c-a906-a145a0cf22ac 193f22a5-e0c5-4d81-9527-60d9a9a2be25.rna_seq.star_gene_counts.tsv.gz 78d8e46c9b69b323257413563cee8e37 394008 CGCI-HTMCP-CC 41e3aba7-c1ba-456a-bb6d-f50ac792df28 b0bba8fd-b44c-44dc-8259-2de03379daa8 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 900c4432-e6e3-4953-b2ad-21d2e1332cdb 39dae5bcfe4b79247863945f112c2dde 4215688 +1033b896-d04b-4d06-9c9d-bdb15b642978 66f598cc-48fc-433f-9f44-0a29100f9d19.targeted_sequencing.Pindel.aliquot.maf.gz f69098756738f91e626280258db964ea 34122 CGCI-HTMCP-CC 2f87aa9b-5a34-44e9-9650-f564ecde26b5 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287febca-8224-43bc-ab6d-1b0cdfead762 c32919905fc93714d21fe3516a020d25 311661 +6bfed898-bfe8-4925-a498-a1c6b31c66b9 221f4ad8-0faf-41e5-92fa-257f72752cdb.wgs.ASCAT.gene_level.copy_number_variation.tsv 5742e821302c81f0a0393c7bf56c1346 3481150 CGCI-HTMCP-CC 2a7f1329-f4de-4ab7-b960-4dfe5f9eae3c fadf00dd-1666-456a-8d25-f1a8c143d4c1,ae4bd76e-5f44-40fc-87d4-8a9d0e48e98f Copy Number Variation Gene Level Copy Number WGS AscatNGS 8a728ea5-7692-4e99-8609-665784a84296 b419c680bb86bafd3f3513dc4870eb85 3441233 +3ab56b78-b40c-4c38-b52b-edb6a713f1cf b1229455-01de-4525-adc9-559f6021b16e.wgs.ASCAT.gene_level.copy_number_variation.tsv fdea1807708647fc5d93bc72177ce8b4 3481201 CGCI-HTMCP-CC 74b5fdf0-acb1-446e-a604-df12010a7384 7deb8f2b-d15c-433f-864e-2699f0cbb3f2,f3174ac8-a9fb-434e-891b-42ed6363092f Copy Number Variation Gene Level Copy Number WGS AscatNGS 9632c3ee-2fdc-4d01-8a71-84eb64e3a7ed 6bddc5a6a75841cb1b0ce9a28b6ea669 3441259 +88facf70-d293-47c2-a9d2-c29b6b1d2273 88f23b8c-af20-4aca-bc97-f1118f01ba2c.star_fusion.rna_fusion.bedpe bee0b528d0ccbbade19e4e6ac4bf2445 4961 CGCI-HTMCP-CC e5e4671c-9a3f-418c-a37f-ef37f95262b1 0505cc2b-6b4b-46e0-9d17-823fa599e220 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion cdbce656-d015-411d-bbc6-8d6e695a8ddf 6e5690795ff424264402ab9d2661b62b 229 +9c07495d-03b2-4f30-91d8-d924bb9a2372 462f63a0-a678-420c-93f0-65159d7f9f98.wgs.BRASS.raw_structural_variation.bedpe.gz 043d2253fa1cd69f0574ebcbd7bcbf83 155503 CGCI-HTMCP-CC e809c820-4623-4a88-8718-ea402b041a41 b6879274-70d3-4679-9765-9a2985425bd9,2f6b6e3b-c48d-48a2-9ae9-90b4604186a7 Somatic Structural Variation Structural Rearrangement WGS BRASS 02457918-67db-4e2f-8c7a-6c3b917dd655 9bb1d9b7116332cf9d46b2d9ab77cb7e 510671 +c743c692-95a8-482a-a7cc-bdf0a44f7aaa 3b851531-a4a6-4259-b376-bf62d9400e60.wgs.BRASS.raw_structural_variation.bedpe.gz 948bec8e7a9d2ab2a6022d31f1d20396 29791 CGCI-HTMCP-CC 80d31738-d3f2-42e6-871a-f0612812a678 8e3ca471-209d-4020-aabd-b578568ed791,7e3ca53e-bf1e-4d52-a332-9c9512e2038a Somatic Structural Variation Structural Rearrangement WGS BRASS 02da6ec6-341b-4f9f-bd8f-54cc5ceed88b f661db60a3ba026973f578abb10cec67 100421 +76416793-eaaa-4d9b-804f-27a616eb3aea 3a1f3b84-87b9-4560-a3f5-03cb78d1c1c2.wgs.ASCAT.gene_level.copy_number_variation.tsv 22c5f23a81188d580157099280bb2a6e 3481221 CGCI-HTMCP-CC 18395371-3c84-4d39-8ace-a3546e9ea34e 397bf1a5-4a14-49bf-b584-c97ee88f2556,d87766da-3f31-4fde-8dba-8d4ade8a3700 Copy Number Variation Gene Level Copy Number WGS AscatNGS 3c0ec7d3-2b5d-4f4d-b79f-c6cecd44145a 1550123baad05af5ae6ec37d0706116f 3441293 +702594b8-de48-4368-b468-d265210ad070 a0aa9e5e-770e-4eef-9fae-0747da02fb11.targeted_sequencing.SomaticSniper.aliquot.maf.gz ed4ec1fc91f3217124c585b80877947e 401618 CGCI-HTMCP-CC 20e986aa-0fff-4f8a-914c-8aad56568fd9 61945582-c06f-487a-be39-e5150f99799e,203454f0-62b1-4993-b9d5-557956361adb Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation d2ba7afd-8a82-420c-9b6f-3ef6cb9b532f 394d21d2f5f99f25382456411fea8b76 495937 +c2e63168-859a-4260-aa99-d59abd9b2c7f 2f6902b7-de5c-41c8-94f8-3568c8d0581a.arriba.rna_fusion.bedpe 406dfec45307691a130f83c7e5f2ddee 1298 CGCI-HTMCP-CC 7324d4a5-804f-46da-9033-30a171f57a39 ee3615de-1608-4975-bdc5-280b9521bc48 Structural Variation Transcript Fusion RNA-Seq Arriba 91e8a561-41d3-474c-9695-b80c811a49f1 362c4c2fa81a8d701af49fea83537f02 1606 +1d2a661c-9bdf-4732-aa58-5787ed977d1a 53794daa-e14a-43b7-b0aa-3fd2c5affaf8.star_fusion.rna_fusion.bedpe 7153a44eafc53fac14d221e9ba22acf7 6130 CGCI-HTMCP-CC 7324d4a5-804f-46da-9033-30a171f57a39 7f7a331a-07f0-4870-bece-8152ef6559ee Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 1011f65a-1abb-4584-931f-0180f6c1c026 36e3961059d5c4ecdecd3596930c7ddc 442 +783d1211-9556-4f02-b9b2-a72ccfabc554 10c6dfdc-f40b-488b-8d02-c500a7340698.rna_seq.genomic.gdc_realn.bam c44541b3d704da6b328d8eb14a00c377 9975343574 CGCI-HTMCP-CC 9485e946-f569-46fb-b77e-e5af68f7961a a5408215-f8d4-415a-b083-76af2c29dd8c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 6b0680f0-cdc0-4c6c-b2a7-4fcbaed4be2c d9efdba763621f6dd79a485569135962 11009491106 +b1d477d9-b3ba-4955-ab4e-c35f49c68f97 b2f9f574-dc69-401d-b90b-06f1d07d1564.targeted_sequencing.SomaticSniper.aliquot.maf.gz 44bb4d0fee6462b0fbfa8eb2bd93cdc7 446948 CGCI-HTMCP-CC e7c4ec49-f1d4-47fb-b827-77f08dadea1c 767d3e01-b514-4df3-a68b-e165b3de7866,3b7cd79e-b2b4-42ad-bba8-6e505b132d34 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation f5afce9a-d562-4625-b38f-7efd53f9c0a7 28104953a0aa45fafc9050a76070f736 569865 +8ec4e211-f613-4570-9e42-35e287f4e48d a9799022-1c20-4722-b4f8-75c2cc4a90c6.arriba.rna_fusion.bedpe d3be5fe6b61d3dc224542e4b1b78c783 3124 CGCI-HTMCP-CC e9230570-37a0-4bb6-bf21-170e830fe9dc af794645-48e8-4874-aee5-7fffcaf40730 Structural Variation Transcript Fusion RNA-Seq Arriba a30803c3-fd03-4f5b-81df-a6c6e2243bad 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Transcript Fusion RNA-Seq Arriba 017287c3-0560-4cc8-957c-8cf7d46b9a09 53c3c88b8091e8c9bce07c9bcb2a0366 1239 +57d524fc-736a-49d4-bfc7-26c5fa4e5c4c 933649f3-e4c4-4dda-9a01-102685df620d.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz 950539b3349f1142171dc509549ec7e4 1389452 CGCI-HTMCP-CC ca0b76f4-7196-44a2-990d-7d71c976148e 0ef6e6ab-1156-45e7-a347-9ef96d81e5a6,d29fe0e7-4e6c-4809-a934-071df69e475a Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 247f2443-62dd-4d55-a8b7-dce190361d6e 6cce88164eabdacaef4b796afb34379a 1437838 +7438a7b9-405a-41bb-a893-221442630ca2 731b1d41-2fd6-4fcf-bbc5-e5764bf92e90.rna_seq.star_splice_junctions.tsv.gz 9938245b07238342cec5bf4e026ab1f3 3261832 CGCI-HTMCP-CC 29d2a6dd-fb70-46ca-bfa3-0a00025970b7 b5999bd6-b915-483e-9ba2-8efa6aa2a2f3 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts fd3c681b-796a-4764-a520-84962afc2b51 31e4e0cc337fcab63cc17b3ae2f020d4 3331510 +c4ae585a-e81e-4a6e-81b0-022a5b7a0b7d 44c6a116-146f-43fd-aa1e-7e8b1636a722.wgs.BRASS.raw_structural_variation.bedpe.gz ff9b28d2b37bcf7cac339509ec87b7ef 40222 CGCI-HTMCP-CC dafcdbd9-18bb-42d5-9b97-7c9feb9c80c4 06bdce4e-3acc-4b09-8c3b-bec0ecf36a36,6da5e99c-97c7-4661-b3aa-a580ed5cd44f Somatic Structural Variation Structural Rearrangement WGS BRASS cab8fd70-9ac3-4ae6-88e2-85e76d685140 c8a8dc62d56997c191a284b8cafeb78f 134833 +c63eab9c-952b-4f03-b97d-f74a277832dd 1a63bc3d-b04d-41cc-9578-44bffc418c87.targeted_sequencing.Pindel.somatic_annotation.vcf.gz 84972b4619e994733627108ecb3b9381 75009 CGCI-HTMCP-CC 008d3744-e7f0-41a5-a419-702960cf1ccb 01bd2ddd-1bb3-451a-b6b2-7fe30cfd7f5a,902d99c9-ddb8-495a-8cda-cdd358668af6 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation 72356ed8-7785-400e-9049-b4cbb1efd23b 548f6a05931ae5030541b10ad834412f 75990 +3a696b61-fded-4816-bc9f-bd2dafd9e71c 5a08d4f6-b8f3-40ee-8931-1d521f6c7733.wgs.BRASS.raw_structural_variation.bedpe.gz 310b85f7e47ac5659b4703e2f295de67 19609 CGCI-HTMCP-CC 4b0fa193-d964-4936-bb28-f21cb967e98a bc40fa2a-a389-4539-81d0-ceff6b6237aa,c20e573a-e66c-4ffa-a372-eae49835142e Somatic Structural Variation Structural Rearrangement WGS BRASS eda1b18a-f342-4ce6-987e-e99f7b53d8e7 42319883593b63815a6cbafb685444e7 66326 +66d81002-0e0f-407c-a626-f58c63f392bf 7f734b66-eeab-4ef9-8178-b5591e5c2425.rna_seq.star_gene_counts.tsv.gz 940c90e3a6df76c6b4b9f42eb2bbf6a8 416550 CGCI-HTMCP-CC 7064054a-aaae-400e-b1cb-e37b27233af0 3a3e18cb-1129-4d72-af70-a9c1d08f7f1c Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 23c3726b-9c29-4943-bdf5-5f6b27be239b b02f8ceaed327f864e7628e1a403a5a8 4244738 +d3695a01-e392-47b3-a4d1-62419b45d7d4 cda48fe0-4943-4bca-a5ee-da1a0a9f331c.wgs.BRASS.raw_structural_variation.bedpe.gz 3a117fa723c7de99528008264193ba67 135041 CGCI-HTMCP-CC dcf269ff-f823-4eae-b604-ac9370920a34 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44cbb787-2949-44fa-9cdd-6264b1dd5db8.rna_seq.star_splice_junctions.tsv.gz 4cc5a9c7b6e85ae1e37ddb065a843869 2944605 CGCI-HTMCP-CC 59673b19-2e14-441f-9624-626ed0a3530b f8c00f0e-87a1-4e8b-88f4-ab62551d6160 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 6fed97dd-2a66-4883-85a1-025bb4d78931 cd35975308e9dcc6dbe376247a96b3b6 2997943 +06a33049-ff0e-47fb-8030-791e685a5520 ff76a220-7154-464a-a63c-ffa5ca55d972.wgs.BRASS.raw_structural_variation.bedpe.gz 4a2e80fed82f0710f46a2c7f0b9e68b4 26026 CGCI-HTMCP-CC 408b076a-0eee-4bc4-84eb-f5590c6f2a0f 662ba776-9f75-49b9-b379-4576b6a0b24b,2a5365db-1d73-49c0-8856-3f307847a281 Somatic Structural Variation Structural Rearrangement WGS BRASS 91fbad60-213b-4c1e-b513-9b66004dbe81 ef9fb5ec4c21cc13416387b09a24b61a 96944 +6b9790a6-84c7-49b6-aea1-f13bed7dfe23 c60d77a7-0281-43a0-b94b-c4cc9b45cfe7.targeted_sequencing.Pindel.aliquot.maf.gz 20ada5e25e800d0caa2c9d9468a89597 229145 CGCI-HTMCP-CC 67137e9d-c86c-4be0-bb0d-264faf6ad7b7 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2afe5f2b-ddd2-4957-8f0f-c71c7a1ebf09.rna_seq.chimeric.gdc_realn.bam 3d9d92aa21f4557f632db348cf88f2a5 48679186 CGCI-HTMCP-CC e852a316-a7d5-4e77-a5ea-c1a8e454d3e5 71afcbb3-f103-4d81-8c4a-56f896157eeb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 93e9de7f-d09a-47f1-bc2b-0b265bbb9b2a 99b5389e035f473e09b4667187d92a3e 51261156 +886490f5-1b3f-4e92-ad9f-984cea45a569 aae854e0-9cb2-466c-8a75-f6e418f4b7bc.rna_seq.transcriptome.gdc_realn.bam 4abc050d516dcc6e6de1c35a23bed3c5 18661952267 CGCI-HTMCP-CC 3860f2ec-0b31-468d-a18f-1de28fb6b07e 5c00342b-8993-4592-8e8f-b6063ee45737 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 1a9d3fc0-96ff-4d77-b103-b1cde9bcadd9 5231b33af2a3094dfa64863e025b2e48 22161476923 +88aaf9b9-f430-497c-89f2-d1de50712014 4d45b5e9-c3ce-42da-9488-177764e15078.targeted_sequencing.MuSE.aliquot.maf.gz 6b9935e8c333f98ec46fdaf9478a7452 78961 CGCI-HTMCP-CC 5395b92c-0ba5-4ee3-a63e-f1621db8daee 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5dc4208c-32aa-4888-8ea0-b87011d555c1 05e543e6c0a6f849b00ed3e54ac5289b 3577353 +7bc46e4f-2736-402e-bdc3-0b6ed5197bb7 89cf8d9d-9a70-45cb-bdf4-3aa2fb6394d7.targeted_sequencing.MuSE.somatic_annotation.vcf.gz 4ba868994379b6dc616bc5419376ab14 244196 CGCI-HTMCP-CC 9e1cab0c-e0ea-4f4c-bcb0-66df88c4f758 112f902b-8652-4067-9c4d-9446ca7479e1,d7593141-3f57-4c1f-876c-977a604998fa Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation f6ff3ad2-8918-43f8-b854-d660a5ccb91e 45e93489181c4763f6f58ef5adb11094 264392 +8e512dda-4b12-44a1-9da4-34e3f3595755 270b0f1a-1a2f-4551-8f32-64c6418dc49e.rna_seq.star_splice_junctions.tsv.gz d9937b4a65a0b1e113083eaf9e56aa39 3532142 CGCI-HTMCP-CC f30ffcfd-c672-4acd-9a4d-6c89368359ef 14a95b5c-6c2a-45c9-ac96-dd724574bc9f Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e95a3b64-fed3-431a-8bd3-9b1553411f86 27f1698bdbbaa359928aca440b08aac1 3624369 +474d5cd3-b844-4644-aee4-002d566e9b6a 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05b927d9005c05981a5d49aa7aad82d0 44866 +a545dfca-d555-4155-8821-703c8a333a14 5521db65-de2e-422a-96e3-f492f25e8e41.wgs.BRASS.raw_structural_variation.bedpe.gz 4e6af0b11d9b738903ccccbc41abbd3c 20512 CGCI-HTMCP-CC f02c03f9-530b-4952-b3a4-ac53469a7769 c54cb469-5f30-4df1-8adb-d83b79667b92,4d3f754f-ec9b-40f0-b9d1-c0cf85c19022 Somatic Structural Variation Structural Rearrangement WGS BRASS 07bc6dd5-8867-414d-baa8-2deb73c163ea a0182ec4e9643f01c5a3babb4cc6202e 70750 +a77d4366-1e6c-4ede-8e91-a3f5b6ab25d0 51b0c6a5-8411-4f01-8f55-9424877afee1.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz a682f2e077441b28f483efc5d54ee490 1578938 CGCI-HTMCP-CC 38aae9de-60c7-4dc6-9697-74729d498cd6 ee65156a-9871-4689-8f79-0d20f612e94e,b66a332a-aa62-48ff-83b7-7c04a481ac2b Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 89c9fd4b-dc62-4687-880d-8e7d27f123fc 981101029cb731fe35188600c106847a 1638376 +6cb268b0-b22a-4227-a020-63e64829f6ca 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Annotated Somatic Mutation Targeted Sequencing MuSE Annotation b4d5c513-d57d-4ab5-bf66-8d3fe22abb36 349aec77946cca38ce1deeebcbd7d41a 97013 +61c2bdf8-36f6-472c-9c4a-16f457af5359 d101dd17-20ac-4775-b71f-5a5aa41c5dbc.rna_seq.transcriptome.gdc_realn.bam 20a8f740325fe2c4efba6c46cceea9e1 8171575782 CGCI-HTMCP-CC 524db3de-46bd-4d47-b5bc-5d564fdc23e4 67f70cfd-7275-44c0-a910-601493852d3e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 64692845-155d-4362-9126-5ea3bec19cb2 74ec3b20c25a931b09d79b061eaf3195 9492288539 +81f7c32d-e921-4a8c-94be-6e7f32209e55 594289ce-a29e-41a7-abeb-491a7d4c8dc2.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz e45ac29db0c275dade08544fd3a8460e 1708495 CGCI-HTMCP-CC 8db95173-61a3-47bb-ad43-6569aa4750a3 99fac76d-3908-403c-9b34-627efca1493e,9a02b0c7-bb4c-47f8-98fb-e6fa8460fde4 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 152dfe2a-fae0-4a8a-b11f-4c03c507cb31 f29ff0bb2b4195754d5ca7ca5f0edba7 1775483 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58cd9ead-2930-4bdc-b89e-9dbdb4131c77 0e08f9279d52a371fbe1592830811019 3542 +a3f0dee4-13e9-4c7a-9c26-26aca765ab85 4164c691-32d0-447c-bef1-096fc1a4b3a1.wgs.BRASS.raw_structural_variation.bedpe.gz 14ed3ec2f36fdc90130afd5acc0f1e9a 50629 CGCI-HTMCP-CC e809c820-4623-4a88-8718-ea402b041a41 2f6b6e3b-c48d-48a2-9ae9-90b4604186a7,ae2616a7-f240-45cd-8d63-e9341571ce67 Somatic Structural Variation Structural Rearrangement WGS BRASS f69b9953-3372-4e5b-8be9-a6cbeef57d8a e13bccdab21770e433ffb83bc91b03e2 176955 +daf815d7-3f3c-4aae-bf7d-bd1ec87e886a ae662223-4570-4782-856f-2c335e8cdc3a.wgs.ASCAT.gene_level.copy_number_variation.tsv bfb62e1000fc8caca9fabfcc106e11f8 3482033 CGCI-HTMCP-CC 226914c5-e486-4041-9b0a-83ba8baae0e7 dcb25438-314a-4800-ad1e-a5484746d0a4,d3642029-34dd-4c87-8ce1-cf3bdc7bdeea Copy Number Variation Gene Level Copy Number WGS AscatNGS 7031a477-6be4-406c-bda9-307e975810bb 9986a7b56404a1e8daa816ceeccc21f0 3442186 +c17b6d48-a21d-48c0-a5ef-07fbd3ffb2ec 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f25261c7cadc5f1d72264632982d293e 121175298 +e021e0bc-3e6e-4813-a92c-b1b3535dd898 4625e531-2704-4c1f-aaa9-6908cbee0ffc.rna_seq.star_splice_junctions.tsv.gz 8de1c17a5f4db04780b552acdc648be0 3690651 CGCI-HTMCP-CC 981300da-9136-402a-88df-2c76b1e3ad87 64428b84-2e75-4610-9c81-27e379074b4c Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts db603487-3db5-4ac3-885e-e76df64df5d0 34927f25357367a1c86463e43c1c290e 3789032 +923af627-6cd7-45e9-8ce1-f4869debb349 16afeee8-917a-4682-abf6-3d599345fc28.wgs.BRASS.raw_structural_variation.bedpe.gz 462e8f2165375647b5bfa7f4ce3f1822 15130 CGCI-HTMCP-CC 1ffd0e35-68fd-4eaa-8b2b-a337fbdff5b9 f1e7cf5f-2335-4657-8e06-0794ed873ddd,900e0e61-e387-4be4-ba67-99423a0a23aa Somatic Structural Variation Structural Rearrangement WGS BRASS 7ac8cb6b-e853-4e48-9d30-797ed97f0cab d7d40b4ffbf5ff0746369a86930efed5 51678 +9dc1d42d-4535-4a1f-be46-b5969024a077 4e22539c-2a7a-4151-864c-ab741f9023a7.targeted_sequencing.Pindel.aliquot.maf.gz 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Ensemble Somatic Variant Merging and Masking dea67cb8-a1bb-40bf-8f09-84d885d824df 6290a1a5182c0fbf36deabd18dfd1b69 77514 +eb94a75e-bcad-453a-9673-8e39e6ef9a43 7075f018-4283-43b8-90cc-c3187a0a02ae.wgs.BRASS.raw_structural_variation.bedpe.gz d45f128f72023b2f699b8d611244f716 46895 CGCI-HTMCP-CC b0e055da-d580-4a7d-b100-06626537d6b3 5569e13b-6807-4a91-8d8c-c956d0679115,2d860b09-f5a2-4bc1-b8b2-abdb03db4cb1 Somatic Structural Variation Structural Rearrangement WGS BRASS df05bd11-01f4-4180-98cb-6826688e3837 901f248c777c3b9e911e425d6f598bc0 169698 +3dd25318-1ec3-4d06-8faf-5bb18f8c1251 8c3facfd-4c1d-42ec-89b2-4673ea9197f3.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz 5e516b6b21b9986b99732f564087720b 1220782 CGCI-HTMCP-CC 24d481bc-cab0-4fe9-a921-444341dfdf2b ecad8697-af20-41f0-b9e1-d967f41e98d4,9d2bc8b7-61ef-4edc-be78-f62752483b0e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 8a1203af-14d6-45ef-add4-10c51e833f78 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Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 9c5d0b4e-0fee-41ce-81bf-f9e06361cccb a8ecafae54581c25fbb9578dbe8d7796 47343 +18ab831b-5d5e-4f81-a49b-26ab32d542e2 b84ec666-4936-40b6-9d75-5512e3b1ea24.rna_seq.transcriptome.gdc_realn.bam 63a4f8973e276509be16d6fb933236c8 5100958261 CGCI-HTMCP-CC 055ef10b-309e-4105-8379-ef6282d30c3a fcce167e-01f7-4f68-bfac-b35a5fe0d412 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 6da39052-3306-4779-ab4b-91a3df0888d0 662eb95600c7d45adc3ec7f83fdaa9aa 6137295265 +fe1719c4-875e-4a6f-96e3-582984976f10 0fd48cdc-cc1b-4ad2-8041-2246ffa94a20.targeted_sequencing.MuSE.aliquot.maf.gz 488154d6bab92edd3120beeb716b4a44 55407 CGCI-HTMCP-CC 6a6d2c3b-4783-453e-8841-d72720701654 dde6dbda-51bf-41ff-a88c-b6ad4d1d4cc0,4be0450c-6be2-4079-b93d-aeca1c0512ad Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 97fc0f09-5d2b-434e-af21-6756ba4a5456 0ab49896dea6433670b4195cc6c3011c 66193 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+2ff1a71e-92ce-45b6-adb7-cfdf7f483c7a c4ff2ef9-a0bb-49e2-839c-1d5a22fe75b4.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz ae912dcc894cc1341a3e7b2096e5d7c8 1331931 CGCI-HTMCP-CC 54a2037c-8fae-4887-8414-15f9d932d616 6020dbef-d08c-4956-9365-55c72c4cf61b,027cde99-cf96-44ae-aa35-1c0ddc8b5d26 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation fd07ed16-e384-463e-b113-d0fed75974dc 78a596d364d42fb568510ba605b7a10c 1378824 +9ebf6bec-3d6f-43e9-9d82-7fb873d1f0ae fb9764f2-f5a6-4ab7-a2f7-6abbb01337f6.star_fusion.rna_fusion.bedpe c78efa2dce3d920cdfe2332ded53e0ce 6987 CGCI-HTMCP-CC 18bce2c3-5060-4282-b7a0-11ada9a3eebf f4960b39-bcbd-423a-9a48-dee201efa9bc Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 9bb32ccc-3236-4453-8e1f-7e5f40c7aed9 6e5690795ff424264402ab9d2661b62b 229 +57946ea5-7800-4b9e-98f5-abe66e431ea9 d4b671db-5294-4913-a890-3a7f42fc12dc.rna_seq.genomic.gdc_realn.bam e05c518fe21145c5af582659122d88f9 11847118789 CGCI-HTMCP-CC e809c820-4623-4a88-8718-ea402b041a41 fc5b92d2-3780-43ff-a5c3-b859012724a1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 58bdf45b-7c58-427f-a0d5-4a5c3e28fe22 33acc7e1f1191324f841ee82306db224 13639359205 +f30ab5e8-9238-405a-b062-d2d1d5311abb 6b14671c-8ccc-4221-b618-33166dac009f.wgs.ASCAT.gene_level.copy_number_variation.tsv 15de2ac66238e19bb34041fd283f22b6 3481560 CGCI-HTMCP-CC 9485e946-f569-46fb-b77e-e5af68f7961a 93fdf417-8bbf-4760-90e8-2bfa548f77f1,b415cfad-6d67-4e2f-aff9-aa43d9ca2848 Copy Number Variation Gene Level Copy Number WGS AscatNGS 29e08822-61f4-4efd-89f5-a929aaa478d3 79c8c7f6e3da906dc688276b5fc93e27 3441688 +76f268fa-a800-419d-9695-4c5ad75bb15b f3463785-a77a-4cc4-8820-c19fbddae7d0.targeted_sequencing.Pindel.aliquot.maf.gz 5d1f351a71ae9417454f0f1f6c918a80 37805 CGCI-HTMCP-CC 8bc3d276-fa1c-4bbe-8af6-06eb87dde7e4 b0910e6d-6a6e-4b8a-b247-b7164801ce08,01096fb0-186e-4258-b529-ddfb6299668f Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation df40e20e-55f0-47fc-875f-27c32e5903ed 9f3807e23d5a83483a24979430cbcf71 40423 +d301754d-69c3-414e-b83a-fc84839a94ea 0c97fcef-5243-48a2-9989-b5f454329f92.rna_seq.chimeric.gdc_realn.bam 9dd28619f0beed597db3f59c48da2b90 136635627 CGCI-HTMCP-CC e809c820-4623-4a88-8718-ea402b041a41 71da5f75-3a17-4929-b0ef-855551eb7dc7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 21dbe5c8-a6f1-4372-ba04-e815a759cf04 8aa0080b4682e467238ba30c16b4b7e9 143224157 +4bb9adbd-172f-4569-9dbc-722cee6c569c 8fff3c9c-f285-4dcf-8373-22fb017f4c88.rna_seq.transcriptome.gdc_realn.bam 07b7206133126c8b8d486a1d7413e593 20286274027 CGCI-HTMCP-CC 29e5a5cc-cba2-424b-a9e5-52218f563a01 ba777d6f-206d-41b6-a1a9-c927bbd20e06 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome da44e284-63e3-4024-acee-3844c91e9120 f8a3c4ddf085cd291d1e802fb54b27c9 23736175077 +cc44b3c5-3675-4207-a9d6-113fbc878ca9 f360536f-8102-4faf-8fa7-cd7d1a9b00de.targeted_sequencing.SomaticSniper.aliquot.maf.gz 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RNA-Seq STAR-Fusion 803eba0b-8050-4451-8ede-f740a698142c 6e5690795ff424264402ab9d2661b62b 229 +faa2bd2c-9e54-4c11-a00f-9a3831fa2180 2c669a3e-39f4-412a-b37e-6f13b5095043.rna_seq.star_splice_junctions.tsv.gz 6b6f0cdd59719a3fef9e8bdf572abb8e 3212875 CGCI-HTMCP-CC 8c2a5be8-0ae1-4b68-9692-ec607ae873e6 a527c3f7-0b43-4004-a972-3ee14af5c8de Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts bba5ad43-5924-4881-badd-9237e69751d3 495c8ebc5911ebed59ebc5c6323342d4 3292074 +6e7238ba-e61e-4c68-903e-73d2d7f85a08 8f2049e5-e7d7-4b84-a623-2c3f835f72f0.rna_seq.star_splice_junctions.tsv.gz b82e0170a2ad36b4fa5803d68ee51c1e 3419335 CGCI-HTMCP-CC 83a67229-d40b-4a02-9d23-46f0806643b1 ab5e21ed-444d-4849-880c-7bfee1b6023b Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 7b1c1aba-9f4d-401b-9a8b-11bfb580deaf c702768b25fb1ef8f993b946c207445d 3524913 +1f497e6a-29e1-4267-a986-bdd8de9d3d60 06e394f9-e6c2-4e03-9d44-4ea8dd764448.targeted_sequencing.MuSE.aliquot.maf.gz 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Arriba 7d620c2f-fb7f-4698-ab68-69c9f0fbd094 ae3325d30cdfa53f9fa6ab7353898c4f 2235 +d77756a0-3fa8-4cf9-a0fa-3890b5f7c792 657423f9-c6bf-471f-af15-2f092f0b76ef.targeted_sequencing.Pindel.somatic_annotation.vcf.gz 29f0d91e6a8b7d7f7177df6539e10010 39775 CGCI-HTMCP-CC 6e6440c2-750d-4440-a9ee-8f0f5c017093 7e52d4a8-84a2-45d5-b95f-74c201cc5731,cca5b8f7-0a98-4c63-8b45-016120a4d241 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation a9a5b9fc-d2b6-4887-a273-916d5401b175 8b86238fa2548f207697229583aec006 37610 +261439f9-b2e5-45f5-90b7-20d218e3d964 251298e3-711c-41b0-99ac-31da182b62f6.rna_seq.genomic.gdc_realn.bam e1cdd6d9cad7654c13a9688abd048660 10884518752 CGCI-HTMCP-CC a79ece94-3030-4e33-a9aa-623f430cd379 c952570c-05b8-4908-a159-ce644fae9982 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome d9d56b06-e0ca-4846-8e38-6641cf322c5a 9f6b4b9082b84940b728eb6cf7e5be7c 12284028129 +659d436b-6175-4123-842e-f089af8d2c41 96424ac8-df97-4cf5-9dae-b8ecf7c49eb8.rna_seq.transcriptome.gdc_realn.bam fa6508c239f5cdb67c9732a300029b50 20852862580 CGCI-HTMCP-CC 9453db51-fff8-4a78-a29c-bb9151e9bd2a 7eaabb44-7e3e-4fbe-afd9-5d37541c0fdd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome c2915f9f-1078-4817-ad7e-7c04d19bf773 94044d895de31bb82657d5eec630eb50 25168024931 +1e2ebf8a-c9af-4f2e-b431-5f5f5fa40898 c5d49403-dca6-4fda-ad11-4d457e180b3a.targeted_sequencing.MuSE.aliquot.maf.gz e9a7309ee2252e7fc48238fbf4efe0f7 50324 CGCI-HTMCP-CC c5789e82-9269-4bd7-9a24-ee7fceeb6239 33535e50-62f3-4bb1-90a8-07b41f749a41,2c11d59b-99ea-458e-b692-8435480ce229 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 4bf0459c-f7d9-40bb-88d4-54d0d6df0933 16e49088ce991d1ccbbebf0a2529750d 61353 +d7a2dfce-3afd-4b86-8b32-b2ea513008d7 c2972174-5bef-4c49-b0e0-0a947b570295.rna_seq.star_splice_junctions.tsv.gz 9cc79839f73ff8bceea7f35235706933 3656132 CGCI-HTMCP-CC 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Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation 735a997f-1417-436b-84a2-e2823703ef55 078fcc04fc46fb5df43d3eeb92eb32d9 34328 +518f5f8a-dc1b-45b2-87f0-4e6a3c09ee25 603117b7-cd62-457b-a146-cd600c822b98.rna_seq.transcriptome.gdc_realn.bam c301070fc131b1ddae327cd06a54102f 18624499968 CGCI-HTMCP-CC f429c531-358b-413d-ba3e-50ea945e68cf a0f6d9e8-9af9-4f33-abf9-ff95f654bb83 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 9373f002-f83f-4eaa-8f4f-77386eddc68c 57aec4635ed62441841717205f9b8c26 21966476070 +c0aeebb9-8859-47c9-9e18-0f9967be03e2 e062ce8a-472a-4445-9cf2-b8927e739af7.targeted_sequencing.MuSE.somatic_annotation.vcf.gz 3a36cacb0d7d99957b542b0e2ac4a942 87738 CGCI-HTMCP-CC 6a644c98-5c38-47c8-8f89-7644d0570d03 e58562db-d0e2-4869-8d3b-9219ca1ceac7,8522de75-a1b9-4dfe-9942-da405875c0e9 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation aa261c4d-9f94-46d9-94c7-099cae8403a9 383d77ea36a1dc161eda5ecc7cf11afb 92608 +1907befd-f8cd-4645-97f5-4e79320f7b5d 3ca80249-5a72-425b-abce-95b8a432ed8b.wgs.BRASS.raw_structural_variation.bedpe.gz a448265226443e233cb29397f8b78e96 34542 CGCI-HTMCP-CC d7f536a7-3cb7-4f45-83c5-9f49b8cb84e8 0cdf6388-a545-44e4-ae69-70cf015e1d68,4008b80d-2f07-4fa9-bb98-2ade471a0cf9 Somatic Structural Variation Structural Rearrangement WGS BRASS f9773aac-5f49-4463-b7d8-28f3733730d2 5fcee612bfe16226b0a031d9e35bd613 117902 +4b547967-61a2-4e0c-988b-af9aaa38cdef 852776ab-970b-4f18-8f68-4efac4044955.wgs.BRASS.raw_structural_variation.bedpe.gz 834a4d57e720c276f2639f80b73e1d6f 41598 CGCI-HTMCP-CC 59673b19-2e14-441f-9624-626ed0a3530b e2488f68-8e42-4616-a58f-3fc2ded230c9,94177f96-29fb-4707-b91b-c1eefa702d3e Somatic Structural Variation Structural Rearrangement WGS BRASS fce26c18-9d63-4bb6-810b-f36db523f40c 6f0b4e89c142cf34235f432ca37a7900 137478 +8745124d-15fc-4b0b-9b72-3a50a89785da d9819313-a623-4404-bb84-eefe2d895f24.rna_seq.genomic.gdc_realn.bam 05094d1bec82da83067742c3e6843e39 18369402075 CGCI-HTMCP-CC 1ffd0e35-68fd-4eaa-8b2b-a337fbdff5b9 42213ae3-477d-4470-a773-ee9d03145f7b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 01d70852-a3b0-4ae2-a409-52f0b56ae26b 109d6f04804f551464d536e173dcf529 20705107084 +42b98aa3-b33e-4946-bc8a-83bdde468dda 09745a5b-462c-47fa-a830-4da0c50fde47.targeted_sequencing.SomaticSniper.aliquot.maf.gz e892cfcb069165a6df92f91d7b9b746a 516255 CGCI-HTMCP-CC 6ade3770-2446-468a-adae-e87f5ca4ce7a daef2e44-7018-4c50-b8cd-e21b1c19bcb0,3566c2c9-2bb4-4557-8849-db7e1c103b71 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation ed4b7060-eace-4524-a192-9d4fef132cbc 33ee2909d6ac7c7c0f73f57e4bd03cd1 640508 +f386d4bd-6cf7-4884-ae91-bb6832fab800 4aaedfaf-c328-4843-9877-6460eea10f26.rna_seq.transcriptome.gdc_realn.bam 1b522fdb5c382e72b5bcb9b29bd5f779 20783719154 CGCI-HTMCP-CC 62353e57-3bc0-40a1-9a46-0dedccb47398 ec6c108c-c87b-4e87-9e96-306973654ed0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome cec09d46-35c6-42a4-a21f-64a6e6cb53bb 2df33c7966bfb222bc97d309d54e3268 24784153148 +b8fe0289-aa98-4265-ab0d-3ffafcfc011e ac35c43a-5da4-426b-9202-e516a9dfcb73.rna_seq.genomic.gdc_realn.bam b6669ee1171e6395c8255ff69de83808 8998502028 CGCI-HTMCP-CC 57b2ae7b-30c3-466d-a25c-fdc49c51a2cc 0ec4d903-a1c0-43b5-8db2-180c1dd1c22d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 797d438d-ca71-43f8-9dbb-db9428272d00 28c2fca0b5dcf051a9b255f6f93156a1 10056145631 +0851563f-f0f4-48b5-ae9e-62eaf30c88cb 3a962097-9403-47ba-84cd-1ee08445a59d.rna_seq.transcriptome.gdc_realn.bam 00aa606ba2577a8b51ab563f9938369b 5677757512 CGCI-HTMCP-CC a7814814-6a54-425f-a7cd-a58b3e510ea1 761dc734-2349-4fce-8b76-b5d89106c251 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2728dfa0-eba7-4327-ab9e-390b4b2fe0d8 e4bcd31e1211bce347c4057b7bd39e68 7540852630 +0602f36a-550d-40bf-ad01-544ee224b32f ab4a23f1-6a10-4160-9268-869d3266d615.wgs.ASCAT.gene_level.copy_number_variation.tsv 99dc8c0832d14b190355f7847ba0c4af 3481308 CGCI-HTMCP-CC 6a234e08-449e-463b-b442-28a3ec74ff39 45d7e758-3588-4a01-a269-01a3adc04f98,5583f070-8098-439b-81f6-216fa2321a6e Copy Number Variation Gene Level Copy Number WGS AscatNGS 6cf8bd09-5d86-4063-9275-a6a00a13d598 a604928cd3fbbcde350f1ee972c5bf06 3441377 +cc483cde-a511-4d13-9265-76a16bc6e1a9 371de264-4d15-4cee-93e4-92503b4c1adc.targeted_sequencing.Pindel.somatic_annotation.vcf.gz 9fa7fb8d6877316bf41ec157e4a22e7e 126858 CGCI-HTMCP-CC 98896129-6a32-4904-a619-daca9b0b0db2 188b787c-af9a-488b-915c-c46f45635dc4,98a10300-701d-4296-8f7c-2dafa17abbd8 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation 5aa8740c-8be3-46dc-97b1-056af3c09926 f0f9a6a59e104f44a2a6f733edfc35ba 133636 +5c53f988-e9f2-4419-b2a7-b31838c0f7cb 1359595e-b18a-49be-91e4-b1ef28fb99e7.targeted_sequencing.aliquot_ensemble_raw.maf.gz 6ac81fcfc4758a64b8d56e2163a5032d 57681 CGCI-HTMCP-CC aaac33e8-d33e-4ae9-8683-c4031a1dd803 110243ae-e8e0-4b73-a3e4-b7e85c72f257,975e4cc3-f9ab-4dd9-b4a9-ab2769eb288e Simple Nucleotide Variation Aggregated Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking 3f03f2b0-aebd-48e3-9ee3-b7c0f19fdadd e5c772d443b67fc9810de6b13b602785 73465 +2cab41aa-f1f1-43a9-9d0a-54365e7e2e55 d00bb2ac-693b-4f03-acb8-d012e856718c.star_fusion.rna_fusion.bedpe c9b255066569bfa28a97e833e4de938e 4537 CGCI-HTMCP-CC ba5e5f27-689b-49e4-a5f9-4007a8bcd2f0 e470f6ac-6e41-4ec3-b131-16bbe3849360 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion eb350d6a-5a96-42b2-8299-d1e988c89857 96e565974b5eb1295e72ad77c5eb5283 1165 +ce591057-852f-470b-b956-7db06d69e6fe a0810898-18c1-4821-a7b0-ab746db2a38e.targeted_sequencing.Pindel.aliquot.maf.gz a4126c57b73058fafb5bcaa4031d9082 35163 CGCI-HTMCP-CC 6bcba66e-2c17-4134-afad-c8ee85d4e1b9 9e13cc51-8257-4eba-81b9-dd1e7a6297d2,e2d10187-1023-4cd8-a127-0f8842d9158e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation bf1a5945-a4ab-4518-9fe3-c6118e94ca47 17a704c928fd6a1f12a5590ef0917d37 37655 +5f0f0a1c-224a-4da7-ac2f-3d342ad6456f ba8f1266-43bd-46d6-9415-d8a5e25cbde0.targeted_sequencing.aliquot_ensemble_masked.maf.gz b881c63a410dc05f5db26f53f1614851 19267 CGCI-HTMCP-CC b5b83242-ef5d-4922-815b-05f88000dcd6 68e61c36-8909-4496-ae65-25ae4d050023,e4402bd5-53b2-4421-bcb4-72e9a8262b42 Simple Nucleotide Variation Masked Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking df359d50-0d40-48d0-8b54-5947e2815bc9 15f0b74e9d01d8d383f6c1d20f594e4e 23361 +3f198f55-745d-4eb0-80bb-31bcabdcb7f8 d0417f51-0cba-4fb7-8214-3bda983ac2fd.star_fusion.rna_fusion.bedpe 0e5184eadc77e0512f1db21c0fdb6a05 5374 CGCI-HTMCP-CC c1c342a6-e8c0-41e9-906f-bb03adb5db72 f3038ab8-5fc4-432d-be03-3339f6027c27 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion c744afe6-fb94-41ad-9baf-df67201c3bfc 40554d1afba5c96ba3294bd0b3516bb8 476 +d651d2ad-ba33-42fb-b0f0-9ac639d2fb15 e64d6089-073a-4d31-a2da-efb6c68abaab.rna_seq.star_gene_counts.tsv.gz 22813a28e8c21d979301843f0e1636ce 421939 CGCI-HTMCP-CC a7814814-6a54-425f-a7cd-a58b3e510ea1 d56ecb9e-322d-407d-ac57-b6c2b7fc699a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 636e582f-35ea-4898-9643-36af86a9a37c 35333aee945987336b394bd034e2d05a 4242675 +ed8aef47-2b48-4964-97c4-affba093e26b 1e7d3382-112b-4288-a2f7-0c9c3a3d82cc.targeted_sequencing.MuTect2.aliquot.maf.gz a5f5dc2820db595e78b0f156fb8d61f4 1174110 CGCI-HTMCP-CC 146bd9db-1645-4950-bd18-de30d0db2487 a64490ad-fc6a-445f-8a8b-cfe86e0f9274,b12b77a7-d93c-4580-9f57-12bd1d83d962 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation faade710-4e8b-4161-b3b9-5c4eb7f06cc0 0753de8df3f50176c7534ad8f75cd05d 1448083 +b1b3de9a-e52f-4759-8384-2ac572c753e6 3cff6f11-ced6-4929-a850-0fecc83d1fef.star_fusion.rna_fusion.bedpe c20d65106127b67f7115bdfa44872951 10358 CGCI-HTMCP-CC 853ee313-7d90-4a57-8f98-5b633bd1273b 6675277a-f1f3-422b-8540-d93453b4e6d5 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion d069e443-302a-4187-b892-e635c07701e3 9e4c091f1bc12135672006bb654ea3f8 2233 +a6971133-90cb-4a08-8b21-365155587285 9d1e8a99-0dee-45fc-abac-72e5f26af8d1.wgs.ASCAT.gene_level.copy_number_variation.tsv cd64a4449189773306d6e0dab53e21e7 3481256 CGCI-HTMCP-CC 4e0d653d-21f0-468d-91e6-bca55dcddfb0 115c46d6-3e94-49d1-aea0-37398f026edf,83ce052c-578f-44cd-9b13-020e28976465 Copy Number Variation Gene Level Copy Number WGS AscatNGS e99a3b6e-b89e-4e95-9927-01e2ee042947 9ca646f47025bb054b51bb574d42983a 3441338 +f8e3ec1b-3895-4824-810f-31875db70cc8 e6452eaa-a6ed-4c1d-a8e2-5a23f5f60694.targeted_sequencing.MuSE.aliquot.maf.gz 380c56ea3d626d22140e368fa9f25760 48410 CGCI-HTMCP-CC e29d9d25-349f-4cf8-9bee-68cc4a95c353 70097847-9572-4bbc-b8d7-7e26a39d2fe9,1ed27bc9-80a8-456e-869c-6d0b98025a49 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE 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Sequencing MuSE Annotation 2a22b392-8e3c-46cd-88ff-8ea27b190bd4 ba856645fc11796e45fe53a0662d1273 69956 +c8cdbed2-3bf0-44ec-a0ed-84bf3f943890 62f7429a-0a96-45c8-8e30-5456ac76fb6a.rna_seq.genomic.gdc_realn.bam e6859f65c11c1b3d4ef9d5f08fef0e00 9433149949 CGCI-HTMCP-CC 2c776c4f-fade-4035-8de6-e91c45c8347a a8f5d28e-e97e-45c6-a213-5b21ad88b001 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 7afcccaf-b5ae-4f90-9b5d-5bcee5e390db 3fba4565d073f7bf5c62892a5d9821b4 10277635613 +3cc5f792-2a3c-4cb9-b06f-c9f6479608d1 21d8ac4d-2aa9-4ab2-ab33-245321c6bef4.rna_seq.transcriptome.gdc_realn.bam 8fe28b6aadaec8d7364e4475c4a155c4 20357704382 CGCI-HTMCP-CC 8859b1ba-2d81-43e5-a845-4966ca6866da 3cefe529-49a4-48ad-b452-1be6396be4c4 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome aa095d59-78bc-41bd-9371-b041e1ab18ff b095b15caaa17e90d39db785a0f4eb87 23454093115 +9ebb6889-ffa5-40a2-905c-e6c1ed42a26c 5ce887d6-ae69-45eb-99c7-9a136048ac3f.targeted_sequencing.aliquot_ensemble_masked.maf.gz 3be0b1d216a3d2fad3beb3305140b336 18582 CGCI-HTMCP-CC c2e875d2-1832-4f94-b8d8-9c0fab711ef0 e8321e97-f086-4886-bdc6-36d8304fec80,88fd30dd-d014-4aae-9aa9-565c025cb586 Simple Nucleotide Variation Masked Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking fd28bcf3-85e4-49d3-afbb-2addc178b23b 97a9ee57dba75b1fd9c64f7e3c5c8b71 24497 +5569cf37-1c90-4f83-8dd1-a730eb5d7195 68454436-6f87-4986-85ad-336bf43164b1.wgs.ASCAT.gene_level.copy_number_variation.tsv 6b301a9487b88e7b53868be052fdb650 3481321 CGCI-HTMCP-CC a637ed37-86cb-4838-b7f1-488dd021cf43 b69dface-c2e4-4cc8-a44f-29a22f784186,7e5fc360-9599-483b-8835-b8c1be085cdb Copy Number Variation Gene Level Copy Number WGS AscatNGS 2c1f9fa9-c0fc-4813-9a9e-2c59ae4310ac 07cc3affa0a6936ee8e660067668f9aa 3441460 +2ff6df67-9ae7-4f4f-8eb5-5a7423976e45 749f5eb0-46b6-424d-8663-668bb4f9902f.targeted_sequencing.SomaticSniper.aliquot.maf.gz 4720e07980f56fbcc71b2d26991f9502 762573 CGCI-HTMCP-CC 67137e9d-c86c-4be0-bb0d-264faf6ad7b7 23524e10-60a0-42e1-a2f1-0d76fca7b0b3,de85b254-6007-4847-b22f-2522336071df Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation 2ef6544f-3290-47f1-a107-f2a2c07658fa 9af8a6df00adea32e4e47c497d96ba7a 923894 +326280d0-13e2-4051-8a74-1ae3ce5edb60 251298e3-711c-41b0-99ac-31da182b62f6.rna_seq.star_splice_junctions.tsv.gz 3594756cd32c2aae44a2e07d610ee976 3116892 CGCI-HTMCP-CC a79ece94-3030-4e33-a9aa-623f430cd379 c952570c-05b8-4908-a159-ce644fae9982 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 38a13a23-9ba0-419b-b2c5-611476198be8 d2d869e21d7072be2e56e056c465c59a 3240002 +3e58228a-5422-48b5-9cc8-18d6629b042a 38346d96-751d-47f8-a597-4eb93d15ed57.targeted_sequencing.SomaticSniper.aliquot.maf.gz 78ecfaaadfe3deda0f40a8356045eb49 304876 CGCI-HTMCP-CC 315ab29d-5f34-458b-872b-31eb4fef3916 571e6910-84b9-4db7-9f33-0e78f826a6e8,5c91494e-1ea3-4448-98c9-8d56dd1bc1dc Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation de697070-50c3-4b7b-87b4-7936e9065c1a 1c5c408ab2bd03222454759f09787fe5 377907 +76e0cfe9-e0ed-403d-9d8e-c5c3a8f7b925 99af7aff-e2ce-4998-bdd4-bb53724c9f26.targeted_sequencing.Pindel.somatic_annotation.vcf.gz c30187e837166aab569d578ab1156b42 43005 CGCI-HTMCP-CC d4c922a2-2571-4516-ae9b-d24d17e32e6d a75118be-c1c6-499a-bdef-1f6f7d247ba4,569cf55e-3c02-483a-8251-d8c6fe68ddd4 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation ebe23478-c5b4-4e1c-9670-b44cd3dfacf0 2a3f29dd076fc88a00c7df5a31bf3cc6 44637 +f3254f99-598d-4dad-ac38-710eff8621f1 14072c1d-d87c-402c-90ed-59aa1928ea88.rna_seq.star_splice_junctions.tsv.gz 7f4395e68a5a90026d696782ef251cab 3773370 CGCI-HTMCP-CC 8c2a5be8-0ae1-4b68-9692-ec607ae873e6 b1299fb3-0cef-4bc4-a2bc-de2d588bc8c0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 8c1c1c98-e3da-4560-b750-61d98db88202 cc33e748c1a9dc1adff7fde5473a75dc 3901970 +8f93b106-10cb-45c1-b36d-68d7c8681300 5ebd7e79-5020-40a8-8318-c2d5e9458d85.rna_seq.star_gene_counts.tsv.gz 8e3ecde8bfbb442e74a1ecd09f0d7c52 404767 CGCI-HTMCP-CC f02c03f9-530b-4952-b3a4-ac53469a7769 15549949-0d6d-417a-98d5-2b44b464f3ad Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 46507c27-43f4-4a43-b8c9-4d366ebcb811 d79db5deeae4e747f568c3ba217100f3 4226190 +990bfec2-8133-4928-add4-fb0a04a475bb 69e81b22-0276-4993-8ca5-91ab4ebeb11a.arriba.rna_fusion.bedpe 1b0e8f2efd75025926bdcaad4542661e 2236 CGCI-HTMCP-CC 7324d4a5-804f-46da-9033-30a171f57a39 2c6b8b65-1a5d-4ddf-8b8b-c64b86dfdb4a Structural Variation Transcript Fusion RNA-Seq Arriba 5d069f03-4dd9-4d5f-9515-04346af22d90 599f5a9c467797d4bd8bc4910cf4c7bb 1933 +eea63e03-c3e7-4fcc-848f-dd8cc1202d43 1763a12c-1843-415d-9463-d8dbcece0077.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz 878b100cf54275d9d59de24401e6cbcf 1467510 CGCI-HTMCP-CC b27381ed-ae11-4f72-bd90-3f5c567de192 c5f5d96a-ffa8-48bc-89fd-2cd4ad9bdfa9,6098863c-886c-4ce6-944d-e4641e2c6303 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 2dc9829c-6bfe-4330-8e42-482d9b2038f6 947a8fe39b4a75307f39a3c4d229f001 1511769 +523af3bc-ce35-4c6b-b6be-0de18785b871 8159494d-02db-40b1-b153-3fcb4bfad7bd.targeted_sequencing.VarScan2.somatic_annotation.vcf.gz 2d9f92e577a316688c4a32385c8e8873 234721 CGCI-HTMCP-CC aaac33e8-d33e-4ae9-8683-c4031a1dd803 110243ae-e8e0-4b73-a3e4-b7e85c72f257,975e4cc3-f9ab-4dd9-b4a9-ab2769eb288e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 98d2ec4b-6968-4c76-9dba-dc01af182b43 e2effc891aa84490314fcf23408a2467 242204 +d14253fb-123b-4cea-a786-ef19c7a69ea5 2609d44e-4d44-4c05-94a7-9d47112fbbbe.targeted_sequencing.MuSE.aliquot.maf.gz 7e36d6cb581bf5443613dc1bc1c9aa95 136081 CGCI-HTMCP-CC 6e6440c2-750d-4440-a9ee-8f0f5c017093 7e52d4a8-84a2-45d5-b95f-74c201cc5731,cca5b8f7-0a98-4c63-8b45-016120a4d241 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation f13de369-63d2-4bc7-81d9-60d121da2678 9adcf59ba91850a47add0bc7d1a443d0 159643 +ef0af024-6218-419d-b412-0961c95c8646 b2df1349-fdd2-41a2-8172-76ee5b8fb48d.rna_seq.chimeric.gdc_realn.bam e55a70712a358ba708bb3f31b4ae611b 305294243 CGCI-HTMCP-CC 408b076a-0eee-4bc4-84eb-f5590c6f2a0f d1f9a1a5-4d9b-41e3-b90c-09dc4105e5ec Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric bbf6c73a-44c2-43f7-ae5e-c535c6b73c5b 702609a2f8d30c4e13e8e06e37a24407 327683762 +d761ca92-4283-48c1-aad6-86940f375ea7 463a833c-2d3f-40a6-a83c-a861705fcd81.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CGCI-HTMCP-CC 90ab8522-2dcf-4afd-86dc-80562582cfb2 119b6d3d-7e0e-4268-9b79-2e0fc95256ad Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 67d73be2-0b68-47a1-9c0c-b9b3960fd546 6e5690795ff424264402ab9d2661b62b 229 +11538af7-28e2-4491-994b-63da3e0dbb0c 6cb9bca4-c5f8-4451-81d1-b529c4d74801.targeted_sequencing.aliquot_ensemble_masked.maf.gz 593791c56e0477cada27f56110da20b8 18655 CGCI-HTMCP-CC cbc1f56f-0d31-450c-81d2-507680895c7e 356e8e02-c53e-4170-b3c4-a21b186e5f33,edab739a-fc29-4a3a-a7d0-80eb35761197 Simple Nucleotide Variation Masked Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking 7df02378-e9c4-4e58-8b6e-01df63d0274e d838434e153b6a0b1e8bac413df3780c 24969 +9a9303e3-b54a-4951-b86e-9f3c1b50361f 4a8a37e6-efba-42b4-9ec4-80a248cd36e0.rna_seq.chimeric.gdc_realn.bam de7517f06d3b271f0a0d627fbc3fc7b6 146835702 CGCI-HTMCP-CC 92da3fd3-df36-43aa-a777-5f693636940b 01bcb5c4-f3cd-412a-9142-684d4aff8364 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e4877ed7-6ca1-4510-a45d-23c02c54c518 0c33f80c6abff1926cb35861759bc02e 151679185 +6ced82e4-bec5-44b8-aae3-84664dc1e655 d47ee584-6e3f-4464-973a-38755d8803a6.wgs.ASCAT.gene_level.copy_number_variation.tsv 285ba4f06574d7973d1403f025cb5e0a 3481163 CGCI-HTMCP-CC ab45050e-2965-4d33-bff4-cd7a067ddd3d 030764fa-53e5-4322-8287-594f9c01d7af,44af9ea9-871b-40e9-86ec-84c795225fe5 Copy Number Variation Gene Level Copy Number WGS AscatNGS fdeb5ce2-3012-4266-9ae2-ba123ad018b9 527a34dbe5c7cb3f4212b65eec2b02ed 3441236 +1df8490a-4fc3-468c-89de-e3a15f5184f0 2b527e30-585a-4cff-84ad-cc5993de3e95.targeted_sequencing.VarScan2.somatic_annotation.vcf.gz 1edf4286e742fe488cff4985e236c78d 138749 CGCI-HTMCP-CC 6bcba66e-2c17-4134-afad-c8ee85d4e1b9 9e13cc51-8257-4eba-81b9-dd1e7a6297d2,e2d10187-1023-4cd8-a127-0f8842d9158e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 555c3483-06cc-47a2-b0f1-80f7f3dc2b1e 100c43210ceac066eaced7921468071a 147857 +52c0ff8a-da61-49e5-9ee3-ad92b518e41b 75786f93-15a9-4001-b008-132de127f6a5.rna_seq.star_gene_counts.tsv.gz f9f1ffcd6bf60fcc00be7c0c878e1bf2 409097 CGCI-HTMCP-CC ab45050e-2965-4d33-bff4-cd7a067ddd3d e8412071-23e1-41f7-b447-502f4f522ece Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 9ff47e64-ea31-492d-89e1-bacdd2f5bb68 603e8e1245b4749eb721083ef271f601 4227495 +0d78378b-a359-4304-b457-80fb115b89b3 44cbb787-2949-44fa-9cdd-6264b1dd5db8.rna_seq.transcriptome.gdc_realn.bam 5e33c9a50861a967ef605eaf40f8aae5 13993683736 CGCI-HTMCP-CC 59673b19-2e14-441f-9624-626ed0a3530b f8c00f0e-87a1-4e8b-88f4-ab62551d6160 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome ebb0ddf6-4dd4-4ef9-bbba-95f8d69d205c eb862797826fa993f9d2e1414ec4ab86 16103970013 +df15159b-52f8-46cd-8fcd-9700800cf10e 641209e9-4058-43e7-8180-40fde233d865.rna_seq.chimeric.gdc_realn.bam fb0ca7d6316246ff99a5e84331cb666a 115033868 CGCI-HTMCP-CC b9a4f274-5e12-4ae1-ac64-83a3c9be74c1 5d6c1336-20cb-4e80-8ed0-d0e8d894e7af Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 20518498-c599-4047-bcb1-38930e3012d7 ddf0b51e15e710d6e37a813faa6161a3 118757175 +d4b1e38f-196e-4b80-ae5d-e27505e1b704 2523d318-7912-4231-b56a-dfd4d5708f5c.rna_seq.star_splice_junctions.tsv.gz 0b0a8938239d6941a20da1892a6a4339 3290697 CGCI-HTMCP-CC 73590234-b978-4bac-8608-c1daeab7b47c da376a46-db0f-4ce8-88c4-d54cd84bb73f Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f2acca10-6ace-4c8b-8fa7-92e9256766ac 3a309b4af837b8971d18c9a0ad591d0e 3364808 +e1c26650-ab2a-4891-a62d-b31506dbb900 d033cea9-d38a-483d-8265-d38917919592.wgs.BRASS.raw_structural_variation.bedpe.gz 7a7c2c9273c9e191aebd24b4f5182167 36359 CGCI-HTMCP-CC 7064054a-aaae-400e-b1cb-e37b27233af0 ca3b6a34-8672-435f-8731-2226e9138901,e03f9446-21fc-4b3e-af0b-701ceb3f7d59 Somatic Structural Variation Structural Rearrangement WGS BRASS eb926f7f-4930-48a3-8e6a-062e1fba3746 7403b5d058aed13c53c9a66edb9cbaad 139778 +eb9f65e7-6a22-4a40-b558-ae043caef53c 939a2bde-ebb0-4bad-9bea-2e5864fa12a1.rna_seq.transcriptome.gdc_realn.bam 4c715d2ce69f4cfd94b0b55c36bcdc4b 19129367862 CGCI-HTMCP-CC f1b9e9d1-e08f-47be-9584-f968ca0e507c 9dd3452f-ff36-4b1f-ba2a-70710a0e25ad Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome e8547db7-4457-41b0-a3cb-3bd8133a45e5 66e71cd2b570fdd9684748063ee60601 22314885770 +6236e883-92cc-4c7f-835a-f9821c035e49 4d0c21ce-8793-49c3-86fc-fc92026bf04e.targeted_sequencing.MuSE.aliquot.maf.gz 02e453b5c03506bf44fb555490bc7434 65865 CGCI-HTMCP-CC 146bd9db-1645-4950-bd18-de30d0db2487 a64490ad-fc6a-445f-8a8b-cfe86e0f9274,b12b77a7-d93c-4580-9f57-12bd1d83d962 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation aa20a1c1-fe01-4aba-9802-93a90fa7af1e 73afed0a31f1666451acd14f0ac2774d 76235 +b883dddf-fa5c-4822-91b9-e58f1a168a5b 6e7c0b84-f4b0-425c-9195-fdc2e4a1f926.star_fusion.rna_fusion.bedpe b96c31b0392326fc59daab1f9df85113 4883 CGCI-HTMCP-CC 8c2a5be8-0ae1-4b68-9692-ec607ae873e6 b1299fb3-0cef-4bc4-a2bc-de2d588bc8c0 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 2fe39e85-0c78-447a-ab09-6d348a2e676b 3aab935329524a6241c1bfc404520e3c 1476 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Annotation cd93f707-b013-47b3-bf5d-f2e242a57f54 0f0af15ae04626893121a5132e7f53b9 42189 +16324fea-8e94-4ca3-882f-4f5631bee87f fc57adde-d668-4d6d-b8fc-b8e8a1438133.targeted_sequencing.SomaticSniper.aliquot.maf.gz a16e490f6ad13bb73c1e06e119d90c43 326987 CGCI-HTMCP-CC 31cdde3b-2dd9-4511-b701-99fb328755bf 8fc4c3d8-8453-49ca-8645-6e95dbbcc865,13f29630-11ef-4b79-921b-9ede908c4f7b Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation 38d1ea83-5569-497e-aa87-17a8a66b2983 5058471917d614db7bc69b03ef9a48c3 403583 +6388cc2f-a010-47b8-9c65-269948e8ffc5 37448201-7de0-4759-9dba-e45f46915c3b.rna_seq.chimeric.gdc_realn.bam e97028fc39f429044296b147206306a7 131713280 CGCI-HTMCP-CC b9a4f274-5e12-4ae1-ac64-83a3c9be74c1 9620afe3-bdef-4a70-9061-fa88e03e8283 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric a53571bf-ea47-46b9-b574-3bb80a1871a8 08a63896cfa46f1f9e2dc4645180276c 143388340 +e024a4a7-1d91-4fde-b2e2-312f130057b5 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RNA-Seq STAR - Counts a806723d-4344-4ba5-9b37-8d743a30ff20 f0d51b1fc8b3d4bf003e3c81c2c170f8 3664489 +32a635aa-2d41-470b-bfca-8cd695dd8186 3b8bfa02-6084-4084-9f6e-7ff4a502e14d.arriba.rna_fusion.bedpe 88992f6502f22da7f4f06fb726b75b01 5083 CGCI-HTMCP-CC 41e3aba7-c1ba-456a-bb6d-f50ac792df28 b0bba8fd-b44c-44dc-8259-2de03379daa8 Structural Variation Transcript Fusion RNA-Seq Arriba d47343ed-179f-4b4f-8c22-90b9369d6e32 6e205a933529f94a19f10afd22623248 4634 +ce0dc591-442a-4a82-b5b8-e7c7b66befe5 c2ad8dfa-b36b-4bf8-8db2-1a3beb9ec181.wgs.ASCAT.gene_level.copy_number_variation.tsv c63c9ac1eb0a58538e8a3d5ba8f251fe 3481232 CGCI-HTMCP-CC 8859b1ba-2d81-43e5-a845-4966ca6866da a61e5f9b-aa8f-4c50-b8b6-d0a03e94c29e,b31928fc-5b72-4043-8d08-0d5a9146fed3 Copy Number Variation Gene Level Copy Number WGS AscatNGS cbd2782b-9919-4075-9da9-ca36506c2233 68b01c2779c5c26e1419547954337203 3441305 +0dfd0016-0ea4-4f2d-8076-344cd32a972b c958a650-c714-46ac-b43d-9c6194fce619.rna_seq.transcriptome.gdc_realn.bam 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Mutation Targeted Sequencing VarScan2 Annotation a0713987-91de-4433-b393-291156b6d13d f1a79abed9429cae1fcb92be66a91c88 180915 +bb40c25e-fa8e-418c-af3f-3a95bebfea6b 7d5ce19e-9961-4b00-ae86-e08359fc1dfc.rna_seq.star_gene_counts.tsv.gz cd78735c6222d49995f65fcf19b509c0 420792 CGCI-HTMCP-CC 7064054a-aaae-400e-b1cb-e37b27233af0 fa47c6d3-4903-4961-b7b1-1e5759a672b2 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts fa772aea-0ca6-4f2e-a553-af187c120398 dd41db431b49d0d6574b5095f4426c5d 4244213 +4eeb393f-d1a6-4cab-9b1b-436cedd96cb0 e64d6089-073a-4d31-a2da-efb6c68abaab.rna_seq.transcriptome.gdc_realn.bam adfaf57d040dcbeb4a841d01a44ec982 10081157119 CGCI-HTMCP-CC a7814814-6a54-425f-a7cd-a58b3e510ea1 d56ecb9e-322d-407d-ac57-b6c2b7fc699a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 1be9985c-7486-4ade-9973-5f57343eba5b bef0c117822295c9be9eba0ac7a0e457 11719388466 +ef8afa09-b427-4a7a-a335-5ee01aef845e 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Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 1c739a8c-8713-4f8a-a565-3453e48a53c6 1169709b8baec3a6f4661f04e914e965 26892122111 +e6d3bb43-05ad-43f6-a097-0bcdf6726a0a b22b6c29-57ad-4497-ac67-bdc545d02afc.wgs.BRASS.raw_structural_variation.bedpe.gz ea058bb939e85edbfa5739ec32790b71 78219 CGCI-HTMCP-CC d86bf73c-b964-4fb6-8e49-c487ce2251a7 15252e17-5158-4b75-8222-2e44ba6c17e9,0baf0fe2-e569-4d68-ad4a-507c5d813c4c Somatic Structural Variation Structural Rearrangement WGS BRASS da8fa8a2-ee3b-4791-869a-fce918e803aa b2a1193e9591cf3c6424c81f353de860 261299 +0e9e443a-ee68-49e1-9a91-b28674a3889a 6c23c95e-66aa-4a67-9f5e-758ae2acba7f.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz bc4ce60481a1cae24a45cb21499612de 1478866 CGCI-HTMCP-CC 51fd7456-3e22-4bec-be49-4fb8c7899355 ca4b5f90-12c9-449d-9c16-3e06d845eb50,c23639cc-a9ea-4508-bea9-a1bc06260c94 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 6bd41b6e-9a39-4872-80ba-0b6071559e51 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276093 +9ccadae7-af30-4248-a517-c72e56fc735b 0c97fcef-5243-48a2-9989-b5f454329f92.rna_seq.genomic.gdc_realn.bam 4618a4d63efa8b05d8cf5a7667cfea79 12344819682 CGCI-HTMCP-CC e809c820-4623-4a88-8718-ea402b041a41 71da5f75-3a17-4929-b0ef-855551eb7dc7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 2d8287a4-78d2-4601-b284-5388253d940b 7c1b9c7eacae27a28a3a88c5a888cdef 13361652727 +e86c2400-e914-47ba-bfa1-b48459773cc7 6e4172c3-6f9e-4e37-ab7c-a63506a1f072.rna_seq.chimeric.gdc_realn.bam d2718a05bca26b8228099dc6026e60e5 63361654 CGCI-HTMCP-CC 20995c26-5612-4473-9b57-6307f30220e2 74d12ee6-70a6-4889-b34e-2919387e6b8a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 2521ad49-a449-4150-9d0b-07292b3525c8 4d0e8d0d34b604a710945111f57be736 67482845 +4277a5d9-1b90-45db-997f-b5c17483fadf 8fff3c9c-f285-4dcf-8373-22fb017f4c88.rna_seq.chimeric.gdc_realn.bam 3c2c57c856260606aaa7ef9936dc320b 68511136 CGCI-HTMCP-CC 29e5a5cc-cba2-424b-a9e5-52218f563a01 ba777d6f-206d-41b6-a1a9-c927bbd20e06 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric a35b81a6-f422-43f3-9120-61af95f7023f 19a2ec83cc2460adba3962a065142504 72817960 +f3bb0154-fda7-4d05-b930-76486e67f114 ee6235ab-f29f-4275-9c87-0fd0eb5bcfa8.targeted_sequencing.MuTect2.aliquot.maf.gz d60b22c0deaadb667f645a2e45d9bdcd 1677841 CGCI-HTMCP-CC 50103b4b-87eb-4d59-a85a-2bf998bafb16 4b0ee102-3043-458f-a5e7-99c69eb41b3f,25d29092-8b57-4eea-9a36-2940fc12f264 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 16a58910-93a0-4c6d-a6b5-0af6197d6c63 a02b25817581ceb68d16b4f877168d75 2046014 +4bfd9c9a-b0a8-486e-bc5f-c9183209c7a6 82fe53a1-773f-42f0-8ac5-919b51a696f5.wgs.ASCAT.gene_level.copy_number_variation.tsv 85c5ed5cf8825d6486f1949dfd6a5164 3481170 CGCI-HTMCP-CC 8882e9ba-8bbd-440b-afa2-b5fedaf87492 589ed935-06cd-4421-9f80-9acf1e7d19d1,df17f568-e5b4-4ff2-8a71-2c31c58e77d0 Copy Number Variation Gene Level Copy Number WGS AscatNGS ca84c8ce-29ac-4eef-b3b2-390f1d7f732a 2b27a3b3ebeafbfe03208c5c9af48a05 3441257 +42c1adef-4823-4d69-9ae5-1c3ce9ebbe4c 35b03427-7404-4203-8dd6-18123f43d543.wgs.BRASS.raw_structural_variation.bedpe.gz 7ee40c429c67368cc0a45939dc2f18f2 36582 CGCI-HTMCP-CC 536e2fa9-279b-495e-a0aa-e980a0139511 a4a1d96b-81b2-479a-bae3-6cdce0774adc,bf550633-02b1-4c2d-8254-76a343be2d35 Somatic Structural Variation Structural Rearrangement WGS BRASS 59a4c826-87d1-43ab-9b2e-3c6088275fd7 c9bcda0d917caf81773efd8e2f827ebb 121947 +6d16dbae-9004-4c2e-b58c-c93894dfc6b2 a1ac9db1-0ff4-4492-b7f0-2cae14452b1b.targeted_sequencing.MuSE.somatic_annotation.vcf.gz 42ad91fb741c7a077099603c4dfac435 89738 CGCI-HTMCP-CC 146bd9db-1645-4950-bd18-de30d0db2487 a64490ad-fc6a-445f-8a8b-cfe86e0f9274,b12b77a7-d93c-4580-9f57-12bd1d83d962 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 550e7a1b-8d74-4986-ab09-47c102687d41 f496246a88e1493706fc2461be9289e5 97103 +739b60d2-c78a-41a0-b44a-4a51db9f2b29 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e00b832f-8a56-44c2-8ba8-dbd64038b066 eff472f09d280530db3f9969f102092b 11117968236 +82da0e23-bf12-42b0-b041-37f2dd0c35d1 d8cef2f1-2a60-4fea-8298-fa7051c282c5.targeted_sequencing.MuSE.somatic_annotation.vcf.gz 3152726d14de13e5c4d5fb7d49270a82 72201 CGCI-HTMCP-CC 8db95173-61a3-47bb-ad43-6569aa4750a3 99fac76d-3908-403c-9b34-627efca1493e,9a02b0c7-bb4c-47f8-98fb-e6fa8460fde4 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 08d3c4d6-9ce4-48b3-b196-3c1057940ab7 1cd7671485b40bda343e1e479254fa5a 76919 +ced3e8f5-6865-40fb-bf9f-f840957772c5 13d9af3c-de81-4ec1-9ed3-851a317b6c6d.wgs.BRASS.raw_structural_variation.bedpe.gz fc9f81d6b61f21c9eb3233fc303e744d 19919 CGCI-HTMCP-CC 74b5fdf0-acb1-446e-a604-df12010a7384 431766bc-d2c0-4753-938d-9a3bb0cd9dfa,f3174ac8-a9fb-434e-891b-42ed6363092f Somatic Structural Variation Structural Rearrangement WGS BRASS 1029211b-c20d-4f9d-804d-039d1dc4e2be 70c909a528c84cc6e70cddf5df9c49b6 66729 +b30a7d57-155c-49c8-8a95-504ac39a4c41 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af1fa500-b3cf-49c9-b4ba-e3c35c736684 be7874df90510762eb8cfeb420c4cdc3 3527328 +85e7a7cb-b886-42d4-b33c-0153d8f51643 62a1a410-151d-46a3-b6cd-fa3b174d70db.targeted_sequencing.aliquot_ensemble_raw.maf.gz 105005a8238389bc52567dab4e79db5f 63881 CGCI-HTMCP-CC 65b8c7d7-5622-4fbf-b8bd-ab7a0de010f7 035a636f-811c-4acd-9c75-abed13ad7704,f6b2ac2f-1692-4b2d-be6f-4e79d41dd698 Simple Nucleotide Variation Aggregated Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking 3162780c-66d7-4289-88fe-dbe69d367c05 179da16a31471375f692d16717386555 83244 +c63db801-2f5e-4627-b57e-8a015b238c49 d06fbd3f-d75d-4e12-a58d-6ece3c50487d.wgs.BRASS.raw_structural_variation.bedpe.gz c801683dfefa739865f77001576b4943 28785 CGCI-HTMCP-CC 99aa0503-246a-4caa-b6f1-c3f998a69d77 81e935a4-0a62-4f8d-8348-6253964a16e4,2430533a-632e-4a4f-947f-505ddcc1da5d Somatic Structural Variation Structural Rearrangement WGS BRASS 8b700e9b-3907-4fcc-a372-42e3f010f51f b6df69266a243399b45cac1a0aa5e8f2 106321 +c59f1f18-3272-4596-8d35-385bc7adde4c 01835939-f0d0-4aca-8cd8-eb72c1b03f13.rna_seq.star_splice_junctions.tsv.gz 2906d087c8369f57335d26bd0b07c3b2 3337169 CGCI-HTMCP-CC e291f138-8517-4add-b647-d96647835168 4e84a933-2ac2-4d20-9234-58c6ce889f37 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 94f980a2-7eed-404c-9d1d-dfaae88da5a1 56baefa769c9d89f5eba65397ee1b2e5 3412786 +4834e399-886b-4fdb-a4f6-ca8847f83a10 0ab47dd5-7a5c-40fb-a06f-cb9b36390396.wgs.BRASS.raw_structural_variation.bedpe.gz d094c3f60439778b4e70a49552255ea1 247368 CGCI-HTMCP-CC e852a316-a7d5-4e77-a5ea-c1a8e454d3e5 56fccd47-34dd-4816-bdc3-08bda2b536ba,80a429a7-cb08-43f5-bfd4-224555472653 Somatic Structural Variation Structural Rearrangement WGS BRASS d45e13e1-73a3-428e-bfac-8cd65ccfad4b f954aff5ac580f0632e730cec91b0a4f 843895 +69e0251f-daf0-4dc7-8541-244f7721a485 79aa179d-a0b2-48a5-80bb-0f089d867b5c.rna_seq.star_splice_junctions.tsv.gz c49a3748d88cf30b7eb98f843846aeb1 3017293 CGCI-HTMCP-CC 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Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 45eb89ac-3ad7-4ad1-9972-652c7bb185dc 9e8cb756f6402e9e238d33062edf503c 4233975 +d7db7d32-87f0-4574-96f1-2ba6185f6b72 48c08890-4120-4596-9428-bb5df557a55d.rna_seq.chimeric.gdc_realn.bam ec04b06967e33a140588e505c905167a 86424953 CGCI-HTMCP-CC b0b16c19-23cd-4774-9337-cac369119913 95533581-1f5c-42e0-bf7e-3506fc427c58 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c5740f41-7205-4013-83a2-426c6a59e9e5 3859236617492d6c39fb3167b8186728 93058598 +4b000ef5-3399-4d5b-aaaa-3d358a3746f4 19a46c4b-d87b-4f41-afb2-852ceebb12d3.targeted_sequencing.MuTect2.aliquot.maf.gz 7d2dff45e5d167ad15cbeedb96c7c542 1049814 CGCI-HTMCP-CC ac48d962-d00e-4a37-8c97-11db4c3f5cd1 e5e1a30e-3236-45cb-9078-e78a47fde58f,53b25a7c-5b39-450f-887e-5da093e460b0 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 7f64fce1-4553-41da-9863-a0491f8175b5 da7c3405050ed1a0f2bd07bc49c66633 1268781 +4f4c47b9-1b65-4a51-86df-ebcde72276bc 8edd17b2-dfcf-4c34-8781-dc56370054b8.wgs.BRASS.raw_structural_variation.bedpe.gz 0cd00cd7b955fbd5acbeae3331b5957d 15530 CGCI-HTMCP-CC ba5e5f27-689b-49e4-a5f9-4007a8bcd2f0 cf57abf4-c16c-4820-8739-57a7d287f8dd,535c7358-7848-4a2c-ab8a-707bcf337f8c Somatic Structural Variation Structural Rearrangement WGS BRASS 011eb8a3-3af7-4864-acac-81bf342e1235 02642e1373ff9b1a46d661c39cd30e70 55962 +3a58e568-148e-470d-862f-b44eb3c8dc42 dd3efe14-9857-4ee5-8d0d-f6888e5f0b06.targeted_sequencing.SomaticSniper.aliquot.maf.gz 7fbb52e76a782abda9d5b759c18903c1 285382 CGCI-HTMCP-CC 9a9899c5-74db-4a62-86cb-06bdd72e5220 e81d46e7-cd8b-40a0-be81-2cd13c42f8c7,9bafdea9-e018-4871-bea4-45c00ca646b6 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation 41b519b6-4958-4509-b9ff-fe70a12fb31d 2bf7fe800f93d359c2c40a1e7bb1fba3 347169 +8f30f163-26e3-42d3-81d6-c0eb546204ae abba1c0c-f977-4661-8fe1-20e2296f12a8.arriba.rna_fusion.bedpe 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Reads RNA-Seq STAR 2-Pass Transcriptome a04bd2a1-5382-48ac-bc2f-c04b9309cdac 2e19de1554dc8dd51851cc045e7b94f3 31558892546 +bfed8d35-db0a-4b00-9a94-5f97eb77676d 5a1e5fcf-eb9a-4197-92ab-399c627c42a6.targeted_sequencing.MuTect2.aliquot.maf.gz 50ef92e8c12bd9f8cd923cf0a33bf93c 1348573 CGCI-HTMCP-CC 1d1173f1-b3ec-4ddd-99be-b5c839e9edac 27606694-fb01-4406-b527-cf08281ba3db,81cd3860-7627-41f3-8ba1-d4312cd006ba Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation f9fde284-d04a-4831-86e3-9b684070064d 72a2d49a8afbbe982e73aa2c8e86b8b2 1654374 +76f4bc41-f1ba-4511-b149-bffc12b4cde8 33827ea8-62c9-4086-92d7-573087f439d0.targeted_sequencing.VarScan2.aliquot.maf.gz d35496d0dbf5962e0df685359bf44dda 200500 CGCI-HTMCP-CC 20e986aa-0fff-4f8a-914c-8aad56568fd9 61945582-c06f-487a-be39-e5150f99799e,203454f0-62b1-4993-b9d5-557956361adb Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 2fe6ce9b-7e52-4aa5-840a-a9aa83c3d2b5 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Sequencing MuSE Annotation 5c9f31aa-f17f-40e9-9703-9ff5890350b2 41cba22fbd7900fbb346200e3f2eb8d1 197595 +ac01f5c8-1cc6-48bb-9a33-cf05f14de4bc 368b666c-9fab-451f-856f-b58eb6204922.rna_seq.star_splice_junctions.tsv.gz 1c5657e1912177cd1345c1df0f6eb0f0 3545860 CGCI-HTMCP-CC 1ffd0e35-68fd-4eaa-8b2b-a337fbdff5b9 d83e8f97-45e8-470a-bbb7-cf3abd8d6e52 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 5766848e-ed8e-431c-8796-c71563c72614 e8cb143429fcc1187a7dc07d5bbec8ab 3682436 +58f02165-081d-41b7-80c8-436c4ba6f749 f9039f42-5832-4b23-b6f8-371959b1c16a.targeted_sequencing.SomaticSniper.aliquot.maf.gz 8774cbeeccbe708d8221ba4f73d62f1b 491432 CGCI-HTMCP-CC 355b4e55-645c-4005-ad68-db0447da30d0 621d63a9-fdf8-4b78-b4e4-75ef5624798b,e2c0144d-105b-427b-9d53-86d9530dc852 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing SomaticSniper Annotation ced3fc67-4638-4f5c-8b14-2edaf7f06111 e43a8bc842d7105767718ec467a6d903 603131 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Variant Merging and Masking bfdac1b5-e431-4db8-92e3-b29c95819a6f 33c1ec3231351d52efa384e2fb946813 116095 +2b5e99e1-ef09-4199-a1db-5bc87f791c01 5f030490-7226-4a22-beba-d8d798ebf0be.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz 9fca30f5a68ef5b85dc445db10c24a67 1387510 CGCI-HTMCP-CC cd2dad25-8385-4d52-974f-9ff67d75529b 16593261-3c04-435f-8d01-281ef7de8fb7,d92593fc-19f0-4066-affc-ec9d9e23de4a Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation f4c8d227-95e3-4bfa-acda-410241785e38 a35ad500a14b66618e554bb949c0da45 1448823 +35d4ab40-e7ec-4a07-8f24-ef51a92c1591 ede895d2-0c3b-4d54-b6bf-6398cd34d8f5.targeted_sequencing.VarScan2.somatic_annotation.vcf.gz 31dc34cef7e7b79b6691f4f228c976b4 179395 CGCI-HTMCP-CC dcd1c0b2-e2d8-4537-9553-f3e69407ca82 201c0626-2787-45f8-af2b-3ab5e61840a8,2cde67ba-f110-4b96-8248-9f6bae93cab9 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 1bc930ac-3d52-49aa-9d51-e109a00f2eea 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e999c3a6-2c55-4d43-aab6-e2be188d61dc 2d55338d7c09a5366b499646061df38f 12324802232 +fae6cbed-4ef4-4948-b63f-1d05d3267cdb 5d1cd99c-87cc-4e6e-bd05-3d1faeedb299.targeted_sequencing.VarScan2.somatic_annotation.vcf.gz d7adbb3fd44a400576c938bf27ce95c2 132911 CGCI-HTMCP-CC 3f6743d8-1561-4cf5-aa1e-8f8bad057c01 b99ad566-089f-4741-9133-bc9b4dc70ed0,00e4f2fd-0bdd-4263-9c5a-8df43584cd64 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 339272a6-37a7-49f7-b347-4f4461c1a6eb ed3acb40ea2e91422765c9ed2da6add8 147075 +fd5ed3b5-e02c-431f-958e-747c7be6b834 bbdd62d1-caa0-4eba-b7cf-a5278efc5bd2.rna_seq.star_splice_junctions.tsv.gz 9ce2ba6a9cb21898c0073990caa5480a 3207219 CGCI-HTMCP-CC 1105dd98-0a06-4938-97c2-7e1582944e8d c9cd057a-22f2-466c-b23f-0bb9aa737831 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 0e35caaa-90fd-442a-8f19-793b5f697137 b158fb1879427f9ce9ee457fcb80f894 3284571 +ad37b2b1-7ccf-4bbd-a87e-c4b852e2559d 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+1f599137-74e9-4452-a7f6-9659bd9744c3 56a80f41-a68a-4f5c-86da-3c786be2c127.wgs.ASCAT.gene_level.copy_number_variation.tsv aab535e8c8cc02f31a5dbe3297a15082 3481463 CGCI-HTMCP-CC 8c2a5be8-0ae1-4b68-9692-ec607ae873e6 4bea9bdb-ae58-4298-b632-2a2a19060452,4668db60-2c12-4eee-99c3-9d7fadd8cbff Copy Number Variation Gene Level Copy Number WGS AscatNGS 590abb44-35e7-4253-a14b-907166c256cb 141f1626ec90b807dd6fbcc88d78cc40 3441530 +130549b6-c9e6-4d55-ade4-81cc8d5a8436 939a2bde-ebb0-4bad-9bea-2e5864fa12a1.rna_seq.star_splice_junctions.tsv.gz 579f797ac150fc750c796aed4c39ce87 3292647 CGCI-HTMCP-CC f1b9e9d1-e08f-47be-9584-f968ca0e507c 9dd3452f-ff36-4b1f-ba2a-70710a0e25ad Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts aef4a8d1-5fce-4e99-9172-81ac1ffd5554 474d992ceef9ba6a6f74e75a8e95f4be 3373128 +4e89f850-b76a-436b-bdf8-328d5ef5d735 633c972d-b256-4ec1-ae83-57db51703862.wgs.BRASS.raw_structural_variation.bedpe.gz c2b92f3f4a3596518df232a5e5f2fc96 32865 CGCI-HTMCP-CC 51078a10-f57f-4e55-8e1b-3995ab75c13f 11d9a317-d658-4efb-bea1-efc0595daa22,667cca03-1fca-4a82-a347-e23c073c2b54 Somatic Structural Variation Structural Rearrangement WGS BRASS bf0a1013-8142-40c2-a2bc-bf944c688091 d2d8ceea6b80fc32238de8b985d036d2 110408 +edc8f977-f58a-42f3-9fb2-291f2a8362c1 81689a0b-4b8b-4120-8512-efb59e794c22.arriba.rna_fusion.bedpe 31d23b589f818a2e3a4a96258975df82 6213 CGCI-HTMCP-CC 1ffd0e35-68fd-4eaa-8b2b-a337fbdff5b9 42213ae3-477d-4470-a773-ee9d03145f7b Structural Variation Transcript Fusion RNA-Seq Arriba b7825f9e-603c-4cc1-a0ef-5ea277db62cc 0fb42679d1ff7598e9e2267f136093ad 5199 +f48f8100-3b30-40a5-85e1-b26a4ae92066 c68b0047-e271-4049-85e7-28203f2880c4.targeted_sequencing.MuSE.aliquot.maf.gz 1cfe75792e72470379c3066a84f57773 151911 CGCI-HTMCP-CC 184e3bc7-f3b0-4753-8051-6e60bb1d9930 848ed137-a2c6-4410-8d63-591f9addee3e,752aec93-f0e8-42d6-8f49-6f217acf7336 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 10c560b9-aeff-4e0b-b067-ec04626d40eb 3f88b2320a4ac70a3f62dfabeece82a1 174577 +48bf7ed3-90c6-4676-92c7-e8e24d073eb4 5962d49c-bd2c-4971-b848-ede85f945de2.targeted_sequencing.MuSE.somatic_annotation.vcf.gz 56631db5a6403eaf9bbf81b7f7f3f35e 30066 CGCI-HTMCP-CC 9d05b62c-6948-4a15-8599-503436349fbc b0e1047b-9579-44b9-a0c0-8afb9070bfc8,96fadb57-9dff-4d23-a3d1-d2a82af46e37 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation f4a105fd-8316-4d3d-9dc2-13fdc475cb61 3e75134e7ac763997bafb724c32fb657 34752 +f00cc82c-3465-4421-9031-2ff6d60f8812 10675720-ce9b-4c25-bf36-ab2939179ff6.targeted_sequencing.MuTect2.aliquot.maf.gz 4cca18d82ca55f9dfc97c5d3137f80d7 1393543 CGCI-HTMCP-CC 1eb3e434-a4b6-4ca3-868e-ff6b6a4d1dab e4b292e3-8454-47c9-8c4d-407c6c335cb4,8bc770d9-2b7d-402b-a152-328db0f5a294 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 132a8519-a78d-4d0c-8126-b09c53ab0e0b 5ed2cb61928571a62f574dd37978a0f4 1724516 +28d9939d-bac5-4a1f-85b4-362d7cf0c53d cfd92d9c-f6ed-4a01-89a4-83acfa32b794.wgs.ASCAT.gene_level.copy_number_variation.tsv 819ed1032ec1f5e3ab430517fbe863ac 3481275 CGCI-HTMCP-CC 4b477751-4768-4d87-bd18-cd9a801acae3 8decb604-6fcf-4247-a57a-08e833d4f9b1,2c7cdfb5-07a9-403a-892e-1100dc1e595f Copy Number Variation Gene Level Copy Number WGS AscatNGS c4c66063-7024-4dee-a850-763b1b56e7ee f3c267f38d51e9d9218eeaf76596d3dd 3441389 +37940783-49f2-481b-85a5-df9795d5e73f 47c35ce9-8e56-4c1b-8696-a0b99415a0ae.rna_seq.genomic.gdc_realn.bam 8dfea4d497b2c72fd0da5de82f909b61 9849101791 CGCI-HTMCP-CC 74b5fdf0-acb1-446e-a604-df12010a7384 7cb9ed7f-7548-4fe3-bae2-5f21c58382e2 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 9936e1af-4368-48ca-891f-c909b5ffc94a 16eb625d2a044763b10049c6a144d7ab 10675002024 +cec3897a-9909-4bb2-bae1-7976682eabaf 6622e448-22eb-4e6d-9d43-188084d25a16.arriba.rna_fusion.bedpe 7bbca458bedb7620d92cf147a801d84b 4160 CGCI-HTMCP-CC 167beb25-035b-432e-8698-c9eb9e2b6b75 054e470f-ee2c-4d7b-ab17-c6be22558084 Structural Variation Transcript Fusion RNA-Seq Arriba 09596685-6bd7-4fc8-af0b-2d77d64196cd 0313472e7a302b551c206ce4e0e63e01 3246 +6c479aa9-302b-4459-ab80-cb7aa1410078 d5c55ae0-6f48-4ad1-818f-8750c3fdad7a.star_fusion.rna_fusion.bedpe 068961c234ffd184f54176f730d61136 1534 CGCI-HTMCP-CC e809c820-4623-4a88-8718-ea402b041a41 fc5b92d2-3780-43ff-a5c3-b859012724a1 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 2f06c226-21a8-47f7-8329-d5eb68ec389a 576ad7e835483671128507d98632c46b 1301 +6fef6460-ba06-4234-a4e3-87cccc2aed45 26d491e9-27e1-4a2e-adb9-109e33355ae5.rna_seq.chimeric.gdc_realn.bam 15632e29dcb134e4000ae9801fbd1100 85034822 CGCI-HTMCP-CC e8e932b2-a6b8-42e2-b395-354b2a9b2ef7 f7788c99-5257-4f1e-a194-d4a9d7653ce8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 33481501-846a-4e38-b91d-13fda2870300 e8a0e610e3367de07362b4e5e206e9e5 91619707 +52eb8979-ee2b-4d87-91c1-b9387880cb37 1ac018f7-7d1f-448f-a93d-a867f11fdef4.rna_seq.chimeric.gdc_realn.bam 3203d1f59246496d0157b7cbc3275174 74463156 CGCI-HTMCP-CC f7647795-26e3-4bf5-9818-a42dad9f9d6e 2f7db8f6-3a30-40a6-8730-903bd9c85d81 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 3b7a134b-3687-4272-ad6f-3d086e06f898 6f7a0aa37efe3d133031292a0dfffc1e 79514950 +c0baf822-712d-4788-8bac-e31522174d6e 9decb811-5e3e-4758-9ef9-ff4d4c443f30.targeted_sequencing.MuSE.aliquot.maf.gz 9b8eb968649c392916ae7e8c296bf52d 22395 CGCI-HTMCP-CC 3f6743d8-1561-4cf5-aa1e-8f8bad057c01 b99ad566-089f-4741-9133-bc9b4dc70ed0,00e4f2fd-0bdd-4263-9c5a-8df43584cd64 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 119f7eca-241a-4da3-863b-33c3c260676d bc8f8a7eb4a460f02b30c8b6a1231309 28683 +fd1a6f18-9aef-4ebb-b7af-b0cfde7eb887 8d685e5a-373f-4d15-ba8e-eaebda9bf7c7.targeted_sequencing.MuTect2.aliquot.maf.gz e560ec12b8215136dea09486133ff4e6 1512307 CGCI-HTMCP-CC 51fd7456-3e22-4bec-be49-4fb8c7899355 ca4b5f90-12c9-449d-9c16-3e06d845eb50,c23639cc-a9ea-4508-bea9-a1bc06260c94 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 1eeda553-dfa0-40de-a886-cf1feddbed56 6896384f05f188c106a685ea00a9ac28 1845188 +5bb3b801-3742-4ccb-aba2-fd9d2ae6d083 8b5c57e7-9c60-4e4b-8fcc-e62bfc1a0182.rna_seq.transcriptome.gdc_realn.bam da99e99539ee047e6ef4931d40674391 22165824184 CGCI-HTMCP-CC 10b32c37-0e82-47e8-8ff8-91a14971737f 1e85a77f-3169-4dfa-8bfd-25dd8ca42076 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 5ba2c16a-bcc3-4bbf-8f84-6635b789bb91 0e7b95bc117dc9f5dfc0730fbc2abe62 25783987081 +6afc4e8c-1430-4ddc-b6a5-2c365796d230 368b666c-9fab-451f-856f-b58eb6204922.rna_seq.chimeric.gdc_realn.bam 4c7d75df62ba291b516b65f35755dff0 256162259 CGCI-HTMCP-CC 1ffd0e35-68fd-4eaa-8b2b-a337fbdff5b9 d83e8f97-45e8-470a-bbb7-cf3abd8d6e52 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 89b7492d-0779-4d20-b183-a529a6d1ecc5 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Somatic Variant Merging and Masking 7cda9562-4a33-47c0-abd1-8db3c61c816b 5b34e86ef0ddd0e8682f1b2b0037ce4a 53156 +31ffc7b7-2ceb-49a8-8e1a-65b373231f1c 9d1e8a99-0dee-45fc-abac-72e5f26af8d1.wgs.BRASS.raw_structural_variation.bedpe.gz c3eb5fd4a206bf902963f32d60f20099 92130 CGCI-HTMCP-CC 4e0d653d-21f0-468d-91e6-bca55dcddfb0 115c46d6-3e94-49d1-aea0-37398f026edf,83ce052c-578f-44cd-9b13-020e28976465 Somatic Structural Variation Structural Rearrangement WGS BRASS 2448e546-f475-4f2a-9eb4-f5e65f20bb4a b6c7d7a69d60661dbeba5efd1947634f 310531 +8a65069e-e406-46d5-84f7-c8345da51a8e 82d5a141-ee42-40d3-838f-277fd0a659cd.rna_seq.transcriptome.gdc_realn.bam 58cb7afce486e7c0aafb2ac16706eae0 18972816323 CGCI-HTMCP-CC db2d6004-1b00-49a9-9f5b-58fdf56e22b7 701961fd-c741-44eb-9644-ff22a34262b4 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome beb103d0-b31f-4b51-9a3c-f442d703dc39 868a93a052c488bb82ff32455898a75f 21714257948 +62a18868-c52a-4ae4-a8e0-7ae87a7ce456 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Mutation Targeted Sequencing SomaticSniper Annotation 8b820fff-2ab8-4b02-92f4-8d5e64c2ad9a 912b31ddba28c75485842d0b08ab4d93 473127 +46f0a104-8ad7-4448-b909-7f20eea6c6c9 df12f7ff-4cc7-4ad6-a941-ecbe80e143e7.targeted_sequencing.MuSE.somatic_annotation.vcf.gz d94c6e8e6d6a86ac7f86fe65bdc8fe8f 142654 CGCI-HTMCP-CC b4f0df8a-ecc1-4274-b8dd-4984aa66cdf8 e4ab7314-c1ed-4ba7-90cc-7b7343d978df,ca5b4090-d807-44ae-aa28-37eb87d51c9b Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation da4c6f9c-0a22-4fca-aa40-292d9c2e77d7 0966d5e3df2231924d042d0e78fe5e2b 153718 +ecad08f7-62f5-4c0d-873e-a0403665695f ac35c43a-5da4-426b-9202-e516a9dfcb73.rna_seq.transcriptome.gdc_realn.bam 2aeb137bdd6b5e986e6a2b393ab8dd52 16667037865 CGCI-HTMCP-CC 57b2ae7b-30c3-466d-a25c-fdc49c51a2cc 0ec4d903-a1c0-43b5-8db2-180c1dd1c22d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 6de5edbe-7e08-4ef2-9f10-18f58d10bc27 1010961a81bf59705624688c1dfb24b5 17894472517 +17a16bb8-41f1-4043-8a87-915d9dccf341 372d6044-278d-43c9-9d40-f8c0ac821a06.rna_seq.star_splice_junctions.tsv.gz 6f03e89b224aceda845f0011ffe729d4 3166362 CGCI-HTMCP-CC 51078a10-f57f-4e55-8e1b-3995ab75c13f 63e7b0b8-df84-452e-bf43-ddafa0cc1aca Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 039e183c-a635-4414-ba44-6413394760a9 8e8a9f8b04e2e9399a78ecab341ad9ac 3252561 +9d97dd7b-057d-4830-bbb4-3c005e06f410 f8bffab8-0efe-4359-944c-fbd1079633e0.wgs.BRASS.raw_structural_variation.bedpe.gz 65d22577437dd81ce10e731ea2165310 31528 CGCI-HTMCP-CC 86c618bc-c163-4fbc-99e8-330ae2f9e262 0ee5173b-263b-49d3-b561-eb72fa5067fb,9944fdb6-0893-4903-9274-3de5975f6266 Somatic Structural Variation Structural Rearrangement WGS BRASS e61799e8-4c5b-480f-92af-11c39b48aaba 7d26e593928f102655fc1280f392eb24 105302 +8860f06e-9762-4bae-b623-6fc2f33a7453 0a90d919-4505-42c0-896f-286c364a4ad3.rna_seq.chimeric.gdc_realn.bam ad5fc1b487e5a2102d7fd4274adef50f 19505212 CGCI-HTMCP-CC 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+8238cb9a-5050-459b-add5-8df9e8ea1b3b ea86af46-aa63-4c33-9779-76b2ab3489db.targeted_sequencing.MuTect2.aliquot.maf.gz 2e655bd468ff90ac6a91f91b27569177 1388307 CGCI-HTMCP-CC cd2dad25-8385-4d52-974f-9ff67d75529b 16593261-3c04-435f-8d01-281ef7de8fb7,d92593fc-19f0-4066-affc-ec9d9e23de4a Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation f52e34cf-b92e-4e18-adcf-5cb819c8b25b 5beae5ae5a12701bdbdd2f5b6baa7870 1695856 +25543574-2c7a-4f79-bb00-50f7387f0ad8 bcb7f18a-925a-434d-9f29-8311680c39d6.targeted_sequencing.VarScan2.aliquot.maf.gz 277cd3c6945ef413dd7c93dd758e182e 172264 CGCI-HTMCP-CC 3d13888d-7f2a-45ca-b1ab-4c8b838db2d7 a3e3b3f1-f99d-4996-94db-4c55d5f26eee,c813557c-4c1f-4d57-bf98-094c563edd11 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 2c85a1f7-1496-47b6-9f06-d57d8dae1bb7 3d2f9d3af1f5ae5fd693f6cad7dcc8e6 205407 +390fb3d1-ed4a-413c-b377-f2a0f73e3222 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9a93578d-eb4c-4232-838a-8b54bedcedda 826772b265c9f0dd52b578d0af8b9c11 12492449991 +8292008c-3789-4d84-8a2f-ab4a7e565690 2523d318-7912-4231-b56a-dfd4d5708f5c.rna_seq.star_gene_counts.tsv.gz d025408c5286ae9b32eb66738b5d41f3 397091 CGCI-HTMCP-CC 73590234-b978-4bac-8608-c1daeab7b47c da376a46-db0f-4ce8-88c4-d54cd84bb73f Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 87b15ecc-aba6-4d81-9ae4-088bcb5edce9 9d9170dc8778b67d23d713a0a2f14c48 4218433 +b02f354a-e77f-4528-b21c-31a638614184 247dab44-cca7-4056-877e-10196825d4d9.targeted_sequencing.MuSE.aliquot.maf.gz 4f4a07c4ebc19752888dda6afdd87d83 26491 CGCI-HTMCP-CC ca0b76f4-7196-44a2-990d-7d71c976148e 0ef6e6ab-1156-45e7-a347-9ef96d81e5a6,d29fe0e7-4e6c-4809-a934-071df69e475a Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation d7812f62-4b70-41cb-9ea4-478ebf26fa71 1b437b94a43ba1d613a07bd3d1e9680d 32749 +0c9feb06-c243-40bf-894a-5ec684d07c75 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Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 67d0ed3a-b4b3-465e-81e6-1dc78d26d7dd a2132ba06599b2484bbae904c0755ccc 144000 +293096a0-c94e-430e-b5ab-404b8cb4dcaa e5bacc67-aab0-4964-a0de-e75916afa595.arriba.rna_fusion.bedpe c93ab3f7f9faa8a74d9e527369bb086b 2221 CGCI-HTMCP-CC 408b076a-0eee-4bc4-84eb-f5590c6f2a0f d1f9a1a5-4d9b-41e3-b90c-09dc4105e5ec Structural Variation Transcript Fusion RNA-Seq Arriba 1973b629-1667-489f-abb5-1d15d4f75ab1 1168b2bca450ee5b865cbcb0b30b55e3 1322 +be21d819-124e-408a-a560-88639a8e363a 58c4d4bb-a303-4637-becb-f4c924674aaa.rna_seq.genomic.gdc_realn.bam 626563ff309aa7c755f4f3274e9cc5ad 9322324950 CGCI-HTMCP-CC 81b9e35b-f290-419a-9286-e475065b09e4 e10f1c2d-76aa-4583-8af1-7adb30cc462f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome e72e5211-8938-4aa1-85a2-ab95b133ff24 ffb24e7dd0f5a772e9a2a0b679c548e8 10366638422 +b09fd6a3-2c5d-4405-8fd4-b656825cd338 5d3851fb-fb80-4320-8763-42095cc423d9.rna_seq.genomic.gdc_realn.bam 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RNA-Seq STAR 2-Pass Genome 096855d0-106d-4e5a-ac9a-575f3421cb1e 922c8e97331c145021f6611833f4e6aa 12675284681 +c11c8aa3-e215-45af-812d-93e28326b544 b2e748de-267c-4d59-9d3d-b1f0bc829234.targeted_sequencing.aliquot_ensemble_raw.maf.gz 37d48a3314cf3051cf9071bcf00b4e52 98082 CGCI-HTMCP-CC 47b1f82d-506a-4d5c-8e1f-da76360d6c25 ce4a23b3-a7d9-4100-ac2c-3dc7c6a75cad,df29bd57-afea-4e1f-8e95-8661fe4ce178 Simple Nucleotide Variation Aggregated Somatic Mutation Targeted Sequencing Aliquot Ensemble Somatic Variant Merging and Masking 819b5f9a-3f5b-4c6a-9688-4b1009a07e00 eac6b6a8b8738f79c691245b91b6f01e 125402 +87c6bf95-9903-46a5-ba5f-774f0d790836 1e74182d-aaba-4f65-8aff-821a8152f6a8.targeted_sequencing.VarScan2.somatic_annotation.vcf.gz 40fe3fe628b4b3143a18cad7647db9fc 208296 CGCI-HTMCP-CC aaf1ebba-853b-464b-befa-383dc2e6ffc0 6e7ecdbb-a60f-4011-9750-9978583c859a,fa66dd89-adc5-40a8-968b-965a44f1d8c5 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation 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Sequencing VarScan2 Annotation 7bf30ab3-66bb-42e2-8a12-9044277debd4 688c192eacc9edd988041923d284190b 216974 +c14a6333-7fd4-460a-954a-2e4aa02d3158 20c4b5c9-5091-468d-9eed-1204865e4ad8.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz 784950542853a5f53d2f322a456024d7 1311032 CGCI-HTMCP-CC cbc1f56f-0d31-450c-81d2-507680895c7e 356e8e02-c53e-4170-b3c4-a21b186e5f33,edab739a-fc29-4a3a-a7d0-80eb35761197 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 26a24fb7-77c7-4144-936f-807666d50bf8 9cf546031528a2ba12cc92d324e201a7 1370846 +4cf1280b-4fc7-450e-9b81-2972dc0c56ec 0a11f49f-b931-4ee2-ad30-6cd093986cda.targeted_sequencing.MuSE.aliquot.maf.gz 396aeffd5bb4baf58c4ead71fb8891fc 79456 CGCI-HTMCP-CC 20e986aa-0fff-4f8a-914c-8aad56568fd9 61945582-c06f-487a-be39-e5150f99799e,203454f0-62b1-4993-b9d5-557956361adb Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 520b6b70-9a80-4d61-a7f2-7be181f54322 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+07f7236a-4f98-4445-b83e-3751f95e821c 7debbe32-aad3-42ed-90d1-70f9b0ba1951.wgs.BRASS.raw_structural_variation.bedpe.gz 77b09b0e30f6ac0f47c1ce255f113005 32476 CGCI-HTMCP-CC 444e50c8-c876-4d98-94a6-0a3474e2964b 114635a0-cafc-42ef-8495-2eee50ec5611,d1e61f00-f58f-4d13-b358-dbe798a6ea13 Somatic Structural Variation Structural Rearrangement WGS BRASS 0213be1f-c6e1-4369-ab18-d0bdf27a3916 dd56bc5100662c5c69729be11e4cb0e8 109766 +8f41324c-e3b3-4365-aaa7-61c240c0b50a b24bd080-7302-4d52-8a73-73df3262d3c1.targeted_sequencing.Pindel.aliquot.maf.gz 3aad6d08064cebf9c00120af07bdafbc 41419 CGCI-HTMCP-CC 31cdde3b-2dd9-4511-b701-99fb328755bf 8fc4c3d8-8453-49ca-8645-6e95dbbcc865,13f29630-11ef-4b79-921b-9ede908c4f7b Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation dd5f9f45-af64-4f0d-8ec7-5f62b7d259a0 7f2f5233ad2e78ef11171134c6f0e32b 44270 +a281ff68-8c4c-4b5d-a730-d47b00d69128 39667c42-4082-4025-9994-04c3739b1809.targeted_sequencing.Pindel.aliquot.maf.gz 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+12b67fce-3f58-4b60-bd8a-345dd5ea200d 37e2428d-f76a-421b-9d14-d917cf5bb5a8.arriba.rna_fusion.bedpe 71ce70a5ad887f6b25a4d8956024a2c4 2434 CGCI-HTMCP-CC f02c03f9-530b-4952-b3a4-ac53469a7769 285a7e11-6af1-4121-849a-010bde697094 Structural Variation Transcript Fusion RNA-Seq Arriba 7af06ca3-04b6-466f-be5a-07a91b956e4b e55803d9e6b1dd7423bf7e268bfe78c1 2907 +723252ac-586b-43d6-870c-abcc4925cb93 707f65ec-4d81-4908-ad58-2fee29ee1fe2.star_fusion.rna_fusion.bedpe d4a62ba3f471d62bd02658ae3a33ce16 3041 CGCI-HTMCP-CC b9a4f274-5e12-4ae1-ac64-83a3c9be74c1 5d6c1336-20cb-4e80-8ed0-d0e8d894e7af Structural Variation Transcript Fusion RNA-Seq STAR-Fusion a43353a6-cbc2-4a80-8898-103537674441 fae4d2c9fb3817f8ba9d8a36b9ea1f82 1219 +6cb1fe02-247a-4b43-8663-a721d3407959 3da98b18-2893-46ec-b273-462e82539718.targeted_sequencing.SomaticSniper.somatic_annotation.vcf.gz a98ab3724a260d1c98705e66694e4e28 317086 CGCI-HTMCP-CC 924e18af-fce8-46fd-8d2a-f5858b415b4d 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Variation Structural Rearrangement WGS BRASS 4888b45e-3a1d-46e0-87e5-6661a56d10f8 548bb5da4f5cab1d0aeda96d09df9d17 73289 +9de7c51f-469d-4679-ad46-2b465d97a3af 8dd07151-b7a5-421e-97f2-f60161cdbb9c.star_fusion.rna_fusion.bedpe c47d31d16ac133b206fa7417af2afd79 2146 CGCI-HTMCP-CC e9230570-37a0-4bb6-bf21-170e830fe9dc af794645-48e8-4874-aee5-7fffcaf40730 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 4d50fa26-5c5a-409b-8d1c-d030b566ed37 bb03ce91df7b429617b5695c1070b908 854 +60e689c2-7ec4-44f7-9a64-219e8d86b71c f86068a1-2012-4af5-875c-37db9b146573.targeted_sequencing.MuTect2.aliquot.maf.gz 150f66c8695df35d0ddbab1a1d9e598d 1684372 CGCI-HTMCP-CC 5395b92c-0ba5-4ee3-a63e-f1621db8daee a01bb65f-6fdf-4fa5-882a-a32f684fb911,5d5d7831-d433-48b9-a75a-de73d8e2c700 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation f8587bb1-9b87-4840-948d-7b6b5df67cd3 e618f39e8eb83c221e797cdb5f7f3167 2068719 +2134d6dc-c4e9-40db-b3bd-752255f3a437 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Fusion RNA-Seq STAR-Fusion ddbd6a05-1e49-4773-938a-a007b6a86dd9 85ce13e6679ffedb5b9bdab1f63568b1 518 +a2a9902b-1b4e-4887-b63d-14cd6eca7837 b3270228-e138-4f70-b703-a587ec9c1b45.targeted_sequencing.MuSE.aliquot.maf.gz c43d4602202c3011f8185bf74ce98e36 26180 CGCI-HTMCP-CC 24d481bc-cab0-4fe9-a921-444341dfdf2b ecad8697-af20-41f0-b9e1-d967f41e98d4,9d2bc8b7-61ef-4edc-be78-f62752483b0e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 50519903-913b-4d09-8dbd-36f792654f1c 13e78b36d2395d201bac815bba1cc6b7 31028 +ae6009cb-17b8-47ff-bc70-32561fe3f3d6 153be570-2ac3-42b1-99b2-d7b0422caf23.targeted_sequencing.VarScan2.somatic_annotation.vcf.gz b627a02e66a787f6afa51342f34c2728 141232 CGCI-HTMCP-CC 8bc3d276-fa1c-4bbe-8af6-06eb87dde7e4 b0910e6d-6a6e-4b8a-b247-b7164801ce08,01096fb0-186e-4258-b529-ddfb6299668f Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing VarScan2 Annotation ec5e9598-8fd8-40cf-a326-5f63e2274027 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41d8194b-e8f3-4c2c-aa37-0214d234e6f9 ac2d29bb-a282-4a92-8d56-cb379d8ce814,67b5cce7-7d31-489b-8b73-e23a03277a9b Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing Pindel Annotation 99609d9b-981b-4f88-93c2-7b5b7516d425 f51c0d1dfe618eaaad18529ba0894705 31486 +6976209a-ad5f-4629-b744-6592b6afa78a 637221fe-abd3-4b58-a826-f6e6c731fd28.wgs.ASCAT.gene_level.copy_number_variation.tsv 79199ad7a9a0598bd2ab7b607f31946e 3481689 CGCI-HTMCP-CC 853ee313-7d90-4a57-8f98-5b633bd1273b 381323f4-3e70-4c9e-96a3-8bd4522dcbe4,19e53984-e423-4624-939d-736c7e77b6a1 Copy Number Variation Gene Level Copy Number WGS AscatNGS d12b7379-7e0f-48ad-807e-03f7c321b020 85602d2011f5a798e228736c65a95f39 3441776 +3c4a2348-4a5c-4fe8-902e-02d5888c5ae9 678583d7-c98c-4523-8bc5-bee45c129baa.targeted_sequencing.MuTect2.aliquot.maf.gz 2792de018daa42fa26965685ce035823 1563170 CGCI-HTMCP-CC ff95a7b3-ab96-4df1-95a5-6e50c3ff5e5f 29c7c45e-f59e-4452-9aef-7140822d8ae6,9092e087-3e6a-4c5b-a8d7-a7e38a16959e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 4783f08d-6841-44e2-9b9a-486129099cb2 3bcd9f6ff63049a513908dd0ef90b459 1919731 +153bc5ba-2973-4387-8781-6c59f214068f 693d8e0f-1b8d-4c2a-8f8b-e07593b9415c.targeted_sequencing.MuTect2.aliquot.maf.gz 25ccd6ed8c9ae313eb7fb35ee485b5d4 1334195 CGCI-HTMCP-CC 935ca1d3-2445-4f59-95a6-19f3311c1900 20c8d239-15ae-4119-a3f2-279d549a04c2,6f8c51d4-12a7-483e-8f0f-3cbd6f82d249 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 84c87cfe-8740-4e14-8f7c-71807089bf52 ed1e68353ff8668e4ae9e340672b1f8a 1638906 +cccd1f21-4a11-4e05-b6e9-e2f5d0dddb9d ccb44e97-6de9-4271-9c8c-a7beebd61034.rna_seq.star_splice_junctions.tsv.gz ba6f14deeb803a0f600a61fe0ae2bdb1 3277599 CGCI-HTMCP-CC a79ece94-3030-4e33-a9aa-623f430cd379 bde302cd-c010-46f6-aacc-2de55ab787d7 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 596f9050-3d40-4f06-a732-69ab7ba8b1ea 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Aligned Reads RNA-Seq STAR 2-Pass Chimeric 7fd85d1f-d376-441e-aa7f-3446452899fc 91ba2fd563ee7d7dfd87a0ecd417b7c4 111541261 +091a9067-e893-46b0-a30f-9bfaa1867b22 d9819313-a623-4404-bb84-eefe2d895f24.rna_seq.chimeric.gdc_realn.bam 05a2bf35babe865af238a5221984b39c 147864171 CGCI-HTMCP-CC 1ffd0e35-68fd-4eaa-8b2b-a337fbdff5b9 42213ae3-477d-4470-a773-ee9d03145f7b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric d3ec0bb2-b07d-4070-8072-b27e22799a71 a90a2d7cb26d949b912d684f5d750f17 158531353 +55bdb256-b796-496d-b3f9-93bce0968f90 9d6b9e36-c431-4fd2-a09f-14b4897884be.targeted_sequencing.MuTect2.somatic_annotation.vcf.gz 123d9479125d639cd88037ee38b3ad2f 1555218 CGCI-HTMCP-CC 6a644c98-5c38-47c8-8f89-7644d0570d03 e58562db-d0e2-4869-8d3b-9219ca1ceac7,8522de75-a1b9-4dfe-9942-da405875c0e9 Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuTect2 Annotation 08e85b9b-f9c6-4089-94f0-01616510202e 0c20e2085ea1795a4f93408979fa1245 1598563 +fff35a27-0c08-47b2-8c00-2a838eaec668 531e1703-0373-4bb6-b4a3-5d8ad4ba4e10.rna_seq.chimeric.gdc_realn.bam 9dc1aaeb9b5427abf12f4b5d503a0011 117736064 CGCI-HTMCP-CC 2d7281b3-0f09-400f-831e-091067ab5e8a f31ee891-a0da-4801-b69c-79a39895bb65 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 14232a0f-77fe-4693-af65-e526236c2bad 369ce637c93387a787d1571da034807e 126188109 +27e06967-4172-4465-b260-5c787b0bb348 a06c7c58-3601-4aa2-b56f-5b3e390e955f.rna_seq.chimeric.gdc_realn.bam bf17fac36cc5d3de97daff7662f1eebe 295898457 CGCI-HTMCP-CC c64d5576-df00-4772-a3d1-1f8863000750 20ca4986-5b24-4b7d-bc98-9cc7018187f9 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 41216084-9907-424c-9f23-5171ae51fbb3 a6f699ca47a9a760d6a9031148a7dc78 313434478 +f60ea13a-4a62-4def-9dd3-0ffa5978aa3e ae662223-4570-4782-856f-2c335e8cdc3a.wgs.BRASS.raw_structural_variation.bedpe.gz fb5674e415fc0a0a73af9cc079ac3479 28656 CGCI-HTMCP-CC 226914c5-e486-4041-9b0a-83ba8baae0e7 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265a65942807fb344f0c9ce02f49accc 3584994 +f1bf8fb0-749e-4e8f-b426-3293096975ca 5fcccfa3-9931-4369-a1ad-6e4ae5aaf796.star_fusion.rna_fusion.bedpe 2ad56eb57432d65b3f7650c39f9bd90a 5715 CGCI-HTMCP-CC 37941fa0-0167-4bfb-a609-29521ee854d8 002d856c-ed7a-4f2e-84b4-1bb83de4c115 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion b4449f6e-f4fd-4da8-9c66-fd2d2ea9cd69 99dbd6641c5148390e244c234ceedd83 962 +c95cf31c-f09b-4fe3-a4cf-8568ff2c0484 e5faf442-0813-43c1-8156-2d3d01da2cfb.rna_seq.star_splice_junctions.tsv.gz 16717fa9c3a70749d641155e7d243691 3659585 CGCI-HTMCP-CC 524db3de-46bd-4d47-b5bc-5d564fdc23e4 aa2b4236-e291-44eb-a2a8-677c842daf8c Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 0aa027e6-0909-4021-a5e5-5576aa85bf3c d6b6175c009b809b0b51a8110ef6dc2f 3791265 +7b68cd4f-1d39-49b3-b84f-6a5b4765bea3 ce960d7b-678c-4ae4-8ec6-bd0f1f7767d6.targeted_sequencing.SomaticSniper.somatic_annotation.vcf.gz 2db2c0da46638c969928e414e2b6e74c 472093 CGCI-HTMCP-CC 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Counts 745c0eeb-e4a5-4d8d-accb-e2a4ae473f7f 0f4d0739242517b881824058eca91fd5 3709738 +5aa1c795-9643-4675-b8d1-e72858989740 d6381f8b-f7e0-49c6-9b1b-481079e84410.wgs.ASCAT.gene_level.copy_number_variation.tsv 24c2bb3da2beaeeb528be63d549c1988 3481961 CGCI-HTMCP-CC 2c776c4f-fade-4035-8de6-e91c45c8347a 173e51b4-4a70-4685-8650-6f4a855204c4,3cdc0362-7f16-4787-913f-68e62668b888 Copy Number Variation Gene Level Copy Number WGS AscatNGS 6eda7604-8e2d-4bba-b87e-4ef09e8a62b4 544b2569696e31ecdc5e71500268b94f 3442019 +eb26a328-ee69-451b-9998-ee46952433a7 55168a49-872c-415c-b7b6-3c07bcac0b8d.rna_seq.transcriptome.gdc_realn.bam 1b7cab125d40b5482a2d66550a3f43cd 16265342673 CGCI-HTMCP-CC 167beb25-035b-432e-8698-c9eb9e2b6b75 422c9fce-a3f4-4ea0-92b7-eb8c5e53fdd9 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 8f7aec7d-64bb-4c56-8a2a-f90653d5f7fb 80eb00b5aba2ad873984a30421071c7d 18712367155 +ca272be1-97e1-4fc1-947e-15d956fcfbfb 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3a9ee309-5700-45ea-8b1d-0a1504e00119.wgs.ASCAT.gene_level.copy_number_variation.tsv 497bb479e496535e5f344bb310ace2be 3480845 CGCI-HTMCP-CC 9453db51-fff8-4a78-a29c-bb9151e9bd2a 10314658-6496-420c-8c03-75c66b4bdc07,dc5da41d-649c-4e2d-b40e-7c306454b524 Copy Number Variation Gene Level Copy Number WGS AscatNGS 08557db1-e226-4e90-854d-94939b4555ab c8d75bebb90bdb3a133d26cb79cffc00 3440923 +535ecef2-a5d4-4f2f-adc7-a061a389b430 17865ff8-74cc-44b5-80ba-c6d7653e2a6a.targeted_sequencing.MuSE.aliquot.maf.gz 4d7d95c47480cefb113917dbce262fb9 35797 CGCI-HTMCP-CC aaac33e8-d33e-4ae9-8683-c4031a1dd803 110243ae-e8e0-4b73-a3e4-b7e85c72f257,975e4cc3-f9ab-4dd9-b4a9-ab2769eb288e Simple Nucleotide Variation Annotated Somatic Mutation Targeted Sequencing MuSE Annotation 2186f3ac-5c80-403f-afe9-bf727ec4d2cd ca5750ac8f5a5a92e46814ac58d7c303 42418 +1fefc177-db59-434c-9279-727b0503663c 7c6ef49e-0306-4783-86ea-028d5773ec1b.star_fusion.rna_fusion.bedpe b3f41ffad7f1f37499b53f6036a1f09d 11146 CGCI-HTMCP-CC 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RNA-Seq STAR - Counts b5d0bb05-aa9a-41a7-9321-ca075b541547 7aa60cc252738bf89134646c43d5c53c 4213809 +f67a4888-4ef8-4170-a87d-3c1b9b475193 04272032-a753-4516-8e89-74badf56811f.rna_seq.star_gene_counts.tsv.gz 47806b221dd68be612a5be96e2fb4001 394993 CGCI-HTMCP-CC 889648ef-3225-4e95-a47c-82a9def072c4 6a4742ce-091c-4132-9546-89cffdb042e1 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 23dee61d-0eb9-4d37-85b6-e73ce4720acc 0b26354fcdfe6149ae1cb4a78fbb3ffb 4213526 +996bf230-8475-4186-8c5d-615e630defe6 9ad47d71-662a-463b-93a3-679455817707.arriba.rna_fusion.bedpe c1ce1c5cb6b05c860fe0723a5531d2d4 7933 CGCI-HTMCP-CC 90ab8522-2dcf-4afd-86dc-80562582cfb2 e1de00c5-7c03-4a3d-b9ac-0061ce0f3137 Structural Variation Transcript Fusion RNA-Seq Arriba c346255b-3283-475b-ba9c-df52ba0af082 795cdb985c3c9241ec2897cb053c59db 8467 +2ee46b30-07d7-4f6c-ac17-c02b46aadcb9 ac3191bb-bb64-4ef3-bcce-5880c7fbf0d8.targeted_sequencing.SomaticSniper.somatic_annotation.vcf.gz 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c20e929c-1652-4c6a-a79b-8c2542e7031b.wxs.aliquot_ensemble_raw.maf.gz 48fd5590687d44471fe965cf8ef88afe 208115 CPTAC-2 38bb0083-a307-4cc7-b15b-581f6c678482 5e09d6aa-82be-470c-80b8-898d2f11bd32,a7112cf6-6d9c-4870-a665-1ddd7964d070 Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 21e83951-b3d8-45c7-8915-9c9042b9e57e 24df6fce96b7c59dd0f5616faa68ce97 254188 +9aaa9623-0575-45b9-bf89-abda1d241369 4e21b502-1c64-4df5-a6cb-5351fc8fbc7f.rna_seq.star_splice_junctions.tsv.gz bff08397bff088fb36aad1c2e1c2ebb7 2588363 CPTAC-2 efa6ad77-da3d-4763-9662-47a5ab3b695e 388703cc-503c-4797-949e-5a6b8fdaaeac Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 30552f73-d681-409a-b7e9-ecd7db53017f 1375e18bc4add38196032e6fa663448b 2606716 +576d1597-24c1-4ff0-8e53-1ff6861438d3 48176c9f-d3dd-4be2-9208-3cf88bb22e4c.wxs.MuSE.somatic_annotation.vcf.gz 3d5d75849fff705875221f95a32187ea 1589763 CPTAC-2 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and Masking 5b228e9c-3776-4586-8c8e-c645c5a29595 e96dafc6d0cf9d9e3f0e4a7d780dfc92 33021 +dfc0a727-8567-4285-95a0-ad03f93c838c e8200dca-d41f-4dbd-91d4-e0baca8c4750.wxs.SomaticSniper.aliquot.maf.gz 4bd64c98a29658eb5f93ec20da01bedd 1559932 CPTAC-2 99d74447-9236-438c-8543-e876b4daa8bf a4f62168-a47e-4bba-a0b8-9de471adcc32,29af2bb9-3061-4096-bd25-eaff51ca6bb4 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 75a8a32a-d3a0-464f-944a-95d61b4ba2a8 91bdb441b30455b7486fe1fce41b7eb2 1962749 +9aba17b2-019f-42be-8f13-727fc572ffe2 b51e6ebd-7d26-4a49-8db4-fd14c5680041.rna_seq.star_splice_junctions.tsv.gz ab07bfd9eca87de0b78f76c8c2a4e9f9 2906379 CPTAC-2 a0bfef36-6e6f-4d61-8f50-b379aa96c8ac c2245f6b-8446-42cd-af95-4e09714f3140 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts c1c95bfe-2f4f-4411-8660-762673886ed7 fe69bbf3a808cd1a4d5c8e59865cd0d8 2928040 +d106cac4-a63c-4f9e-bfa4-3d68ccea9c14 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SomaticSniper Annotation 8a4ecaf8-6738-4e70-9761-ccf92f6ca1bc 02cd90a5061529608f83bdee8fa4b77f 8416269 +2d6c5ad2-2a9a-48da-828a-d28d624966d9 72103f1b-ffbf-4e5b-bec7-2535b7ef6cf5.wxs.SomaticSniper.somatic_annotation.vcf.gz 84d92a997298736a71244ce6677894a3 4130282 CPTAC-2 d7e3db60-1891-494b-81cb-5412cab99f5d bf311b7d-0375-4334-962a-3eec9faa434a,b3168d1a-424e-45c0-904f-15a380c54414 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 961214c9-4750-4c48-80fa-51ea95c289cc 1929b501dc3ea373d3ced018b648e482 4324776 +6f25e4c4-49e6-4712-a1d2-b9b286696085 7fec7cbb-55af-4a0e-909d-731dd500dc66.wxs.MuTect2.aliquot.maf.gz fbea8694ac3ac10e30fb31508a5929c8 5068009 CPTAC-2 d10080e2-8d8e-40bf-95f5-23f03cd22d85 266f6db8-0b0f-422f-9ef7-4122bfc6a7dc,7e832437-f081-4f15-b6e8-5303fc4bdfdb Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation aabefecf-d763-41a7-92aa-aa107f752fa4 df5f3aa264004053ad24d118f5218da0 7142992 +461ba734-3778-46b7-b862-85591c989c27 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+ddca40f7-f393-4676-8611-4646c3029f77 89b3ad60-1585-4f4f-9b33-903774d151cc.rna_seq.chimeric.gdc_realn.bam 9e8b2c01cc634627bc6656b008befc62 20583797 CPTAC-2 faf8cebd-72ad-4da2-b55e-73cddd8dafff 427f36d5-0947-4b3e-86c7-84e8f365f244 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c918169d-8af7-477a-94d9-d30bcf04dc82 f927ac8102ba940b1d0b7b0b85fb891d 20582443 +060ffb5d-b1c5-437b-8ed5-79213ee77aa0 19277a10-3b4f-406c-bc2d-921387dc248f.wxs.SomaticSniper.aliquot.maf.gz bb0e8b8817642629d3d6db99ec50a5fa 2060954 CPTAC-2 f8400a0c-624e-48fa-8a18-e4fe04eebcac 64d50ff9-4693-4517-a325-78aff46a60bd,6e70e15c-fec4-4fbd-9f89-b36d8d556a9f Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 6620393a-f64c-49ca-bf65-d2697939c03f e05caf53891598c35f74db98efac907f 2652798 +9b30e4c8-1a33-42b9-b9a6-1e365115c665 0037cb37-2e19-4638-b8f6-61d23cf9ca46.wxs.MuTect2.aliquot.maf.gz 29880705115d496f67d2e05ec5108728 4469574 CPTAC-2 4b355c1d-4202-4291-93ec-7882e702bd20 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Annotation 282f0161-3665-4e91-ab07-a60a38aa9b6b 2dea320f65ea19e0251c47f3dec59275 6795808 +1c3429f2-4ffa-4b94-b663-825de3db1bb5 22d8150d-5733-45c6-8192-940f409c0657.wxs.SomaticSniper.aliquot.maf.gz 31958b6b1aef2802f76154635e564a79 10213743 CPTAC-2 ee726188-31d4-4e9b-bc6e-7545a0ea19ee 2fd699d2-77ae-4275-be4d-25f377d62f04,4c43f3b9-b900-4d8a-8165-c7c9fa5b853a Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 615ec36c-5600-4106-837e-417160698485 dd472f8aad75d1c6126990da7de671c3 13421325 +1c0a4a4e-200e-450e-bf20-41c929478d6c 7f5011b2-1238-4c33-9e64-e985a8cce979.rna_seq.star_splice_junctions.tsv.gz 97329d2fb28b69f52f84238c8d1eda98 2631602 CPTAC-2 0f8ac7bc-6b51-477c-bc1b-cab58b4ce769 95551d77-69e9-46fa-ae68-1475e5cf76e6 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts ba003630-9353-4b91-b591-c3f0fb9ade35 8479a8fe3013ff943df6fa5929dee4c5 2651155 +e27db860-0a5b-4bca-9030-fba0e25db351 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Annotation 7d7b4f59-6230-45a3-9842-ab58a909aed1 68e017196d3fe523754a78e5cb059c35 36782 +923dd6e8-84dc-47f4-9a01-4f32768a2b37 f1c04309-ec0f-44d2-aead-450192152feb.wxs.VarScan2.aliquot.maf.gz 574184c59c8d91d5e40ed097b6924499 346581 CPTAC-3 e0c39f59-1297-4c0a-9478-77e5c7207230 a695af96-c8ba-42aa-8290-8f485ccdbdb2,d1fe7625-edef-4de3-8580-c5a1e327b334 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 60c75f4d-7762-4006-a69f-24999ee728d0 e98f9c51c35e0c4ab69d0bfa49f4afb3 399016 +738f1e39-c79c-4205-bd40-5de9e4313c14 1ec11928-92e4-4a28-aed6-bd6a2acf47bb.wgs.BRASS.raw_structural_variation.bedpe.gz 9c882b1e608ee2699e1ebb33b55c4a46 25856 CPTAC-3 bae31638-f9ed-4298-89b6-e74422d84ffc eb7cddfe-2246-4542-8756-06d1b3f872d6,0ea1f237-cdc6-4d6c-a4a1-15caadce1ebc Somatic Structural Variation Structural Rearrangement WGS BRASS dd298897-b377-43d5-8e1b-381d26c0aa8c 080a27c934a1ed9bf36971bea912ff71 92502 +f8beb31c-d740-41a6-bda9-cbeb2c8fd369 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Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 7a5f45a9-cfa1-4e11-aae4-bada5ac55036 6e5690795ff424264402ab9d2661b62b 229 +80990319-002d-4ebe-8eb1-2e17c0d925be 356f1387-4cc8-4ed2-be89-b5a1ddfe3d85.wxs.VarScan2.aliquot.maf.gz 457e13dfb7e6dddc93c8856fb5dc382b 847546 CPTAC-3 0215c1e2-70aa-495b-a1f1-25bd989a9f12 c93de7f1-762b-4ca7-a1e4-8f959c170856,5eab67d6-ad15-43ea-b7d4-265945e3ba09 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 4e5349bb-7c08-45a5-986f-542d67460363 95e25fe26ca736c35710c488247c0867 965187 +dd4829c3-d5fd-400c-a170-7cf8aac4c887 4eb5be8a-421e-4f46-bbdb-c8688f140f48.wgs.BRASS.raw_structural_variation.bedpe.gz 25c88d058e099029e3bd677fab4d88a7 2953 CPTAC-3 fcb92ce9-d9f4-423b-bf9e-02bcd5be561e f1a6dc62-ade8-4e25-bcf7-752ecbc4f7dc,953ddd78-016b-47f4-8708-054f23481a45 Somatic Structural Variation Structural Rearrangement WGS BRASS 597fa67c-8c22-4791-8121-587a132b79b9 c0923c68f379a02703b6550b68a389b6 9313 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STAR - Counts 5c239f41-376e-4134-a70c-86b4b20bfe7a b6014d76128766ab63993739725d1b19 3321628 +a19ca027-6cc3-445c-b898-2ea12bce5850 2923f52c-a269-4e4b-ba3c-1b005eee2066.rna_seq.star_splice_junctions.tsv.gz 264621466c98e1d4806b269baf078925 3504810 CPTAC-3 2d75c2fc-90f0-4169-92ff-4ac8e4817ac7 2c396bc8-3c21-45a5-b729-c99ed50f5d16 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 2ba4dd70-8ef5-4e12-b5ce-b5e289c166f1 4014c7132e20f938e356ea607afe6068 3548584 +8aede48d-161a-44ea-9721-5975277b4858 3c397b09-01e7-4784-9ddf-595757d2bd70.star_fusion.rna_fusion.bedpe 4ee97e8dbe5268df184e49b22a27749e 446 CPTAC-3 2d1ffb7e-8600-4d11-8a65-f27558c3ecfb 0deabf08-73e3-4453-afc3-b960957b8663 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 0eda1ffa-bf65-411f-9f7a-b117c3a95539 6e5690795ff424264402ab9d2661b62b 229 +bec76689-5bf0-48e1-94bd-eab0a9253d9a c371f315-894d-455f-88a5-fa250f52b9b7.rna_seq.chimeric.gdc_realn.bam 670712ccbea2cc42299b272087341dd7 24907164 CPTAC-3 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+c3ac6e71-7c55-4a56-b9b5-476f0e2f5423 0aa70021-b4be-4b23-818a-d91a96d1d431.wxs.SomaticSniper.somatic_annotation.vcf.gz 7bb4c11e81b9bdaeb89f1ba987ce8ee6 567407 CPTAC-3 2d1ffb7e-8600-4d11-8a65-f27558c3ecfb e08784ff-f64c-44a3-8b35-3facd041574a,9c909c63-b574-4d09-ba11-1cacb92a327a Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 233ae082-a5e1-4cba-b4f3-a9c5c5f6b94e 7d6576750d24519abbff31b39b1f6173 580629 +8851ea70-4aa0-4e50-b19e-32e7e9b0251f 593fad12-e48c-41ef-a6d5-fbaf552dbf9d.wxs.MuTect2.aliquot.maf.gz 60d8a1a1b2e0918a281301504fd4be50 6009409 CPTAC-3 9ed4e3ba-0dcd-4436-bf21-14d68087fac4 4114196f-7a4a-4bca-acf8-d8829c639934,e2aaffe0-cd97-4b93-8e61-de5f324f901c Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 89821751-20d2-4d13-9e41-19e45fea1e84 b157f6dde1cec6c324f68958492bd9b4 7121745 +5c08084a-af59-4d7a-ae37-ad6c0f5000f3 d58031b2-4dd2-49b9-a934-266fe70bc072.wxs.MuSE.aliquot.maf.gz 2f5ae12ef3937e716851f20c9e7287f9 433630 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Mutation WXS Pindel Annotation 5cfc30bb-389b-4264-898c-f23134800eda 744955e40961df3b52225ff4d9f3d308 62803 +4dc1f3c2-4c6a-47c6-9d8b-e58ef79931b4 0ae7ac24-644d-421c-98ba-e7c9c6bacae6.wxs.Pindel.aliquot.maf.gz 77e83b5a91bc8d3747f0ac0920be5a10 286320 CPTAC-3 a4dcabb2-3414-41e7-87f2-a7926ed625d8 ad027991-1119-4114-bd08-47af71ae25e5,b52dfbb4-71a1-40b5-8f03-56122d428afd Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 52f19d96-093e-4936-844b-51b31571f664 e72cc21dbea196d7276807046887cda1 290291 +21c9829d-f4c5-4790-8e36-f19c48c31e4a 0e947ea6-f7ec-4bb9-a383-d8324cb2db75.rna_seq.transcriptome.gdc_realn.bam 03e85c75de35c4f9221d2b21ef610af6 7161468562 CPTAC-3 188f9191-e4e2-4b00-80cf-c1e1424580a7 033d8cf1-959b-47d5-a607-129079a8c173 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 94ea282d-3955-44fb-8a6f-84e2f1a1d955 21a82141d63f0565ebb37502d3a90ec6 8109919530 +b7a05465-e9fb-48a9-9ced-1f1290e610f9 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87772cb8-23bc-4a2a-8f66-afe32d5f6973 535df1e543e13873ceb3a996e1175dd3 3145082 +2efb42e5-650f-498a-bf26-86592e8d4c62 b01de4f3-fb90-4d0d-86f2-e17a4d4701d5.rna_seq.genomic.gdc_realn.bam c3605a7772206ee97814a5e1c3824ed7 8676440569 CPTAC-3 d6d6c315-2b2e-4347-9c38-8784d15192fb 06e62279-fa76-438b-8552-0235b572e75c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 024d645f-eae8-42d9-bf85-a824a4580af5 a67bd361fc1e33439765a819308b8e85 8678217569 +729a546d-7861-4e13-9f86-2740b3fbefb2 1bd804ba-4171-4e29-8c87-af7006263ef0.wxs.Pindel.aliquot.maf.gz 30724f36f9e3c972aa0ee7149e4844a7 393687 CPTAC-3 c6ae1472-04d0-45cd-aa7c-f56e3d7aa8a3 f6acdb05-d0ca-4749-8b17-c1af50669ffd,e1873371-dfb8-4bcf-9862-d45b58e04f41 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 1e5285b8-86a8-4cc1-9b8a-eb1dce08eb8d 435010bab284f6d9c45ad3639c4dc15d 420683 +4f744878-fc18-4c46-be8c-462f604abba4 03b03dac-f65b-4233-9d29-36cb1546941d.rna_seq.star_gene_counts.tsv.gz 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7f382304-45dc-4ca1-ab0d-2d9aed727f25 40d2c75c4a587814f0d163d947b4dac4 27128 +da218080-61de-4c8f-bc7b-7ca3e66dc556 cfaa12e7-9001-4a34-bb98-b1b68072de84.arriba.rna_fusion.bedpe 95d5651ed07fe7bc53db49c8abb71aca 3721 CPTAC-3 5a88652c-cc2f-44c8-9e61-e89d46222743 06467550-def2-403d-9aa3-7a3a34f02dde Structural Variation Transcript Fusion RNA-Seq Arriba 2401884b-a50f-4f77-b042-6b834a9fad1f d283793934e544f96de73512eb2c5ea7 4347 +1d4fa423-ab87-4e3b-8a2c-3357afb52a77 0d45e64a-0224-46ca-9247-e4f33e9f8196.rna_seq.chimeric.gdc_realn.bam 8d2bd017f8f6e713ba79d237060851f6 48056122 CPTAC-3 239a5fbb-0145-46f6-8ec3-2a96a04011dd 40e674e5-a06b-46f9-b604-e0145b171886 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 933c58a8-0119-4ba4-bdd6-f6970257bd77 11fc2b40a4e1f375fa0531e9cefd2702 48040467 +45c29beb-98b2-4b9b-b813-e35921c20787 df2ec34f-2f3f-454b-b18d-cf18f31018dc.wxs.VarScan2.aliquot.maf.gz 33991bb9743faca158687e55f6edbee7 344874 CPTAC-3 32647966-e243-4cbf-ad05-6041071853c4 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df093852-8356-431b-a37f-a93a62550588.rna_seq.genomic.gdc_realn.bam 4e5b88d9e81d5484094a287ffac6a669 7534629897 CPTAC-3 e8bc3792-92f6-4924-8047-9f805afb4b04 511b4c0c-e2e6-4a9f-aa8e-917474e1751a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 36152147-0f80-4d95-bd45-e80d318fba6f ec1e065f6c087585a6f4941a7bc2537e 7535796418 +dcae1d59-2e78-4e82-8f35-c7e517b217c5 41533d32-2e2d-4bb2-b231-17fc9ba14246.wgs.BRASS.raw_structural_variation.bedpe.gz 39afb4beb3b395d9799d33122295eb2a 10477 CPTAC-3 d73b1616-f3eb-462e-bf33-345872fee45b 2df2a777-76f3-43fd-8d48-ac283e79c4eb,61f5b700-0bb6-424d-aab5-ecf10d369c99 Somatic Structural Variation Structural Rearrangement WGS BRASS 80189783-61c3-4c29-84ee-458097820186 db6b3ecace416bf9cf6e64ef5a7f0e79 36146 +83a9c868-3e87-4e0c-b66e-a4796db1a721 d725a687-e340-41db-94ba-4aa6c2a31816.seurat.analysis.tsv 116cbc19dd09e5c5bbef869205dfc610 2670930 CPTAC-3 94f90e9a-ecfe-4682-8d19-2ac88b31a5b9 f5d551ce-6a3a-444c-b22f-eccdd33f8a79 Transcriptome Profiling Single Cell Analysis scRNA-Seq Seurat - 10x Chromium 9a5b6362-971e-41eb-8f59-9c7b637b07b7 2b2f7f630e3698e3899b3498dfa12513 1987917 +63cdfc7c-43ee-4a30-a677-0ca7a03c71d0 599fb7d8-f23f-47a2-890f-477f3f5aaeca.wgs.BRASS.raw_structural_variation.bedpe.gz 9249916c22ee6c8b991bebe56afdffb8 1293 CPTAC-3 17e6c62f-cc0c-4e13-a80c-f9bd6c2cfb0d 3bd9e2f6-ff3d-4e3a-86f3-9f790485e5b3,9e37fe3b-588b-4e4b-87fb-8e427490226e Somatic Structural Variation Structural Rearrangement WGS BRASS 28c5e11a-b728-4b49-875e-d75adee067c3 59555ac9190927a0e95cdd4f90b59dac 3137 +3db2bfc3-fa85-4406-961b-a27115eda2de d22e995a-39ca-49b0-b94e-dbccf28492b3.rna_seq.star_gene_counts.tsv.gz 8df3ea78fb62efa4107aa204d42175fd 421765 CPTAC-3 d53bb16c-51b6-4ed0-a1aa-bc88a7894e2c 7aa350e8-d42c-4405-97a5-1161f136e421 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 31affed4-63cc-4fb0-b1ed-ded40a31efed c1165b67b807cbad70f56e5bae24af51 4235299 +fa65872d-e520-450c-aafb-31cf0ec662aa 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Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 82c310bb-80f3-4c8c-a971-6fa3f4080946 c4c64ce6cfca9ed349e83eca7b059259 4225140 +7cbdc0b6-9c4e-4b5d-860a-ac8ebc701d53 f035424d-0e87-4122-8618-71aa311ac939.rna_seq.transcriptome.gdc_realn.bam 55b7bb4ba29bf4821608545722646908 10873173718 CPTAC-3 c6c75c5d-b3c9-4918-8dc2-02849933cd3c 51bf5d7e-a9fd-45e0-b91a-52a34369eddb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 00257c9f-1dd6-4f80-86d0-a8351a9c2c21 32a8476d7067747fb7e3d3810bf9daaf 12459867482 +988782fb-f1b6-47a4-ac34-1ead8b4062f5 0e2d0dbe-0859-4978-938b-6b851516c6d9.wgs.BRASS.raw_structural_variation.bedpe.gz fe1587188591e2330e1b632e8d20bd54 1371 CPTAC-3 a7b5ecd7-d16b-4c41-87d7-881c3d53d185 db1a7dad-b66d-4d4f-811c-4692fdf6fbcd,faa668ee-186c-4f91-9d95-174aa0475acc Somatic Structural Variation Structural Rearrangement WGS BRASS ba1656b1-d2b4-4730-a04d-2be04f6a88cc c77ae08c92abcbfc4f9dd2228cfd5066 3490 +9700bf77-2931-4fa7-bf24-65872b8e614a 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RNA-Seq STAR 2-Pass Genome 15ef39e3-de1d-4dce-ad0c-142edcefe860 e4a42d7134580bd447f684198510654c 8917268248 +112ecd89-6263-4333-9278-150ffeb62fa3 2413011e-1809-4c61-ac4e-e1e68c8e306f.wxs.VarScan2.aliquot.maf.gz b8bb0e57f1512e7d7325e6f3741bfcf5 201247 CPTAC-3 4ee85d91-504d-4389-ab5a-e37b2cebdbcf deec3429-33f4-4946-a550-66acc74ee372,d6e45feb-9d72-474c-9d5b-a0b8d6c4dc8c Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 058f7554-cd43-44a0-bc1b-522ab328d7ea cbd822c97a63e768d16c35a154bef33c 249221 +edff96b4-c47a-447e-a2a4-5f829dcbc92a 800740b8-5f63-4376-885f-33f46bb8b123.wxs.MuTect2.aliquot.maf.gz 265d0b820a6cfb22fa381cdce6e47966 4239834 CPTAC-3 bc8f9b37-2f05-4508-830f-9356b99313dd 609e24b7-042b-4088-a100-b55d5f0beaf5,d678d221-9dbd-4e9f-8f94-9aaef5f7092f Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 97fdeeef-b72c-4108-9262-80627299f09a 07da076ac7d93ca482502b68b61b0d5f 5099729 +415d0f34-f2a8-4857-8124-46b7a9a87610 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7d7e7aad-fb40-455f-a4b1-67d2398c7ec8.rna_seq.star_splice_junctions.tsv.gz 78c4b16191c0b418f1e639a0d8fa896b 3020867 CPTAC-3 e80deff0-6d18-4093-8d6d-ee481e4d06ac c1b9066d-3de9-4ff1-b2ee-0e570749b670 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts a5f0e853-149c-43c7-94ab-9c12972af71a 973d579024b2ac50039bd17d50a837e7 3053550 +ad42dc3c-bdf7-4de5-b2a7-ecceb973a0e0 c9774b4d-f0df-4b62-a522-91d15c2cc2e3.star_fusion.rna_fusion.bedpe e7ed56b8383680a716984c9be5606efe 878 CPTAC-3 fab863a1-138e-4caf-8489-409d05511795 74e8e745-6ea8-45ba-8a17-f5399b2d947d Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 54906499-4f79-43f5-bf45-91447a518963 325d1086adbc8e3a062e09466023512e 874 +e7ee10df-28d0-4011-ad89-4cac3c3534c0 0d23d839-4880-47cc-952b-a38967844d07.rna_seq.star_splice_junctions.tsv.gz 4558e7b1d43998b1a18f2e42da8bc999 3202137 CPTAC-3 6e5e5bb1-b76d-42f6-bd2b-c2f325d79122 d624b662-0c8b-46ab-9648-30e6e55c6bfb Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 19082c20-b8bc-4c38-9775-9373d54c2c31 a15c4d2b7cc1504f60821561ae0d5687 3238252 +346792b1-3ac1-4fa6-b27d-6e411afb4a13 67f80984-e135-4218-a539-1ce4e0b5aee4.wxs.VarScan2.somatic_annotation.vcf.gz 7f2cf8a0913b4c22877dc1c36604dec9 422537 CPTAC-3 1570eaf1-9b92-4506-9df0-9ae9a704a731 c1eb9e6d-669b-4d1c-83c6-9710f4c80717,baf79fe8-b7ef-4e69-98c2-81b4430452bd Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 83ba48f4-1a85-4f9f-b925-04e50335ef17 a26620f19fff0e3cf3f7d7a74c61f0f6 430878 +fbfd66a0-0646-4b82-9d88-3863bd4bb149 9f0a72a1-aaaa-4147-aadd-ee7fbab14513.rna_seq.transcriptome.gdc_realn.bam c3c683f42845655cc2fe0519c29c062e 15171266760 CPTAC-3 eac6ceca-d905-4a4d-ae89-ea533370aea8 e14fe70b-915e-44c0-9868-58a2e5e8e3ae Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 4fce4632-2117-45da-99c9-38f6143e4a82 1948f5110cc28c29b22069167ee286a1 16933378838 +eb8ecfaf-0124-40a0-90f6-88def05aabd6 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Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 53b04a6e-f7e0-424f-b0b6-801cb13c8967 7a20c9d6caba0fb950bf8cf798fb6e74 256625 +e58f2097-cd7f-4724-b797-2e1d5de39eb4 30c71a54-4a45-4921-b0a1-6c92fe1228af.arriba.rna_fusion.bedpe 54d576e1f03cc2eecbc5ca064346d10e 4720 CPTAC-3 538424a8-0d56-4d6f-806a-19a0630c9d83 b4f80031-9316-4c99-a31f-74effdca81ea Structural Variation Transcript Fusion RNA-Seq Arriba af580cac-8732-4be0-9011-892838970284 92f9b7e3a831b2d962d949cf37c8bc44 5412 +1110cc04-3f08-4b94-86cc-7ffc762d7aae 43eee82b-08d8-4559-be6e-1fe478f05e09.rna_seq.transcriptome.gdc_realn.bam 0d21bc698597628263f0d767319a1c36 8250664650 CPTAC-3 c6ae1472-04d0-45cd-aa7c-f56e3d7aa8a3 cf3e0964-5b63-4083-88be-e6b111e7a110 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 49c53332-89a7-4e08-8b11-a501ef82e231 d73d0454c12e66cabd005a950b30252a 9391726705 +c87ef43b-67c2-49b3-9ce2-01f8d5291e8c 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Annotated Somatic Mutation WXS Pindel Annotation 841d0a1f-9bb8-4edb-81fb-c7e0a7ec7e02 4e558c23bea86f6d2be8a6807091f2e3 123029 +5e7a8e72-71d9-478e-8a1e-c921260df851 1a8378f1-f7be-4230-a532-14cca3b5b718.star_fusion.rna_fusion.bedpe eecd2c471be2397dc28e005c57154793 3590 CPTAC-3 a270e912-5fda-4f46-8450-a77dc78ce53f e9bbd3e8-30df-47d1-9745-d97f68416d1d Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 2739f9dd-8e99-4c98-b67a-1761e8f05a11 fbf93e09ce6ad38134a5206bc480e70a 4356 +3b22205d-c98c-43aa-8ade-98df877b3524 b52d05d1-ab17-4a43-9236-aeb0f1e51b95.wxs.Pindel.aliquot.maf.gz 81d9dd2f956fdc6fefd1e69f58e47516 389226 CPTAC-3 2c779d6c-f661-4621-9e3b-f9705da342a1 f5ae7b0e-9213-4424-a10e-7f1383d33b5b,ef72c57f-f998-4e9a-a563-b5969a93bcd8 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation c714c6c1-7eee-4e57-93bd-a0d0eb4486bf 11b4eb8ad3c396888cac734d7dbc5a67 415283 +417f68eb-49ad-4562-ad79-df127bd63d6c 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VarScan2 Annotation 9f007947-7d31-4e8f-84b5-214530e9fea0 206104e0e0b4015e1c38ab35f45e78e8 622762 +fc12dea2-2468-42e5-8724-37b1cd803ab2 9e35efef-3c47-464f-8969-fa8b62cdf73b.wxs.VarScan2.somatic_annotation.vcf.gz 8160d4ca964f891046c5c4ecc43c313b 188438 CPTAC-3 08b1070c-1562-4465-9c0c-670274d70f74 02ccbf9d-f299-4000-8151-97a51c2a74f7,1cdbcb35-ccb2-4bbe-9adb-1ac5f24201c2 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 8b55ca1b-70dd-4973-9c5c-0efbe2047fa5 d9f80b0f44cccac2f2a84ade4ae5dd8b 196326 +75f5877a-5a52-4af9-b459-675016ac613f f03968bc-08e4-4db6-bb07-ff15353a5187.star_fusion.rna_fusion.bedpe 7df6d3ba2d69fd0b41e3f5a4d5161fe4 1492 CPTAC-3 208b87e8-f96f-419c-a659-c94a1b4c12b7 df939cc8-fa38-4599-89b6-4c7e1ec9ccd5 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion a151b161-6775-425f-9d7c-c0ad89bf0906 6e5690795ff424264402ab9d2661b62b 229 +648431ad-cc4a-4adc-b8c4-6e53698848cf e8d67e93-4c8b-4444-a375-9c6aa48794e4.rna_seq.star_gene_counts.tsv.gz 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Somatic Mutation WXS VarScan2 Annotation 1e4af38b-c299-4bf9-9788-216256c0b257 f2eea5ac2f19b4db32823e9628c93f94 260702 +d8efd94e-be76-4a5d-b98b-682369d07793 ceff574d-0348-40f1-8894-1c3a7e2781e9.wxs.MuSE.aliquot.maf.gz 9779d251070980c59e65e91904b5abad 261728 CPTAC-3 2f9e1f15-769a-43e3-a68d-dde243883422 68b4ea45-a8af-4d72-b8b0-35a102d2f517,0bf76841-56c0-4d7b-9ac8-404463eebb19 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 7a1edb62-b408-4dc8-955b-58da3b692061 018417ca639b5890254cf4e6252ac7f8 325314 +12534fcc-b4c0-45e4-89e0-ca96367fa8f8 a2a8fa38-fb2b-4346-9561-10a18f736cfa.rna_seq.genomic.gdc_realn.bam 9d5d4f34da293f756b6193aee3f98a79 8147526632 CPTAC-3 f59ce549-5cea-4f2f-8662-aa9060247f80 19e8e372-fb4f-499d-8c88-a2b31e972d8c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a065290c-1d8e-43da-9bec-5cb79b080272 76bc5f3863158e3572d0b7d8266d5701 8148333610 +f478ee46-a09e-42cd-a849-5a5c7b559fcb dad6028c-fec7-4b2c-bdb5-17eecf94899d.wxs.Pindel.aliquot.maf.gz 8fc43d5f6ea15ff45d74c09fd4d0fbce 365588 CPTAC-3 1a53c571-af1d-4c79-be44-180cc79e0d4f 474dfea4-f2db-44d5-9f00-98c85f07f20b,d4205a17-5d31-4f86-9a43-4631df1263ab Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation ecf89fc1-42f2-4953-8824-de341fa2fe6c ffe06788de5f05d7e2299f3bf611bf42 385989 +10218cdf-5d09-47ab-8e10-c1ff4b058d0c 0a4e31f9-f262-4440-8f79-76bd1bac123d.wgs.ASCAT.gene_level.copy_number_variation.tsv ea3e62cbb3570b1eea22581dc33fb481 3482803 CPTAC-3 6116ed25-e657-440d-a5b5-24dcd90b0bb5 9e8bf09d-6c3c-41f6-ada0-0255af5e514e,55b09b6d-156e-41c5-89a3-dcf2239933d7 Copy Number Variation Gene Level Copy Number WGS AscatNGS 0d1ff882-3b74-40ca-9e5d-877ba4b63aa8 a0e0bbaa8e980602ee8f58a099db50aa 3442799 +06a87a55-a70c-40c0-9459-04f89bc4cf0e e987a0dd-873d-40a9-8dc0-2606dc0f82f0.wxs.Pindel.somatic_annotation.vcf.gz 1fc2d2dd8fae37a0598813a4ef870f7c 209457 CPTAC-3 2573f4bb-998a-4424-b241-3ada0627a92e f9340864-be80-405e-a3a3-e0b123762976,bd504223-27b1-4c70-af68-6985b7e5d23b Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 7ea2a5b8-f49b-4af6-8293-8b5b9ec02b36 d931153ee1fb7e1ba437726b773f0ec1 216878 +7980098e-2f60-4e45-9dd5-fbbf4c69e98e eefa86f4-691e-4df9-b4f0-ed3f33fa7e76.rna_seq.star_splice_junctions.tsv.gz 8cee46d002182c8b053c63351ba216b1 3238521 CPTAC-3 a5fa1602-d98b-4953-b549-902ec3f4cdcb e30bdd9b-fb52-4072-9d55-f7ec866497c6 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 2f2f71c9-9670-4f5f-97e0-fe5497b17ef8 5c71004dd8eb1c84df4fd7257fab6e26 3276710 +24f616a0-d767-4f67-8c68-2544fd4cff65 3a1edde6-066d-4432-902a-90d79380a9d1.wgs.BRASS.raw_structural_variation.bedpe.gz 9b39d5d72bdf1376bb41357dda02449e 2914 CPTAC-3 a0d5a7b2-4c7f-4d19-bda1-1357d3b1d72b 366e021b-ebe0-4ef7-8a77-80f237dc316d,631f5939-bd6d-4a1e-8476-e2fee9ebe6c4 Somatic Structural Variation Structural Rearrangement WGS BRASS 843f4dc9-3582-45da-86d3-0a63b2a544a4 1048016480cd48598cba437508ee35d6 8800 +2457e1b3-44ef-4496-b11e-1db112768d18 00b3da4e-6836-46e7-a975-67146d2b462b.wxs.Pindel.aliquot.maf.gz b3444da5403a4d3c116771ea76c936b9 79233 CPTAC-3 6145ec3f-90c8-4fc9-8f49-9f2d699da65a d14970f8-64a4-4186-bec7-ccdf5e2a0505,d2d9af9d-8785-44b7-b3f2-3359c624c777 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 36810ff6-70b6-46b3-a909-8bbd19ab5e14 2755c24dfe5e4365aad470076e42b884 74879 +8b524d99-7ee7-49b7-af37-1e58205190ad 8930739b-4381-48ee-aaad-1229ea213c09.rna_seq.star_gene_counts.tsv.gz dab6eaacc468bda2587f16740760f854 396739 CPTAC-3 5bbdafef-dde1-45c5-a2c9-433ce7b246a8 b38c77d7-c235-44cf-925b-b86e74077cae Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1259de18-8eb4-4fb1-a47d-a68cafde9bbf 4e051367359802fc5372d7941a395962 4207243 +847ae8fd-528b-4381-af8e-1567c1d40172 22bc0607-8f27-427b-a589-a90c8c0c0db0.rna_seq.transcriptome.gdc_realn.bam 47da81a5cb1db527d98ebc86f81f4fbe 10437969500 CPTAC-3 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+38456067-35a0-4783-b9f8-fe31ceb14dfe 90bf7eb8-6a85-43b1-95cd-0aba37a1efea.arriba.rna_fusion.bedpe 6866f86b3dfef3ded5cfd635f22cc04e 1162 CPTAC-3 98bed41e-96ac-434b-90ad-cc7223998602 9bee9add-07d8-4c2e-87d5-71e39edbaac4 Structural Variation Transcript Fusion RNA-Seq Arriba f297eb29-db85-4082-945f-2d1a5a6601d6 784c17a8f00f713b9e9707643f5411d8 1304 +652472dd-5ceb-46ab-8013-17356d707196 40b5c7d4-4029-44a0-b865-60a59c557316.wxs.Pindel.aliquot.maf.gz 2e59a3c6294c833ed4a36d146f7d1033 51995 CPTAC-3 da4a0eed-b755-49b8-96ae-31d3d396862c 4f7cf63d-7f7d-4b92-9616-d101839c5d0f,d199a60b-540c-4728-969b-c420123d9b5a Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 9d0127b5-0a69-4c48-9908-b070b6e3af35 3b8c46d5eec28220bfeb73f6e7d88838 58342 +68ba4fc4-b153-4e9e-9973-86764c8ba27f 0754eac5-cd08-4967-acc0-b63fc8d90996.wxs.MuTect2.somatic_annotation.vcf.gz 53e72c42fe02f102c78053ef17d748da 3770764 CPTAC-3 746b10e2-5824-45e5-b85d-fdecffef3e1a 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3039aaf97525673bb6151a7aabf65d4a 65465 +65aa0a2c-c5bf-4914-9c3d-2be19a2949f6 507507ba-58ec-4f6f-a30b-6b161b577e3e.wgs.BRASS.raw_structural_variation.bedpe.gz b04544e283e33727016aa61afea4005a 1564 CPTAC-3 5cb7b327-5f17-44a8-aed3-989a1a99e780 449ffb6b-9f0e-4cc3-8632-720344de67ca,59f6a8d8-d2ee-44ae-8a9d-473c5812c66a Somatic Structural Variation Structural Rearrangement WGS BRASS 12b1e468-c2ea-46a5-b247-8d7a956b3ed4 3513adf34d3ada6ca5abbe48302e3ec4 3966 +bc8e13d3-bb12-4650-9ef1-eef93430a395 54b51b1e-3880-400f-85f2-0864606b32fc.rna_seq.star_gene_counts.tsv.gz 8a343a0920729bee4a7c7f8b8b216db0 415669 CPTAC-3 5023cef4-3bba-44ef-ae7e-8ac30bd19412 ef929482-6acb-45aa-8561-4988dbea1fe8 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 52c18535-6854-4f89-a5b7-ad766cebfb29 9c0fff3a39571520ce334ab2ee4a20bb 4228056 +8a986d45-dcc7-49b3-8eb1-04bee53e045a f6456338-e69d-42aa-98dc-de4dd21f297f.wxs.SomaticSniper.somatic_annotation.vcf.gz 9b32426e33aa2703f7e803fcf09bdbc5 883593 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+0c85475b-0eb2-4f2b-8150-7f4e0603bbf0 ab7058b9-2f1c-4c18-8e16-dd293c9d5737.wgs.ASCAT.gene_level.copy_number_variation.tsv 8ca7ad5cb0aa784230d359a3392e2c77 3482794 CPTAC-3 2171413a-4d2c-4ad5-b539-f231a3d0a2de 4a02531c-43ca-4755-b48a-f9732230695f,0ccfe2e3-b8d8-46f7-9330-adeb25be08e0 Copy Number Variation Gene Level Copy Number WGS AscatNGS 6f7331e0-f408-4c19-88fa-4e7757cabf9b c5a003bbabb884c9865e7db94476d61d 3442786 +cd43e061-c9a1-4851-9bb9-501b45b75eee b2551f87-ee00-4abd-a032-299319e3f957.wxs.MuTect2.aliquot.maf.gz 297e7a301c47ed1988cae61b952707d4 1866118 CPTAC-3 12126fde-c904-4b3b-81b4-083824d7a0d4 66637cfa-407a-4d07-abc6-5ed16df0ddc4,caf681d2-5806-4cfe-994c-6466c2908f86 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation afadb866-83e0-462b-add8-e2eae05b77b6 45e031333166d31bdf182f4bd61224ce 2243166 +22a520d5-c3ba-4b27-a780-d9d0640fc35b 9fef51d6-f9e5-4af2-8430-5190bb0c518c.wxs.SomaticSniper.aliquot.maf.gz 0a9b5b645bbed2f881142bf333ddcc8a 246180 CPTAC-3 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Annotation 58fc40cb-c443-4f50-a2a9-eea99e1699ab 798fb8b257293534865b82b3d4abfc22 10301383 +985440e1-5535-4355-a957-295cd34c107a 140686fc-9fbb-4de5-b634-0e0f924efcb4.rna_seq.genomic.gdc_realn.bam 071a3e11ea639275969c2f14f3973486 7339988273 CPTAC-3 d4fba188-8ca4-44c0-a9e2-67bcff29b99a 86192daa-a2a0-41dd-8bd7-33a7eacb1226 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 5726a48e-03a1-4fc0-afbe-d124a490ff02 3aa0c77e5b79ec266d97b24b5c17e88b 7341117208 +398222c1-9dc8-4a9e-8bf4-cadb1e8e737f a250c2b4-6f11-4f58-b09c-d50708099e12.wxs.aliquot_ensemble_raw.maf.gz 93aa9b0f24b25b88bb7d60100c3fb34b 432996 CPTAC-3 4a40e29b-aaa0-4de4-949e-e4a5d6295bed 50495b8a-9bca-4f88-af7a-0d1181f82755,2fe897e3-129e-4d02-a5b7-a4f3e64192e7 Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking ea6fa23e-3a61-4962-8090-ace68bf48bfc 0312de111327bad2497ce66a99dc158e 499341 +86a4ef39-1a6b-41e7-a9f0-21eb7330b774 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Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 25ca7a40-5520-445a-9e8b-2244c43b8716 8826307728cc40083c82bf7058747916 7076 +2ea5968e-b6f9-4919-b98a-b76ff531cb10 b72b0000-29c2-40af-b4ca-c070bb0423b7.wxs.VarScan2.aliquot.maf.gz e1244810d9c681b97d0f70402fa32f0c 168622 CPTAC-3 5bbdafef-dde1-45c5-a2c9-433ce7b246a8 c426ad7d-ed66-442f-a1ce-2695de7d1033,e1401e98-8f02-415f-a1bf-b72c4bbcac6d Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 557190f4-7cfd-4108-98f7-5f8015843c88 7e29454f9cf2c73b3330b7e5ad82558b 203105 +746c5f9c-e500-4ecd-ac85-eaa51cd4b91d 2e7b1121-670c-4941-9108-59b3145be8d5.wxs.MuSE.somatic_annotation.vcf.gz 619684839740b556cb954b5aea021f13 548673 CPTAC-3 423ab312-1482-428f-9b52-fc3169706e03 a22d7330-2df5-4cad-9469-65de69d006eb,0ccc9616-79cc-4ff5-b33b-2eac15b4078d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation bfc57392-9a07-42ff-8331-e67696a6ca1e 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Variation Transcript Fusion RNA-Seq Arriba b748d6d1-f8de-42a7-a509-3953c567bb95 95bbeb0ba3356dbdb713c4f88179a3af 1308 +ae6031f2-7a61-4b96-9e47-5935a7312e74 bf8d3e6d-5223-471a-88c4-068d5c6e0085.rna_seq.chimeric.gdc_realn.bam 6f3885a61d4f669905fbf887c623f139 189483974 CPTAC-3 892a5650-f576-4977-9c03-257f45320f09 e304251e-650c-4d99-8265-64fd84f5e9e1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 25ca107e-ed68-45e0-9b5b-2fd357bc8b6a 4f462e7a071fd497734fbcdc12839cc4 189455309 +9dc87248-e834-4d88-b66f-caccc84c9d6d 782a06bb-f123-49b4-9f1c-9615c5a971c2.rna_seq.genomic.gdc_realn.bam 5e1846a80fc5d92938426f2960362bdc 8980458301 CPTAC-3 de35e7e4-1e13-4180-a7d8-66cc967a9ae0 5230eeca-6296-48c9-a9ad-a968a819f68b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 3ad7f3d0-4636-41d9-81e3-905da16d708a 62ca06a452c4823ede74a63ae688f587 8981648015 +59528c0c-4450-4592-9fe8-8c6c6f945bfb ce475b84-30d7-4332-9555-f85223002bb1.wgs.BRASS.raw_structural_variation.bedpe.gz 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Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 07b796cc-0bfa-43d6-9634-ee9b3c0450c2 297b124d6fcbfa00361595b70ea2830e 3399288 +c48e8be9-a0bb-4436-bbea-0928cc7732bd d1ed67dd-227e-4957-8bc1-718b4c173e27.rna_seq.star_gene_counts.tsv.gz 3bf2681f471ae49d788ef72f1bb94928 418726 CPTAC-3 5657645b-d839-4035-8e69-2a9c78232cdf 53e567f4-aaba-4360-8829-4f5229503467 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 8edd2ab4-377e-4d07-879b-b6bac439a29d 439092935341ecb6fc272365fb8f714a 4233640 +8191e511-95e0-47ac-954d-7b1ce7b18038 d15805ac-4d8e-4e38-8a2e-bbc91da597b5.rna_seq.chimeric.gdc_realn.bam b298e84b8157922abce74faef263fdbc 98534337 CPTAC-3 e51dd5ca-c12d-4608-9e6e-73b658b106d6 67396db5-4715-4c08-8a9b-bf861f8f8c33 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 59078078-03d5-487c-a641-7723441e3937 1af1f6fed6fe94a3658a971b739571f8 98515029 +56aaa828-9bd3-4e4a-93ce-d36e39141f5a e56ace06-78a2-4fe9-8845-c0125cdd04ab.seurat.analysis.tsv 8975b3fb7ca51c88a63a87fd937a912b 5502294 CPTAC-3 3a58efbf-2708-4f13-87ab-253d7d67ef52 560c535f-a736-4372-b1da-61081686824b Transcriptome Profiling Single Cell Analysis scRNA-Seq Seurat - 10x Chromium 8a8e07a5-1b8b-4a27-9492-672ce4bad381 4e092867dc2032e32b39d1501179e850 4725223 +10a55339-9770-4a84-8d64-faa7568af622 0ab6ac0c-4fdc-4c48-9336-075e65861f1a.wxs.MuSE.aliquot.maf.gz 696daad0398f8cac4070377d906e8023 165883 CPTAC-3 cfa1bc06-94a6-44ce-b52a-1e4aa3db48be 1464b756-be16-4e28-a7c9-29d5bc6172e9,c8513c30-14af-4dac-89e8-03450586d9f6 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation d1e683c0-f3f7-427d-94cd-d61b07248802 13af25008d3ec4dc85d82cf09bf2f064 194023 +fb56212a-0809-4481-90bf-60642da574d4 544152e6-3ec5-49ef-ba16-5a95b5b5836f.rna_seq.chimeric.gdc_realn.bam 84b7b28e49dbb3e26a55c3cb0ad7c32e 27793910 CPTAC-3 a587c48a-28fb-43b2-8b6c-90218f864f26 16fb7b4b-f3b6-4346-b6cd-d1699bcdfbee Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 26c0e9c9-d919-4dcd-8aed-6fead9be65a6 cc07c8e0a759827bf8b8c1ec93cffa6b 27766425 +a87106d1-2692-43d5-a505-7d2269f57f91 5e6b9498-6bd3-409c-b152-a1c01168dba1.rna_seq.genomic.gdc_realn.bam 962e925f9abc08ff5a9b91bf78bce564 9524669565 CPTAC-3 e46562b6-3f3e-4886-ade9-43a35cc05c79 1f1a7087-1990-4713-8fa7-6ad260eae8f1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 924dd384-8480-4725-bfca-677de4581cc4 94dcea3a077d3acc0e3f0e5a48297688 9525860464 +e80909cf-1e32-46e7-a079-b83ef233aefe 05f85ae2-5f3a-4f37-85f3-c74a8574780b.rna_seq.star_splice_junctions.tsv.gz 99e1fe2650fdc0801bd37fc6684f9c16 3481529 CPTAC-3 5d9f9c9d-2188-4106-b75b-6add5e560855 b83b430f-76fd-428d-90ea-470913f28f1d Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts a79c97d4-e1a7-4301-b50a-abca01153a36 4564b5d4e6ca75c1bc8494843fff5aa2 3517408 +1a8749e2-3aa5-4958-91f4-59bb9391f8b8 40625db7-d3f0-4315-8a8d-f8a4893e5393.rna_seq.star_splice_junctions.tsv.gz 31b992500d94a74ceee27c50ccc589d6 3101645 CPTAC-3 ddaab412-1171-4704-8960-85d85835e219 85d973dd-9126-4757-9da9-249a1672a302 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 62d821de-7fed-457e-a039-d3264675d1ed 8cee73e02654a9dd06cf6a5df26725e1 3138278 +d271bb7d-071b-49e2-9b50-20b0d4a0900d c5212d73-ab0c-497e-bb67-62100b372392.wxs.VarScan2.somatic_annotation.vcf.gz 383dbe0f6208f3ed43493d8229ca3c74 373998 CPTAC-3 e2ec60db-be44-4b4b-a519-6320231f7be9 c07b641d-246b-40b4-b031-8ff1fab81044,fc028a4c-0e9f-44f7-9d44-d51bee5a66b7 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 608a8f76-f8e1-4aaa-aee9-2c765b373873 e77aeace1df6cb27678bb7df0550ca15 392233 +360b2c03-8dde-4a61-8145-d94221fc8f9a 8828a8e4-28d3-436a-bed8-b521be3971b0.wxs.SomaticSniper.aliquot.maf.gz 2840b927f3120f48de06141d02644ffe 1536351 CPTAC-3 86f0f35a-5de0-4c7d-bd63-56141d40f09d c1dac155-9fca-4217-893e-8b02a8e95dd4,90b9cda0-892e-4532-a1c5-44df34c0e5a4 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation b5d322fe-4491-4e32-b21a-6aed6c2432e6 af8fec06a3fcc0bfa13b2baa53a5ada8 1992337 +d92ff37b-9856-43cc-9401-85a41e65b6d5 df703f03-c50f-4c54-8041-bb983811d6fd.wxs.VarScan2.aliquot.maf.gz 44869f8f8b024236e05e3f36e478f0d5 86340 CPTAC-3 f8a5b06c-653d-4a39-a3cd-72ad2784ebd7 6c385d7e-9b75-4b98-92f8-903fd6337d95,ccbbc857-6f4f-4bbb-8faa-84b5092fe6d6 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 476b08e2-0fb9-4469-b973-bedf1f854963 996e6681d0c9ea839ad690876bdaa9c5 106839 +57df883e-913b-4e7a-94a4-4c1c87c070b3 22c3d29c-3029-4876-9acc-a099bb2d66d4.rna_seq.transcriptome.gdc_realn.bam cd142e840ffdef28f4dd1e5bc57a134d 11803857643 CPTAC-3 1dcf0d2d-d119-4654-a7b7-28d1eac23772 5e21f7da-d7b1-4235-9be5-fca13fe6048b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome e00d1560-0a8c-4b05-9707-7972479d3679 77d6965e74b6b14c77de75cf1171adcd 12956692466 +3a560603-8bb9-4770-803f-5b3ff68e6ec1 24f94aa1-9710-41e5-b9ea-89343c96f7ca.rna_seq.genomic.gdc_realn.bam 91fd6f71ddca9e70fae3ed911da33bfb 7596038456 CPTAC-3 59ee99cb-b820-4ae2-9306-105205f1bcb8 ae2442d3-78c2-430c-9169-37e1298be8c1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 6a70e252-3c2e-4a86-af4a-24347b7d96ff dba4970b248a9ffa0746ec35fbbe4fca 7597482780 +714d6d84-cbdd-4a57-9c00-9fe61ff887b9 230b5f08-35c7-4063-b1d8-1cedc15df9d4.wxs.SomaticSniper.somatic_annotation.vcf.gz 96cb87972b5c673f70274023ec500caa 943835 CPTAC-3 715f4c03-f9ba-4cd7-867c-a4e69a1d2f7c 052c318a-0d9e-4bea-97b1-7f8bab5866f7,9a3c5972-f65d-434b-a425-b815f5c1ade7 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 12d6e22a-761e-4062-a8c7-82563ef7a9a1 686c07a33b4f89877bf2649287799d02 974179 +27e2b056-6d48-460f-abcf-eeae0f217cd8 51b02eda-4f1e-4ffc-80a8-abd1013688b7.wxs.aliquot_ensemble_masked.maf.gz 2344018c1883fa11455ba35df399fd4d 14674 CPTAC-3 fa3bda9a-329f-4422-9c13-10c38f546862 9a42f513-8016-4919-b2f9-5417ad2a5b8c,68aee3d6-a976-4077-b5ca-d52924379119 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 90f5a10f-f1b6-4058-84d1-2fdc6380ffab 332c64e37c4c1f4c848833bc6a43d22c 18757 +7abe1a84-a5fe-4499-a795-045ef14a7a56 fd99ae30-1548-44af-bb1a-3baaec35ebed.wxs.MuSE.somatic_annotation.vcf.gz 5d50d83f8dacdbc757a5c1c7b3d590c9 577701 CPTAC-3 3da7fd40-f066-4057-b5b6-24f5f4877f8a 556af585-1b23-404c-ae5f-9a74ebc5356b,a5b555c2-cf25-4110-829e-6d4d6ba23e1e Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 1128b9b7-cb09-4e5f-8ed0-b835005e8a93 60f04f443e59e3aa6d6308e9dad0bb88 633388 +da5df431-1865-47df-ba17-93321f48c127 db0ca7fb-ced6-48a6-9e2c-40e8d3b1dd74.star_fusion.rna_fusion.bedpe dc7cc255ca0cccd15588478757706a6f 1128 CPTAC-3 da1fdb3c-3031-4072-8ca8-96f1729ac276 1aa3fda7-744d-443b-8907-e653ee5056e0 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 3d493e9a-a75e-4d34-b74b-68cb041dcafa 1e4ee6bb718990845519158d6d2c84c8 1118 +510bcf2a-44f5-4821-b885-db740a37594b 4164e0e9-8038-40a0-b5a9-61f9617e9135.rna_seq.genomic.gdc_realn.bam 696237bec1dd11c4eda68c6a1efb8093 6469999487 CPTAC-3 3c0035cc-7cf7-4319-a5d2-79c79c4fe9f5 8e057a91-a53b-4e85-bdf9-3a8bd834f4b5 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 400c5102-022e-4e11-b2d9-845359b3ca69 ac1a026859f5b849e4245158454ee8d6 6470793023 +392593eb-07db-4c29-89ad-cd2489abcc8d 60684c4c-8427-43c0-908e-513c24c2ebe7.arriba.rna_fusion.bedpe 1abbace4fc5f4d81ce3382cf81a5578a 4229 CPTAC-3 d2ba6170-58a2-424f-974d-403af8f2f6e5 b74acaa4-369f-4a1b-847e-a293ceaaa880 Structural Variation Transcript Fusion RNA-Seq Arriba d585eefd-7028-4f2e-b11e-99d111f0d4b2 e598651ed4eb2b1366edf77778e1602c 3971 +0c7501b3-bf98-4755-8f5d-3152c9db9cbd a5f135ee-5265-4c4f-8612-d5084ca79f50.wgs.BRASS.raw_structural_variation.bedpe.gz af4b1a0f0ca3b30ea885cc369a66011e 11580 CPTAC-3 61ca5e2a-1809-4970-a50f-07698816ef85 1343972c-60e6-47e7-b70e-d19bd6d3f653,2e314885-1454-4783-a831-75870cf75983 Somatic Structural Variation Structural Rearrangement WGS BRASS bbae9f4c-79c7-4f80-b026-121fbfdeedbc 0cc3346ee282b7bbc9d3bffbc80d4d2c 40874 +c935e48c-eb92-4d64-86ff-06c8849e5a05 a1bf4d6e-c4a6-436e-a5c6-bc92c559efae.rna_seq.star_gene_counts.tsv.gz 69eb2f19f8925ec736705dfa256f29f8 421941 CPTAC-3 ba67964a-2738-4d95-bf42-8e2217ab4dc5 bcc6a9c0-d52a-4624-8503-22788ff5978a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 8775d86f-4420-47ac-a752-a47eb8a380cd 545e70fabeda78e4e39f51c33eea92ef 4238190 +43b62567-7c5e-4b35-ac0b-57dcf3ac1508 2d0f5744-b6b4-4211-a436-24a778a9febe.rna_seq.transcriptome.gdc_realn.bam bdcd1f7286bbb9bae495a8bd79ffcb7c 9278001015 CPTAC-3 669caded-109b-422e-9c91-2de87edfd052 5b4078bd-967e-4815-a12b-63c52731ac79 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b15c3d50-e189-40be-b2af-edf983fe9ee0 488e8fb2a6b191e9cd9ae944d075480c 10490493547 +c7c73464-c722-4e78-af74-cca0e5531672 88ef1d48-df6f-4033-aeac-9541865fd5b4.rna_seq.transcriptome.gdc_realn.bam 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Annotation d3dc1848-a702-486a-b665-a99954446879 2c0ce9fca8fa57199581f6f3c311100c 805181 +c61e3e35-ca02-41fe-8065-025b4d1e1ef3 215ee23f-0bee-4208-a70d-f188b8d73b79.rna_seq.star_splice_junctions.tsv.gz 745ed48aa93d8e62361c5fd9a370feac 3173417 CPTAC-3 ba037761-7166-40e1-8f27-1c1561a18b9c 1e446c25-0f79-4ade-b721-5e713fd0a9f5 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 63356460-8584-4b1c-9544-b56daaf11fbc 5fef46e7432b7b1bd3ba6cb51969f00e 3213723 +7df49872-6616-4008-be20-326d2b89fcda a983f83b-9c35-4733-9feb-632687100a2e.wxs.Pindel.somatic_annotation.vcf.gz 24daf03e7dfb93458184b3bb56d3b8e3 63289 CPTAC-3 2d1ffb7e-8600-4d11-8a65-f27558c3ecfb e08784ff-f64c-44a3-8b35-3facd041574a,9c909c63-b574-4d09-ba11-1cacb92a327a Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 962788b7-2170-4c83-935c-40341d6c76e1 7062fcb71b4cc30452ee5108839f7556 62844 +4c27e999-8dd9-48aa-9123-32b58ec19d96 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RNA-Seq STAR 2-Pass Genome 5b610db7-096f-41d8-845c-9d59ca95069c 60becbd5f46dae9fad14254ab235eac2 8441421981 +81f0b63e-7b15-4271-b078-e4f62c5229c2 fc45bfd0-401b-498b-9130-8cea9e232eba.arriba.rna_fusion.bedpe 338444da99f3d5656041b895916b8853 2970 CPTAC-3 a4dcabb2-3414-41e7-87f2-a7926ed625d8 d3c94de2-dbbe-46f2-aacf-d848be1593ad Structural Variation Transcript Fusion RNA-Seq Arriba 25dade44-6968-4aa6-95fa-7d87e9825532 bf21392bd494ba87d6e1154091bedd90 3685 +6be7ba0f-9ea4-4094-bfce-738666691c39 73044442-b91f-4e00-814b-b173816b63b8.wxs.VarScan2.somatic_annotation.vcf.gz 892d62401df5477b9cd389ba9767868c 315494 CPTAC-3 adeb86f4-17ca-4ab1-b5aa-30ea0f5bdf56 945dbda3-ac53-448a-abd8-96ebc5c55b48,b6b55db6-b2f3-4d98-b1d1-3958bf5ae28f Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 6410c8c7-be49-4cfb-acc9-c84f1f2f86b7 3a92173f733494be6217b00b994c5a3e 331384 +cb4497c9-7202-444d-a595-3003faf1a69d 3bea4087-e72f-46cd-9dd9-bb284e799212.wxs.MuSE.aliquot.maf.gz 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4feb104d-bc34-44d6-b867-40d855c32dde daa67566f03adf0e7e4591e137aa4675 316990 +d0ddd283-5e7d-474d-9098-429d57233972 d4fa74cc-6367-4cd6-8467-044633d3aecd.wxs.aliquot_ensemble_raw.maf.gz 9b539770f2b01fea4f8319a7a1683779 483282 CPTAC-3 98bed41e-96ac-434b-90ad-cc7223998602 0ea25eb8-290a-4a16-a5db-b5b4c4be0e32,db37ef3d-5f8d-47c4-9f46-2ecafb8ee37b Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking de48814d-0c01-4c46-849a-e757e0fd715d 9546abd89a16bbacae3059e8a41dac3a 607068 +6b8bcd2a-b1e3-4946-81df-a79d40821ae6 1db7a747-89a9-4133-a216-4653520bc5ae.wgs.BRASS.raw_structural_variation.bedpe.gz 7b19a664967ebe6cfb96fd07f5703f52 1138 CPTAC-3 ad688008-ae8d-4bfd-99ab-24998a2c248c 4f0458b3-ec64-40f2-9332-0a3ecc0ddf46,cb8f35b5-827c-471e-8b72-b9430f2df9a7 Somatic Structural Variation Structural Rearrangement WGS BRASS 165dc93a-062e-4cee-82a8-401abbeace53 b7913c37b3c8511c694edb6dcb1ccc5d 2606 +194aebd9-6f02-4bc8-99d4-f2fe3f879f04 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Annotated Somatic Mutation WXS VarScan2 Annotation 87aaf3d9-8d47-4d9a-8369-ed06e1d04b3a e2a67efa8457a1370ab991f1a78bd01b 375717 +7e8814ca-e1cd-4bc1-8e43-271a4cc6bbce c0530981-eeff-4d06-9129-2bca3b9b9255.arriba.rna_fusion.bedpe 6f061a62989d3343786045100b64eb58 1951 CPTAC-3 239a5fbb-0145-46f6-8ec3-2a96a04011dd 37b95732-7fab-4d4c-852f-1d430d2acdb6 Structural Variation Transcript Fusion RNA-Seq Arriba 9c42761a-3fd0-4411-8b72-6da2353bad10 7459e51e6750d7d66e19484329d60dda 1460 +060c8c2c-50c5-40c0-bd71-60a28e08aa8e 29af8dda-6b60-4cb9-a662-957ae712b589.wxs.MuSE.aliquot.maf.gz 8f1d56a0083898aba764a238a0081796 147423 CPTAC-3 b18f1b80-72f1-465c-816b-65e06d2b1fa6 c123a154-adec-48b6-923a-9bc5a29d1601,2339475d-cf4f-45bb-adba-cadfb3acca30 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation d3f3cb6f-e4dd-49f1-b301-08ace0bca91b a59b0a72a33aa5551d232c9be55c293e 177116 +a4aa830b-693f-4cc2-a739-765b31844e0d dd97641d-a083-4bc4-85f1-798a9507da7c.arriba.rna_fusion.bedpe 47f36ba83317456a4660e0b812c1466a 5037 CPTAC-3 fed33fff-0310-42ad-a7dc-d563792f18cc b4aa1028-91f8-4791-a666-711da8f22bf7 Structural Variation Transcript Fusion RNA-Seq Arriba fc1a0bb7-4b34-45a2-ba34-debfe7a6cae6 8f84f7827570f1d6bd5c232ea30fa7d5 4055 +061fe54c-62cc-45a3-8f7c-43f92d1d90b6 5238a59c-82a5-4dbb-bf00-f55c8545de76.rna_seq.star_splice_junctions.tsv.gz 4e135e519ac229242bfd638119d9d10d 3103084 CPTAC-3 872dc350-1ca9-4910-a76e-e244d9636f46 a326b125-78d5-4634-bab5-2fe733b4d68e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 6f1d7a13-7cab-4846-b718-42b69b6d54d4 07d0b0c368c1939aadd39be1c6d9f644 3141158 +6369b7fc-cd42-490e-b2ac-f690f9050f2b 4ccf38f2-138a-4acb-ba21-b6988a69ce40.wxs.Pindel.somatic_annotation.vcf.gz 0eb17c782afc78393aef1f8a65275292 684120 CPTAC-3 48737b20-3e04-490b-9b39-921bf2c09e52 004f4cdd-b07f-4986-83ec-2288789ae627,84eb0d82-6640-4db2-a981-44810476cca7 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 0775e90a-74a0-4e7c-80b9-8bfa4a399efe 4da815c102c05af8058aeb443ea565f1 675368 +5183ff92-9c07-49e6-8fb2-5af63c5743f2 75a008f3-ad56-4bfa-9ef0-1d49e87a7672.wxs.Pindel.somatic_annotation.vcf.gz 143174e39ee15855ad3a8b9bd09dfc55 433813 CPTAC-3 e80deff0-6d18-4093-8d6d-ee481e4d06ac 7c8a6a6d-4e27-40d7-af65-aed871abbd2f,3f1962c7-2a1e-4ac9-b8e0-3e0ab8150728 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 95bc0885-3095-427f-bf1b-a0aa49caa89a f71065134bdb4ed7d6b90185843c0c0a 425723 +a72c4aea-0858-43eb-bff2-e6742c6e748b 8791bd03-58e1-440e-bdbe-949c050bc7f6.wxs.MuTect2.aliquot.maf.gz f8fd67ed9f916c7f262c3ac1b2814aac 5813427 CPTAC-3 3348ec86-9b46-4f5b-85ad-1a126385b695 378ea411-3d58-4f9a-803d-8b7b89c9a5b3,e8c358f4-8994-4b68-aa8a-521b69eee0f9 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 9742ae25-06c5-4ce1-bf6a-d6c7278f6331 f6f179d3aa9772a57123fd862b305098 6906205 +8ba32a15-4f66-4a50-b980-494e635cae2b 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STAR 2-Pass Genome ad0ea188-0ad8-4bee-a357-c47b13e26483 a0079b1e27028eab65c04cab7d2c1697 6329248607 +d9beb7a8-5a88-4b8d-ba7e-e8cfba4e8f84 d44a239d-6df7-4a7b-abc8-61c1e14c431d.wxs.aliquot_ensemble_masked.maf.gz 0472472b302736ee5d789903a1649e44 14224 CPTAC-3 f9f0c320-a695-4e5c-b1e9-8b6d013a0a9b e1a71e63-7248-4ca7-a7a5-be2a7c90de9f,c1d8b688-7c23-466a-8885-f6fa38811bac Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 163d2a41-5ba0-45a2-a914-cd8a6c5a4ee3 5e77fa16a02bb569dc28f84164a76e9f 18959 +5d2d6d5b-2765-46e1-9df8-a467362838c4 7038c768-a1b0-4df4-bd0f-c380083e19bc.wxs.MuSE.somatic_annotation.vcf.gz 26f62b30caceb6e38bddc9c57ff98080 192824 CPTAC-3 ce10e6ca-05e1-4495-a3e6-868d375207ca 055a4b03-332d-40b4-ac7e-eb2e3b16fa1d,62e37b70-37a3-4ffd-a5b7-df6b75dedd16 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 744089ba-abd6-445e-b33b-f6257e343778 3ce041fe89a85646651bbe2f21ad5219 204516 +9ce20382-987d-4a2d-8454-0ba78fe94840 76820715-bd07-43e6-8563-c8878332d448.rna_seq.chimeric.gdc_realn.bam 8380b01682830bd6697378ad2a863217 43178230 CPTAC-3 325984b4-c283-4b06-aeb8-8f1c76b44dc3 96fdce6d-82ff-4882-bd92-2156325ae4eb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ac6185fb-1287-4efd-bedd-1654533be2a2 9e6f2070d1ae298857c203ef958319dc 43173440 +9d0c4a7a-60c1-4af5-aaa6-1ccf3764f8ef 11bb8f20-a9b6-48ec-b6cc-8c70de3ade4e.rna_seq.star_splice_junctions.tsv.gz 69bebc42d5244955397d4e3ea40ade1c 3096243 CPTAC-3 5ee53fa7-8ebd-4ad8-9adc-affdd8b76bbb 1651b695-c146-475c-b6fc-eeca00702fdd Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 3b3c0d9b-ae40-4f2c-ba2d-9b37f95afc84 03c51c765920d86ffed63d9913f59b74 3133506 +9993d1d2-47a3-4e74-92bd-d7ce75f28a29 94304b7e-c8ff-4cca-93c9-51b45a9e0d5a.wgs.BRASS.raw_structural_variation.bedpe.gz 66da2696a9dfd78f7591600279010934 29393 CPTAC-3 bd2dab4e-ee4b-4477-af13-ecfccb9c3523 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+8d42280a-c1a2-4359-b674-a329130bbf94 20ef1a1b-d416-42ec-a0fc-d42207aee114.wxs.MuTect2.aliquot.maf.gz a2a189fe142516648fa6147083fa29d6 6451241 CPTAC-3 ad9a7ce1-9f9e-4092-8eae-493297289022 03f0c034-cfab-4864-bfcf-fcdeabec1493,91a5b1e6-a1b8-4402-b8ce-842c721fdbcc Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 4bc2c29d-97cf-42e4-a9ac-a4f09a642916 0e50178d50327d16a88792b9a353445d 7763172 +c8b3271a-c8ee-489f-899b-7db4c4f44983 522a9a29-e704-4cce-ab47-b9999f7c508b.wxs.VarScan2.somatic_annotation.vcf.gz 869d867b3668026e985fb0ae726cc31e 314298 CPTAC-3 6ff701cd-7efc-4bac-93a6-7b27d2974d89 ff4668a7-c6a6-42a8-b0a2-87e2ef2e888a,3810cfb3-a774-44ea-9122-965669d70781 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation bfda06f5-2b0f-4407-9a52-ba19c56c1c5c d405dee2c79642a18681fb2d0aa42028 329012 +e618bf68-0525-4ff3-bdcd-13ed85e15402 9e7e10da-5636-489a-b1bd-c4030d281f06.rna_seq.chimeric.gdc_realn.bam 9f43009388f314ffa9289f22ba2e972a 45418536 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WXS VarScan2 Annotation 9d189fad-477f-4697-b539-1ffb6cf0f17f d54a4e48c8e6c61013a00c684ed5b1a9 214668 +11171161-2b3f-41c6-ad57-fe4901a0be9d 188ca58d-fac5-40cc-bb2c-fff3b027902b.rna_seq.star_splice_junctions.tsv.gz b65bcebd881bb6c1b56782791723315b 2850427 CPTAC-3 c9486a50-8d6f-4871-b4c4-692e0da5803e 1ba9ebfe-3899-4f6c-b63d-c1e1589d53ab Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 692ec7b7-2e6b-4bc8-b34e-4c1bd24d2de6 98cd24404afec23e3fb2eb18f0f9e2a4 2878375 +1d7bdd0e-4062-4e29-9119-009cb05e2eb4 ad496032-e26b-4b0a-b48e-ced3294c123a.rna_seq.star_splice_junctions.tsv.gz 2112031fb25b92b8392fdd80581f5b6a 3192539 CPTAC-3 9ed4e3ba-0dcd-4436-bf21-14d68087fac4 a5bf2760-831c-4f49-9e7e-1df33e2eacc7 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts acc20a8b-b2d5-4706-b439-60eb05ca1e98 79991a3c61a867bfb24a049047f9b926 3224704 +4685410a-2b74-49db-8474-5f265f5b7d73 9bf60b03-4667-41f1-aa44-58d46a91ae74.rna_seq.transcriptome.gdc_realn.bam 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Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 32174a04-94d4-4c73-8e28-9b952c394473 540dc7a6ecec31d47672a0dd4b630a02 1467543 +e388720f-2ebb-4786-aca4-31a753da5b6b 5762fea2-d5db-4e67-aec8-e409a91697d3.wxs.Pindel.aliquot.maf.gz 9561ee6c30df2e3c1311afb65a740811 43437 CPTAC-3 785aebb1-a760-4167-9076-53024e317d04 3610bec5-9fcf-4587-8898-7af65b5599ce,dec7ca10-fdd0-4772-9083-99eb76cada5a Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation d04d813d-7629-4f7f-be1b-28429f7a2461 38ac00259fbe3a8676fa08295c04f3ea 47587 +fa3b30bb-1bc2-48b8-95cd-aa2d2b6a2401 57b437db-f057-426b-92b8-972416268931.wxs.aliquot_ensemble_masked.maf.gz 67e79e5f9dd9f2d384ca69e454ab7fcc 282220 CPTAC-3 8d1b1bb3-2633-4a22-a8fd-19c07931ea46 1c70d264-927f-4bb7-b896-3c68c0ba3fa7,db4e039f-71a5-4b7b-814c-bcf90189c650 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking cf17d819-97c7-4fd2-8cd2-8499b7970335 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8ad7c716-d14b-4ffc-8752-7ffe745a6ecb 0a2da5ac2e4aad917122912fdb93603d 2932073 +994d2245-198d-4d4c-be25-1bb696a650c1 a319edc9-51f8-4158-afa6-abaae6a2a9e8.wxs.aliquot_ensemble_masked.maf.gz 989bf1e377f1b4b9a72955e0a1f681c7 69232 CPTAC-3 45100883-6dcf-4cc4-9dc5-ac18358df6d8 dc765b05-ce52-46f4-a45c-200e98c13c17,169a9157-ea3d-4d12-896d-093c39862823 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking c4e8075d-fff2-4527-8533-f98a49d1431e 05c032b2e67f953de231a37530d05ff9 85565 +6816b1cc-9166-4a10-adc3-e5f6935d223e 763c6038-c1f9-4cfd-9316-b272ea5b6a03.wgs.BRASS.raw_structural_variation.bedpe.gz fe077faddb528e68749652942091f8b6 20722 CPTAC-3 afb7729c-4ee9-4a64-8382-422dc3d8052f 8e4d5871-709e-49fa-aa5c-ab5e9060fca3,6fdfe226-a6b6-4836-a287-4b8b6e167e07 Somatic Structural Variation Structural Rearrangement WGS BRASS d2d18d62-6a92-4c30-b649-d4b06d62a5e6 41cba925ac08f5e0221ab738508506ba 74424 +39312432-3d31-43ca-b759-515ce3c9f130 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Fusion RNA-Seq Arriba f6de6d33-551c-4a67-bbf8-1c4dfce670b1 3a1f8e64158fd6740e492d962260e0c1 4145 +b1246e1a-f2de-4654-b413-ab624f74bb34 afc4589b-3d16-4349-8e7d-7717b25941a8.wxs.SomaticSniper.aliquot.maf.gz 928ac7d3e3c89eb05cc006de6afd8b79 2159621 CPTAC-3 4f65a41a-32ab-4b78-aff4-f8c1316687ad 98a99ed8-3078-434b-8734-672dfba4299f,ed416ffd-7a75-4a7c-b34c-b0d650cb5115 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 6caf3f02-2478-4b75-9ce9-473ff07ae79e 90bb8b71e0edf29b54c8efbdef49c115 2722996 +07b05513-4dca-43cc-901a-581b4a268f69 5496e60d-4863-46ed-99e3-bbf7cf7dd46c.wgs.ASCAT.gene_level.copy_number_variation.tsv cc7d729f23db0eeb9fc8133db60a6da8 3481259 CPTAC-3 68daae26-f752-43de-bf53-a0737e50d00e 6924323a-8bd8-4aa2-8a97-0c739132af78,cd161335-d26a-4e88-9cbf-412997314bc7 Copy Number Variation Gene Level Copy Number WGS AscatNGS c3c82604-a7d1-4410-ad14-70d18af0cbaf 98f77ea17f2e94db51796b2f28a033fd 3441318 +80f88b4a-3e35-4514-843c-56f2837b0526 1fefd412-21e7-4803-9aa2-bb26231f83d1.wxs.MuSE.aliquot.maf.gz 01720fc53e3b8933aa4fa3e7a33e263d 69039 CPTAC-3 dbc7d02b-6c63-4961-a8c2-8a8b811d8d7d 04647a29-ea3a-414e-9087-cbc7da3dc358,3fd5c3cb-602b-45a6-af9d-08dbd550b3ed Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation ec774992-7b50-4460-9d6f-5b86a0141427 9d5280ab537de43532d90f676e0f4fe8 94044 +5ffdbd61-54ab-4da3-9733-c14d9546a4b2 232eaa47-5806-40cb-b33e-e79a5ac6c2f8.wxs.MuTect2.somatic_annotation.vcf.gz 1865024537d08e06ba6c81aa072b2dd2 3541909 CPTAC-3 61c4a631-c7cd-4411-b5d6-f55e584faf6d d2db9a6c-ad14-496e-accd-afcbf09093e7,7b5613c5-fbe2-4c47-8aba-ef678ce19f29 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation c8ba353f-9aa5-427a-9e9e-3882a9562fd8 ea7f4c3f391f8b72df8a3bf65d1579ec 3765520 +87d01e6a-5e39-4a96-a318-be69d31945f6 26f1b340-7bc3-4119-b673-2f99ae9ef8b2.wgs.ASCAT.gene_level.copy_number_variation.tsv d3bdc909d0b7ba576260f17d972f97cc 3481186 CPTAC-3 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Annotation 75519d06-9aeb-481c-bc9d-08882ebdf5ea c88fcc275578f109e8d75bf53892ff1b 2737632 +1709ed42-0112-43a5-bc82-d50903296aae 016637c8-5ade-4541-98f6-9341e0a8cc6a.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 e8bc3792-92f6-4924-8047-9f805afb4b04 9478b81c-4959-4780-b5e1-57ea6bfb5c6b Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 60fb859a-aa9d-4362-ab90-ce93dc2b6787 6e5690795ff424264402ab9d2661b62b 229 +4242a134-4344-423e-8e70-788ddc28f934 d6b76912-6a04-4db1-95cf-3f169bad966c.rna_seq.chimeric.gdc_realn.bam 44be4ec23ece4911f3145f6448d51572 163524403 CPTAC-3 860584c4-94e9-455b-96c0-833414095091 f70bbbd3-e229-43d0-8497-446a9a7573be Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric f85d6c35-879d-4f31-8296-7c356130c993 9a49a19e7c86cea08c34c5f5d86577b7 163488880 +b62d7614-06e1-4ad2-958b-24a52fc6219c 984f9b8a-6e24-40ff-8ed6-c00e07746872.rna_seq.transcriptome.gdc_realn.bam 4ca23feb8cb53dbf5a17d6497011f18a 10829506052 CPTAC-3 0d81506b-7823-4ef2-8c94-d8fa624a51a1 5f64e2de-2fb3-4ae7-9862-6074a82e2d22 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 3acb0850-c2a7-4df7-8f33-ecd5f2666f40 71d7a5a3050dcc2cba16efe842907db0 12323354871 +e829c289-795a-4e77-972d-3f0f846752cb e3275a3e-d2c1-404c-bf33-63c7751a53fb.star_fusion.rna_fusion.bedpe b9e1e5355aaf61aada7c52cc2e8cae73 886 CPTAC-3 6f235976-c04a-4a40-be28-8ed9dab93365 191d4059-d2f9-4667-af41-b657add5f0e2 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 87eb01a2-0487-4e40-9503-93d891a8fa9d 02a353e20a4e1179ec6861eb7db4c0b1 874 +b21bfc92-8637-44f2-a12e-b4cf6dfd39ad 9eb4be43-a3e8-471b-bf10-edda13e6265d.wgs.BRASS.raw_structural_variation.bedpe.gz c237d2cf457d10b185d2fc09f4377810 738 CPTAC-3 46abfc84-7bf3-46e1-9e95-1ad76553ba9b 37e6dbaf-8495-467a-97d2-931a4061ec47,6e9f2a37-b53b-4017-ae76-ac141191ea9c Somatic Structural Variation Structural Rearrangement WGS BRASS 6dc64f3d-3738-4ea4-813a-6f470e2da9d5 607da7918d66bce44ac77918b850cad0 1567 +375b6283-4347-414f-bc99-4472a208335c 0fc65fcf-b7e9-4c39-b408-30166d1ef0ed.wxs.MuTect2.aliquot.maf.gz 0f348c51bc849fd698973ee657042ded 2353104 CPTAC-3 8767d970-812a-4828-aaa1-0b9ff956dffc 016f1a26-26fd-47b4-97f2-e1be18215a1a,4562d6e2-e2a9-4bc2-84c3-69e1d9fd3663 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 6b2dfe66-b550-4c9e-8bb9-91c73f0da160 827f6cd064241e482bb2b8af9cb0537f 2659881 +ee16ee66-80ea-4177-9b25-017570fc8108 276e2b5a-83be-49fe-8ffa-2abe6781a73a.rna_seq.genomic.gdc_realn.bam 71e49ccd6030021483057f99662a443d 7884069555 CPTAC-3 e6dd953b-28db-43a8-a4f1-9bf260082107 3e9d0699-bb98-4f86-945c-5bb9cae012bc Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 1c30782d-091e-458f-9e36-2cf7504e2890 3c3aa69e5a9e871ff9c1e323397bfae6 7884877876 +634d6a4f-21df-45ed-8e8e-1daf065f25c4 a0096eee-6554-437a-a61a-3e58b6e7db9d.rna_seq.chimeric.gdc_realn.bam 0c98bcdb2aa6cb89d8b6185a01956e06 42838098 CPTAC-3 80d14fd9-4413-4fce-9d75-f7ec4711e285 b47317d1-3276-4937-9eef-e6ffb7da72f1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 208a8192-331b-4c00-81d9-305520ae73a4 b66b351daf03540da08da09f8b90d340 42820477 +81b3ff89-be18-451d-ba8c-f2a74863e0b7 9b168b0e-5b40-442e-aa94-28d5337ce3e5.wxs.SomaticSniper.aliquot.maf.gz 3a2da6a0598d2d96db3a0588b338be45 554334 CPTAC-3 5690ba19-ef88-4bce-b275-27f715cc44d4 f912ddc2-0ba2-4be5-aad6-aa64ad5fa1b4,b35c7cca-5e9e-4445-8b60-2427084ce2b7 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation f29c1cdf-b2ac-447a-b7ae-f7de4beb8a3c 7eef98a6116ffeb1232bb71acb36201e 745344 +87829d6a-6644-4a27-ab32-ceaa64c01b5f 4bdc1541-8360-44fc-a5a8-08d36fc79143.arriba.rna_fusion.bedpe 6d9b9376e815c880a4d55c4e89373d07 1802 CPTAC-3 ef69bf08-bc64-4f86-9604-17c77bb4b27e 9573ab0b-4cbd-4471-8eb3-6ea38df4e9d7 Structural Variation Transcript Fusion RNA-Seq Arriba aacb0455-b20d-4189-b700-806e7290d383 a5344f3a40bd38c82c9840ec76b73039 1014 +79b91d32-e0a3-4723-b84c-2ee6445f9bae bfc05fe9-2a3c-4e61-a27d-77eb39b3d627.wxs.Pindel.aliquot.maf.gz f0b450bc4b642e3af4c0d82251525321 35837 CPTAC-3 6ff701cd-7efc-4bac-93a6-7b27d2974d89 90efd267-01a3-4c8d-ac68-52f973a6f027,3810cfb3-a774-44ea-9122-965669d70781 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 32b27999-87e3-47d5-b4ec-625ae14ab0b2 9297f2ec44494941894729b6b1a89766 39288 +d1f8d4ed-d784-4f84-b834-666362e695c8 7c59c27b-4232-4146-b36d-ce23de7fba1b.rna_seq.transcriptome.gdc_realn.bam caf814610bc04d61d25a07bbc4756d27 8114362587 CPTAC-3 ba0fe300-d3f0-42fd-b609-3ee3d0e49d7b 834f8510-5890-4124-912e-192ee6bb31ea Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 426ec756-7bc8-4167-8024-ddd61fc3af03 411c36fe376e951d98e0ecfd33f1cfd0 9284220107 +545cf27a-76f5-4293-862b-461f7448ba39 9b7a2f48-e658-41b9-9d4a-68d83082cc29.wgs.BRASS.raw_structural_variation.bedpe.gz 1ef722638fee256675d3fd608adba76b 31660 CPTAC-3 4b29f9c4-3e7b-470d-be52-44af8733f056 c9645e62-b3e4-4624-90e1-dfb6cec6a2e1,af5e5eeb-1d07-479b-902c-a8c807108148 Somatic Structural Variation Structural Rearrangement WGS BRASS 8fcfd05b-db9b-4952-b53a-abdad0322865 04604102b09e3795df81db4cb6a0de84 121251 +430f10db-e316-430f-851f-51a360c1d2a9 07973777-cf3e-4f95-80b7-9532bacf3437.star_fusion.rna_fusion.bedpe ef760e37afac4e67a516d1b92338890c 455 CPTAC-3 c162cd70-4f27-4361-94f5-882259f41522 e954edf9-525f-4d7a-9bf1-28b065f63399 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion b5ccae40-d4b7-4e89-8dcb-ae7b38407c6d 6e5690795ff424264402ab9d2661b62b 229 +add7a8f9-c467-4a3d-9e1d-e8b13f3c472a a8c74318-d6c7-42f4-bb1c-8382cd071063.wxs.SomaticSniper.somatic_annotation.vcf.gz d6c3f955c2ec4cd006223186fce22bc5 327024 CPTAC-3 32b7854e-de74-42d6-a4ce-f4b304956ee9 47d67c08-4bdf-4fed-a0fb-fae09f213c99,7d908a13-1a96-4c8a-a8ee-2574360aeaff Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 6edc5baa-d94f-4450-ab93-30b60362c765 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Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 800825eb-18d1-45eb-bccf-5be59c1ca9ad a8ee81b13fb3b5152c6c0162ccf4ba29 69139 +4f357375-62bb-442c-9bd1-fa41351ec714 3fefb213-88b6-40df-9220-f0b96e1f1c7b.rna_seq.transcriptome.gdc_realn.bam d2175840ecc748abda7b730fdc6a2d50 7220577151 CPTAC-3 f05dc58e-c9dc-48fc-bf07-e0aca961797a 94d601ca-c75e-4136-8c94-f59291e859e3 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 4d985b25-1f04-495c-8428-d2c16d47c9a5 07a21a49d571eb29527b41d4f74e55de 8108245710 +5bc0ea98-3629-4d45-ada0-129f0af27759 314896ee-3e66-485f-9f78-3fe892a633ff.arriba.rna_fusion.bedpe 129d6909f7fe5c19520feb68f3ecd544 3125 CPTAC-3 8ac75c82-eb1a-4e9b-bbe9-131a78a9f540 a7e3a6fa-4202-4fe0-bde0-3b985f6dbab0 Structural Variation Transcript Fusion RNA-Seq Arriba 610ec762-7252-4da6-af3b-040280e5c6e3 bcc153b5fb2a2ee425ffac887c383e6b 3199 +7ad5af3d-7d80-4496-bec9-51112e84410f 97752d52-bbc4-4792-8e52-535d19cb9dad.wxs.MuSE.aliquot.maf.gz 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524f25d56788e2154874fd152bc9508c 44616872 +2fd93e6e-2d71-4651-9f48-1caa7a2a03cb 16ea195e-383c-42d2-a051-d8f94b5534e1.rna_seq.star_gene_counts.tsv.gz fa0756c3f5a0c32b3586314e95106c74 417115 CPTAC-3 d79d4830-d55e-4efe-bf00-9543461c7af4 9f719a4a-a9b0-4a83-82b3-b1e1178dade5 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 601e1be4-db93-405e-96cf-1fd534af6ae2 46f16ed3853b73349b92108a8c1c8b48 4236621 +85a73465-8238-4f69-9dd7-d07538b81155 eb45083c-59be-4515-9513-928e8390be6b.wxs.Pindel.somatic_annotation.vcf.gz 5cf30cdab90cede8a619dcdf924a5815 667324 CPTAC-3 410b95b4-6d38-4c25-91ad-c09f2c34325b d47d42c5-c6c1-4788-b66f-9e4eb2854c67,abd00977-e5b2-4ea2-9840-a0cbcc03e13c Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 4a6e059e-99e3-4bbd-8fb1-4b4bbfbd4325 e911d43f98164e0d818da18a8da35328 679243 +83425b84-86e7-41be-8f5a-687d8830fae7 54b51b1e-3880-400f-85f2-0864606b32fc.rna_seq.star_splice_junctions.tsv.gz 36e8035ebb229437a0365dc8287fec0f 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Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 18730770-6844-4e84-bcaa-f927c233ce38 17a34d211e441a14fc5e794bb5c83f28 8948929869 +9867ff0c-e47a-4850-8af6-1932511154ac e597d73a-5e35-41ac-b0da-05640d38605c.wxs.VarScan2.aliquot.maf.gz 366fe91ef9656af9c7f0953fdd5e58b1 306179 CPTAC-3 1632bbd5-d5ba-42e4-aee4-c8637991a892 bec76c94-3da0-4689-9357-39119f6b1418,7b562d7e-e216-447d-aea0-dec192194ad4 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation e837ae55-83a1-4c3d-95c3-fd01d1115686 0091a692abff0e7e18f05774b73c0222 391550 +6c3d742c-f1e2-4485-9c5b-ef7482e17bb7 e9e0eb35-bd6a-47f2-953d-5d40ea806e3a.rna_seq.star_gene_counts.tsv.gz d3db21d5b1a1995bdac7be81bff2d36f 418627 CPTAC-3 17e6c62f-cc0c-4e13-a80c-f9bd6c2cfb0d 9101a748-ac4f-4aa3-8abd-c6e4a3691619 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 154017fa-8ca7-43b6-b417-86b9890083f0 7e19e6f521f4eb8ac2f4c38528a35873 4232210 +cd823de0-e397-4ff0-ac91-81fc2029033c 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Somatic Mutation WXS SomaticSniper Annotation d536caf0-cf51-4015-9cc6-15cbcb62b49b 7db6c47accb9a70dd9806d3183f11910 1442241 +61f221b7-d54e-410f-ac78-d06ab7c0f3b3 0a2067a8-fa1b-402a-aaff-8b28cecee830.rna_seq.chimeric.gdc_realn.bam 89f021c779bfd3f197c8a4fa8e38f996 39007647 CPTAC-3 b288852f-66f5-4949-bc13-883e634313fc 4670d6ec-b2f7-40d7-ae66-039ad794cc76 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 07c69c7c-081f-46fa-8bb0-9691946f4a45 1e764756c57b3fa44d0e3a18b3892788 38988076 +2aaf1b77-af6d-4a80-b25e-15cd7ff0eb13 6c9f7998-16ad-408a-b83e-85d64173eb96.wxs.MuSE.somatic_annotation.vcf.gz 7b9ce6cd341b886af6f6f2b1df727f5b 158672 CPTAC-3 bb039a50-909b-439b-ad8d-4abf711e4a42 b9201c7a-1778-46da-a3fe-855315fe403a,855b4f54-6be8-4afb-bbd3-ee97f4f24be0 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 569d1bb6-d909-450c-b3ec-8147c4a683a8 194b8eac5f8673f9a80fb9255563bff5 170248 +92251a4a-e6f1-4a1d-9112-a9bbd367db51 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Somatic Mutation WXS MuTect2 Annotation 693269dd-1b7c-4f3f-8436-5c5c1fdd1209 d52e7a1256b6a23068b9edd48c4d8848 7858218 +7d783371-1267-4eca-9e04-e9d5cca2136c 249d522a-2058-4687-9488-b4b8bd62eeb2.wxs.SomaticSniper.aliquot.maf.gz 6e0cba6379973ff7875c1f3d4efa32ae 955570 CPTAC-3 9816a96d-edbd-4f6e-8a93-69c5ff368417 d9a888d9-211a-4a13-bbed-23dba208a9d2,9c7363c2-750a-408e-aa11-1bfaae41e7d0 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 10638d26-94be-48e2-9cec-3cd8c0d1f512 50e29b1b0d6b215c2eab94597f5b4427 1243180 +8e1d88e7-9602-4442-a850-6585b66ef591 29cbfb63-6e93-4dce-ac6f-60fef4f4fe39.wxs.aliquot_ensemble_raw.maf.gz bab6ed41957420011636b2cbf4d7e6f8 168376 CPTAC-3 5cb7b327-5f17-44a8-aed3-989a1a99e780 20edbb55-6868-4cd4-a52e-39f17635dba4,59f6a8d8-d2ee-44ae-8a9d-473c5812c66a Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 181b4c11-5141-4ed4-ba88-616066141fc4 8d4f2172cc9a1dfb835b514d2009e8d1 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Annotation 4d558227-94f0-4369-8f1d-5d6268fb00f4 aa939f098d3b48342d443f6daef0f399 758055 +6f46d64b-1189-4520-bfb5-cbae3c917bf3 270b976b-d199-4d2d-a207-dd118adad06c.wgs.BRASS.raw_structural_variation.bedpe.gz 5f4ca9d61c613f9a9a322fa68506e515 5849 CPTAC-3 f0dedbcb-1151-4bdb-8f32-9c3311d298fb 6d4a2a29-c227-4878-8bea-90a054f4950b,dda4c83b-732e-4465-9f7d-f790f7328218 Somatic Structural Variation Structural Rearrangement WGS BRASS f6fb4f6f-13cd-4d1b-9b45-6c1115cd5e53 3bc95df67b8d9707ac90c7ad02f9e49a 19343 +fe7b0cab-6af9-4823-bf79-d5c477a5aa6d ba66e3db-8d01-4ce1-bdcf-7e8850fb7772.wxs.MuTect2.somatic_annotation.vcf.gz 250aace49b5a68d2ef7dd742ea23c60b 12528210 CPTAC-3 ed69df53-631b-4c3a-af08-e502cc64129a 331f1cd5-0c8d-4594-9f92-2364cb839192,2fe6535b-e5dc-47a4-a646-7b014053a3aa Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 8b424595-6527-4493-8d9a-366a68701608 f027fa6ca23044593fc6990a15364080 13736178 +83631d40-1f24-4e18-bae8-e13494466890 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+ec083db5-e7e1-430c-9f4f-cd3d342b2ee3 2cbf9ecc-ed0c-41e0-b556-4bb8b9392ca6.rna_seq.chimeric.gdc_realn.bam 2992bb823a4583b4c5f3c185ef858180 99892203 CPTAC-3 fcea94a8-32f5-4021-8d27-b4d03e8bb3f7 811ef88c-9863-4dc9-8e02-4f229ef9f96f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 578ba582-18de-4278-a9ca-659c9c32e1c7 902164d47b0353a84ce6b8199cbe94a6 99870007 +faa67dce-078b-4f25-ac5c-75e5f96ced0c c6758665-5587-4e98-97cd-139d22b31048.rna_seq.transcriptome.gdc_realn.bam af5c308459e2746ed33ca2393567cdb1 8300038664 CPTAC-3 98bed41e-96ac-434b-90ad-cc7223998602 c5457d01-f4f0-446a-a62d-a2e5703f3d92 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 76db6b1c-0071-45fe-bf17-f7a435d4b8fa 5e6a6f9ac89728d8c0b1b20ba4c56e0a 9365875572 +857bef62-b55d-4526-898d-075fbc3cdef7 fd5ba74c-b762-41e7-9d0e-e54210b7fd2b.wgs.BRASS.raw_structural_variation.bedpe.gz 69f624f469dd1cb947fed8aeff3ee2cb 10304 CPTAC-3 aec3c953-dd96-402f-807f-9be99d8a8aeb 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SomaticSniper Annotation 65b0743c-ac32-43a4-ab6e-036e6fe345af c126dffb2abe3d18e3bb8957cf0493b1 1189107 +00426658-2f25-4cd0-98c2-ffd8215cb74f ec61ee22-bfa8-4657-952a-eb7ca401a102.star_fusion.rna_fusion.bedpe 1d1986a5cb9c7fab91ba7bddd3e5a67a 454 CPTAC-3 a02322a0-c133-4220-a6f1-508f90a99f8e 2305cf9b-f8fd-488c-bf2f-e2637aa6cc52 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 1f9be1c9-3770-4e3b-a004-eb17eabcc363 6e5690795ff424264402ab9d2661b62b 229 +c446244b-0bb8-48c1-80a8-c85593e67157 13e15029-d159-45e4-a076-f8fc2bcb6ecb.wxs.VarScan2.aliquot.maf.gz a50f619226b3fd854ef987ec89e70813 407790 CPTAC-3 1c5f10ce-d248-404e-be55-bf8e37db0240 0a96746b-2a5a-4b98-9b2e-7d3207b988fd,55194cd1-6ee4-4c6c-ab7e-ff73a429a1a9 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 3c58256b-1c94-4867-9b1b-3500d5cf0ea0 435ec386187edb401047d714c214aaea 475188 +62571042-acd5-4d13-9577-f5e83e4e5ccb 05af3572-9e14-4e12-ac43-9a3becf0ab47.star_fusion.rna_fusion.bedpe 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Annotation b9b7d4d2-4f97-436c-b3bc-3910e612f6f7 7d0174e6b55a11d3c954fcedfa05ed05 59055 +2d3bd350-d999-49dc-ab8d-b33faa0d5e44 c578ab18-cb73-4ec0-95ee-562fef2c87e9.rna_seq.transcriptome.gdc_realn.bam 03d6f360d5bd43a361abebc93298a465 10351823654 CPTAC-3 eae77c25-2317-4ec4-8f21-3975ac9ab827 f6ac31fa-56d8-4c8b-a21b-8d7f5e538572 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2b22bcbe-9b7a-4f5d-b285-e24b227ccbd0 3b0b0ad425727de59626533a5e0f6c33 11637410107 +f2bbf37f-1a7a-441b-a6ba-8a41b2ad2e05 1a41c249-457d-49a1-a5e1-9a62d4e89c54.rna_seq.star_gene_counts.tsv.gz a7cc2d4cf9c86b56c4386af4f5c33037 418420 CPTAC-3 54af5967-283d-4dd0-90e0-d2c351694c4c 72d4f312-7a7b-4573-9d24-cd0c6251971a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts d81df0fa-def8-4ad8-9266-86745a1842ab 4b4d3f7c8db4a380dbdd8168926a4d61 4231832 +fa5c705b-012b-404d-b5c7-3e63640a81a3 ebbf2f51-93d0-43f4-bee0-fa52858127eb.rna_seq.chimeric.gdc_realn.bam 5c37c803545f30a7ad5f7f29e3934a2b 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10809132-3baa-42b0-927b-28e0b51838b6 9c34c78daf0ec67e6c3ca8d472afd605 6783252 +05250070-3bdf-4d7a-9692-f090a2be8001 bea63b22-9e43-4263-87c1-2ce46a4e5b3a.rna_seq.star_splice_junctions.tsv.gz 5885df62a4dc322ad40167fde6a32ca3 3412129 CPTAC-3 cfc61554-67b2-4ab4-813c-5f9b72bc325e d2d0e91b-12ec-4dbe-8c1d-c419f630e615 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 0173454d-7b40-4562-aeca-024f1e9b0b2e a6030e06e28dfb0d02103bc8421e348b 3450672 +8a579c15-cbaf-45f9-8c95-017e411f95d7 33a6bb0f-d5a4-4c8a-85fd-d65f457e3df8.rna_seq.star_splice_junctions.tsv.gz 6a252b5596cd6e24cfbf7cba20212068 3003561 CPTAC-3 533e8ab7-099b-458d-bd82-ccaa066b5f82 c33d7302-616a-4893-b241-0599dfc4911e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f869817f-fdd2-49f1-995f-3d90bea2dc14 86521a4d5e46b654d40825b7621709e2 3044173 +db223255-cf7d-44d7-86be-042a6872c049 ba4fa647-5f65-47ba-9f47-994e1854b3d3.arriba.rna_fusion.bedpe 1a85696bb0b34efbec5f2b3b76861980 2193 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Somatic Mutation WXS VarScan2 Annotation 956c4aa6-7817-406d-92ac-4643c722a866 ff41c9363876835a48049bf532e0b867 249118 +1f2e9c16-713d-4688-b99f-2fb86b8aceea 92e1bf44-71ad-4920-b46a-6482c63b9319.rna_seq.chimeric.gdc_realn.bam 6cc226c05759abcb1e5db1dd07cf2297 169427046 CPTAC-3 d9b2cedb-cd03-4464-b423-cab6a753213d 9af36d0b-6d21-474b-a70e-88892d0fbc1a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 01c101be-6a5d-4327-8e0a-0a419b436707 8c37bb3d0272f3b5a86cd04610799e4c 169400394 +df1b66bd-d87f-4a40-b91f-28efa6fd09a3 8690a95f-690f-4e00-8616-e86deaade4e3.rna_seq.genomic.gdc_realn.bam 311f01afe97d149be06448b86c0207e7 8128284195 CPTAC-3 b4f1321b-865f-4f3e-a0ea-7678e1dc08ff e85a667a-b5a6-41b6-9064-33b4b253e2b2 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 9c8f255f-0e70-4a3b-9499-3e7a22df279f da96f1d7e2345ad407e2adcc0205e223 8129045978 +373953d9-192c-4122-a1cb-7e0158910714 ec1bbef4-1500-4395-97ad-335fde90eb3d.rna_seq.transcriptome.gdc_realn.bam 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2-Pass Genome bc8ced21-7457-41dd-a51b-69ad11ec45aa 1bcd8a58ce08069431ce1995845218c3 8039236624 +c612198a-fed3-4a6b-a32b-2af27b4eac80 425008fb-b39f-4355-8c2b-c2ebfc3236ea.wgs.BRASS.raw_structural_variation.bedpe.gz 8307b389f38904b35ec81b8917035338 4131 CPTAC-3 bb32a75f-8129-4549-9635-9dc67e610a80 87c5e2eb-49ba-47c4-8f8d-a99d26927ff9,81f9ede6-25c7-4ade-85de-a5cbeff94b5a Somatic Structural Variation Structural Rearrangement WGS BRASS 428434a1-6662-45ff-881e-bfc2116bd99e 1301f0f6db1e94556efd8e758ed04c30 12911 +65bf707d-6a95-47fb-afa8-8ac2025832f1 5f25f88f-4751-4062-8fdc-f8d9c6551fce.wxs.SomaticSniper.aliquot.maf.gz e54a2ae29adc83d15491242707782b61 1153277 CPTAC-3 1663baf4-aed4-4ea9-893a-6517a67c4819 aee98919-02bc-4677-80c2-675b148f9d7b,cc5cdc32-6156-4237-8640-0855f5c3ba0a Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation f331e68d-cba0-49b5-82b4-a39402bd246a 9695ac4c071950ecd7fc36c22a12556a 1477458 +08e15876-dd82-44c9-85ba-ffcf1f02aa30 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Chimeric 05f9d01f-9b67-4424-b465-8f03519d778a 4269f843954f37c7244c1ab28dd97633 60436984 +ce44299e-dee1-4279-8a32-71587c955810 599dd6bc-cb05-42ad-ab15-e1a32c3a5072.wxs.MuSE.somatic_annotation.vcf.gz 49d377b9f7f483df028422efff6846d7 991150 CPTAC-3 e94c9713-d731-4c6d-964d-35b8ed25baac 02977102-9859-41f2-a8d4-089f6cff43cd,24ce24cc-3d67-49d6-af28-d453465da942 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation a0f975f8-eb06-4c91-abbd-209fdf0a3848 7b35b18181028827e056aa9600c4f9bf 1069259 +1141b440-d582-4ad1-be3d-f03022a31b8c 2fd9848e-bdfd-48f5-a314-99e464ba4ee6.arriba.rna_fusion.bedpe 3d512d0127c94a16d5ea8622497ef0ba 1968 CPTAC-3 e8df42d8-58bc-4c43-b18b-5b23f5e61508 dc12593f-588d-48c9-a871-409bfd080502 Structural Variation Transcript Fusion RNA-Seq Arriba 56e6c7e2-6e37-4555-957c-78f44cb854d9 709c0dcdc56e991650e872a2f32df3bd 2151 +6abd81bc-fc64-4beb-b3ab-c08927e1a4f5 3710af18-a00d-4c48-aacc-a95f9120b20c.wxs.MuSE.somatic_annotation.vcf.gz fbd6d5db6a252aff98f17a18038dd403 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RNA-Seq STAR - Counts 51dd26d9-46cf-4357-b689-f0aea4d7dc95 ee6e64372fff6c8572cebe86cb688d77 3163407 +f82f31da-c7cf-4401-8756-84ef2c4e4951 46a89868-bbb2-4775-bad3-8a633cdd0ee8.wxs.MuTect2.aliquot.maf.gz ecbc10419f00f0d2a1ce09b4ca9e01f6 8032551 CPTAC-3 b595f6fa-22b0-4646-9dfd-c49f53623587 7c72d1eb-35b2-4f3b-ac73-db99b0c1832c,89bd375b-f0de-4c53-bc3a-0857dd2a02ba Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 40bff639-761b-4be7-b632-3c601e370d86 56332c425be9b906ba73f8bbcfe8d5ce 9462138 +fd1b6c4f-cb13-4189-8839-442a4e7ba415 b0b9e590-a00a-4742-ab13-77a394315538.wxs.MuSE.aliquot.maf.gz 9a5a273534871179dc770198d0160381 451559 CPTAC-3 6d268ea7-eea0-4984-9e78-1b959f7e9a2a 17383aa4-7eb8-4b1c-9d16-85970c936aba,1f25a90e-1fea-4361-b8d3-4b14350454dd Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation eab0cd6a-b1d7-4d1e-b7e5-b00f7389d648 473bb2ca44f89d6b4b6de988cc168f95 516018 +d8b8901e-692f-4ace-a312-65a8fb54dfcb 55bb1a74-a506-441b-b682-8e64e0c8fa16.wxs.MuTect2.somatic_annotation.vcf.gz 3468921ba09f8417051f6cae6c842ea2 2655517 CPTAC-3 40311512-c531-402f-900a-222e4572296e dcd9f76f-2677-45ee-b940-43a6d6bda211,e56a3c11-9494-43fb-899a-fddd5544db14 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 3fa2a8be-52bd-4249-bc02-d7c5ca16d4fd a27477c8e7743d6e353bb7b86a0ea7c5 2845966 +861dcf54-5bd7-417a-8e39-3189ba977c47 7155304f-117a-4213-9ed5-caa705a3b7c5.wxs.MuTect2.aliquot.maf.gz 7c34839b3967a342ce88c385b3c94f18 6524961 CPTAC-3 178f9a51-566a-446d-a28c-2d16aee4d42a b93f9712-3ac1-4bf5-b4c0-a3f584dc872a,bdc38930-0dd6-4f39-a41d-56574c4b93ea Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation cb54b04e-9981-4f1d-85e3-a4ec5eb1936a 034d68117040f0210d5d91cb22a76192 7651454 +d360fe95-3ceb-408f-8a42-1b5e25bc177e 0df70d14-9ade-4449-83eb-d6bb2437292d.rna_seq.chimeric.gdc_realn.bam e73be3afe5e3104eeadd908626c55c03 91055044 CPTAC-3 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Annotated Somatic Mutation WXS SomaticSniper Annotation 5366e648-391d-4eb9-8b2a-a21ef5dd6ef5 c62ca38f50518c33250269da8fa349da 1424737 +6ca286d2-6b1b-457d-b3bc-2ac82e22f234 7c5ae6df-cf3b-4f98-9d45-e728c58327bd.wxs.Pindel.aliquot.maf.gz 9bf634b5bf09394aeb8daba74e486ff3 674391 CPTAC-3 f223ac50-c620-46b6-a194-381e40e429a2 033ec902-7b53-4260-ba74-cc11cdd77e17,e7c86c73-63a8-4e75-b394-56dc2c0179ba Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 24fb1fd5-ddc0-4b51-a6d8-977f05fafb17 154f7a71c7da267a0981897b878fda6e 716913 +cce4e55f-b7cc-4626-ad6a-561a45b24bcb a4647500-8c5c-4024-8bb8-98a42401185e.wxs.SomaticSniper.somatic_annotation.vcf.gz e008b134ce239b27e132332f2f9be09d 294358 CPTAC-3 2e2659d5-540b-424b-aa0e-3389204a8b96 267e0dfc-7fad-4927-9713-c9930f88228e,57a37074-e98a-44e8-bd51-641dce6ec71a Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 11de9033-c8d0-42df-a1cf-ef61a2d6c29b c53447b2bf9dc120509f2efa5e422232 298602 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+592c03be-bbf0-424d-be99-ec85ff840739 6bb47cc1-33b8-4a32-acd9-f15efa81beae.wxs.aliquot_ensemble_masked.maf.gz 1ecb05d5873727f70cdf63411b83b9ae 20247 CPTAC-3 96ddb2ea-c179-46d2-9676-4fa88dba1d93 ea611a56-b305-4dcc-9d4b-620f7ff6410a,2754920b-81c5-4087-8d0a-3d4142cff7c4 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 342cbad9-c93c-401c-9984-887b6d665cf2 013ed50a7db5b20ca60837334c46259a 24353 +e9c67f67-a006-4317-abd8-15634c9f089b d01acc6e-cde3-4ba1-85fd-ebc6f442777d.wgs.BRASS.raw_structural_variation.bedpe.gz 6a556b55bdc21e1da3402eb59d6a0236 1555 CPTAC-3 8353437c-ec0a-4fca-b619-74e6c4e5b375 3993fcff-1eb7-4269-b65d-17692a77b538,277a56c0-5e19-4292-951f-6b10ac741447 Somatic Structural Variation Structural Rearrangement WGS BRASS bb76c5f9-2d81-44f5-84a1-2552cb5b84b3 f5bf184954c57cfd70887e00a6196777 4007 +30101e52-ba69-4641-8325-8816cc116eda d806a8cb-e989-4140-903d-f5579781f22a.wxs.VarScan2.somatic_annotation.vcf.gz 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Somatic Mutation WXS MuTect2 Annotation 8af55287-ae27-486f-b9c5-a5a4ab8b56cd 994aed254fa1bf53dc1dad8c249502f3 4779200 +ec105d75-c500-454a-8a19-b14a9914cbdf 64c1df5f-1c77-4f27-a823-03ab11c2a8f3.wxs.SomaticSniper.somatic_annotation.vcf.gz ec9a842a7031d1c49882232184896680 592704 CPTAC-3 68daae26-f752-43de-bf53-a0737e50d00e 6924323a-8bd8-4aa2-8a97-0c739132af78,cd161335-d26a-4e88-9cbf-412997314bc7 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 1a6f3abd-02e1-4668-bbc8-2140b021fdc4 3f4dc9f731e811e83b309b8f1095e4bd 622874 +70f90b3e-e00e-4969-af98-60327512caf3 9f018f29-d84e-4364-8ba5-4e5910ec699c.rna_seq.genomic.gdc_realn.bam 1da82a244e907f5bda5e983cb065ae8d 7826536290 CPTAC-3 8220be9e-ca4d-4a48-b48a-06c0b223700e f06b2a06-4874-418f-ac56-445c1553c9d2 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 42c2af11-e10e-42d3-bf27-20821f1ce962 efebd75a51a22d0f7d3f71c2dbd61d0a 7828047599 +3e918186-69a1-4178-a7f2-511c7c196c66 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Somatic Mutation WXS VarScan2 Annotation 23027033-cce5-4cac-b05c-ad703115a03b b2f5ec1a224f0e9f9bf15925200876e2 548609 +cca1b409-c541-47b2-8ece-6e1201626dcb fb520525-e9b8-479d-801e-706f26cff616.wxs.VarScan2.somatic_annotation.vcf.gz d22cd5e29670c6ed068f4ed85223347d 342779 CPTAC-3 59ee99cb-b820-4ae2-9306-105205f1bcb8 593a72ce-4932-42bd-b701-d62a7220ee4f,845737d4-d42e-46e9-bf0d-6679c70156c2 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 4c7852fc-c5c6-45ac-a76d-bc3d723c6c4f 291a3139fbd14feed83adef339a5c6cd 374380 +d4ab8ade-5518-405a-92c3-3f13099d17f3 ee7f796f-7744-41d5-b2b5-60ec61c44738.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 1272f46b-0d75-496b-8f06-cb659d9e22a7 7a57a25f-1d9d-4823-9731-805c24799fc7 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 1b21f8bc-fa80-4b6d-bc1a-8bf4c14a83db 6e5690795ff424264402ab9d2661b62b 229 +f85d95ef-78a0-454b-a2a6-76d2e9dcbd4b 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Mutation WXS VarScan2 Annotation 0497744c-d742-4226-a4a3-40a2abaa2d8a 699e427f73096ee71bbcd51537cdf575 137322 +c03e3393-e592-4b82-b8ec-7004a47f19bc 0cd4970a-28d6-43c0-82ba-b82f94406572.wxs.MuTect2.somatic_annotation.vcf.gz c2e872fcefb3b2578154a492a6da9014 3322781 CPTAC-3 e2ec60db-be44-4b4b-a519-6320231f7be9 c34fad46-4da8-4e0a-8b47-44c57040312b,fc028a4c-0e9f-44f7-9d44-d51bee5a66b7 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation cf9c43b4-0ccd-4f15-9897-c8f7f7359971 2a2b8ab56063ad5b39838d2f941a0ae3 3488927 +569298de-9475-4307-a2b3-456baf04c438 042ba1ec-e09b-417e-bf62-88816f823501.wgs.BRASS.raw_structural_variation.bedpe.gz 01e35de6175a96d752ffff2360db8d5c 1053 CPTAC-3 1afc3a78-4e91-485c-93e1-43f17738f530 8cf9a884-3e61-443f-8784-17e365f879cd,a0658f29-2a4f-43c0-8d17-e351ea2f073f Somatic Structural Variation Structural Rearrangement WGS BRASS 8678f551-126d-4541-a10e-afaa4ce7725d 7f3f4fba37fc82799af407c97f73a46e 2491 +077a0072-a59f-4694-9161-9c2547350700 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323b9495e4fccabecca43445becc1026 8092109 +a32f9964-29c2-4bc9-ad7f-315405dd9601 df8663ca-7d71-42b7-8a03-f7cac6568c91.rna_seq.chimeric.gdc_realn.bam bcd59b5633fe20cfbfae3ec443752f33 133397588 CPTAC-3 1e887511-098d-4cd6-818e-aa1087118d7c 4cd0a6f5-e248-4fe5-b25e-176afc6720f7 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b1d908b8-b684-4e52-9f06-b27f409f932a 5a1de12a6f9f56377ee361e4a82f6302 133399353 +edb15f32-1ed0-49ba-ac43-28dc834a38f6 33dd8eb8-5f6b-40de-80f6-72f207273182.star_fusion.rna_fusion.bedpe d76bfe8576288106b2839bbba83acb17 672 CPTAC-3 3ef779a0-457a-4045-b04c-191b734b81a4 83034426-0e21-4d1c-8ee8-372e0acd7eaf Structural Variation Transcript Fusion RNA-Seq STAR-Fusion fb44cee3-42e0-4be1-90a5-15cafdcb1300 a3a5afd62fa86b3745744354e30a5ce2 663 +eba69b71-989d-4595-8745-29ae33b52d8c a076997e-d2cf-425a-81fe-442ba6116ed2.wxs.aliquot_ensemble_masked.maf.gz cbd860607c59f576142d9f5e16bbcfa9 32739 CPTAC-3 8be8aafe-ccd7-437f-aa68-09c4bc248d1d 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Splice Junction Quantification RNA-Seq STAR - Counts 37b72afc-7249-4d35-95a8-5a2cbefe4dba 92ba81d2920d3c7ba9474953d4e94ae0 3232630 +5321be94-6187-4136-a6d7-13eae26a95ad 5bdd02d4-a0b7-450a-8097-3cb16153f091.wxs.VarScan2.aliquot.maf.gz 85caed82e807ec90aea8ece8be4def7e 162726 CPTAC-3 bb2f14a7-c52f-4a2b-8224-c747a3daa488 35d8f6b0-b20d-4676-bb76-9416d7a5bd11,e57bbda9-d5ab-49b3-a731-7b3050424f62 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation af3382c0-17f2-4571-b690-9b02da7fa527 cf93141b244a79b8411b9a2ccc6ef844 217629 +584b8afa-9148-4494-9c23-a2b7ded12209 dc576199-74d3-48d5-9adf-d459f9ed6c98.star_fusion.rna_fusion.bedpe 49f3e92be087b7f89bcb6a8fe5f5e527 2087 CPTAC-3 d61d80c3-aa2d-4d6d-9e88-ad1913d6ef2a 650c8c92-99e0-4002-97a4-6d287e02493e Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 0dc15a25-39d2-4b01-998c-770806c50ca4 6e5690795ff424264402ab9d2661b62b 229 +26f80d46-7783-4fa5-ae52-c50d4259ea5d 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RNA-Seq STAR-Fusion f3f376f0-a310-4f6c-ab3d-7684eb806a33 6e5690795ff424264402ab9d2661b62b 229 +2abb97c7-0b0f-4e5e-b380-d99dfa59fcfa cd8f3ba4-a08e-46ef-a474-b3afc614d154.wxs.MuTect2.aliquot.maf.gz 30cac41b57a85f521bc362f51896d3f5 3728461 CPTAC-3 55b590d7-fecf-422a-bc3f-51e118daf7a9 4d2cc1eb-ce1b-4e8c-ad2a-480c13132e7e,eb3473d6-b6f5-43ef-8950-2d1c236750ed Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation e178a1b0-2a0c-40f1-b434-27b04bc3c275 856c5f4bf063a41b14ec25970120fb75 5110714 +8b9980f5-ab27-4f92-9755-7145f0166f86 cbdd0de2-aa21-47e8-b052-b84f5764e9b3.rna_seq.genomic.gdc_realn.bam 28439699b01c3258a6387f24528beec0 8107780482 CPTAC-3 2e653fba-5d9b-446f-af7f-a986e39ed713 d08d339d-97c4-4ced-b844-de117453286a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a189b183-f0f2-4558-8f01-da60a44231f1 986791f8e3ad8c63a181bbcf6cfdd4c2 8108963815 +87976e2f-ef43-4d1c-ae72-549736f1e3d7 ef79894c-d730-477e-ac8c-f5d1e9936247.rna_seq.star_splice_junctions.tsv.gz 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Somatic Mutation WXS SomaticSniper Annotation e5b172c9-cdb8-43ea-b065-e7d5a3de6e2c 1298f948cfbb2a616ca10587231090ee 722852 +ecfbcd73-78d7-464f-a3a2-6794f7f9dd86 4f8fe744-db04-4e0c-ab4c-f64f66a093e2.wxs.aliquot_ensemble_raw.maf.gz e174fc7e4f9867190db0aa38f20de7c0 233242 CPTAC-3 57b28192-8454-4ec2-914e-9228456d8648 f6488f85-101a-4703-af6d-d7a024f8294f,80e3b7fb-78b0-4ea8-9792-264a50cab826 Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 0b63da7c-fbaf-40b7-aca8-3537dc59857f a1ef96d84d869b983f0952fe496cf2b7 289544 +62bd2b3a-9147-4668-b2f5-e95c8be9b3cc 3ec5b000-1a65-48c1-af01-47c7427c2eac.wgs.BRASS.raw_structural_variation.bedpe.gz 6d669985415751a9dc078778d1d36ac9 8035 CPTAC-3 c954ffd0-f64f-4cee-a802-48e0960f7910 6e1356e3-0fdb-49b2-b2b9-b40c87cc3ba4,61c4ce19-1344-4ae6-be82-de54cc998174 Somatic Structural Variation Structural Rearrangement WGS BRASS a6a1377d-cfb4-4c5b-b809-4a1438e67034 da1f85a6708bf96c1387d3fb6c096a52 27611 +74de7880-4a6e-4e1f-bc09-883ca80efb7d 6ed60683-7df4-41ef-ab83-72163429c0ce.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 c43e357e-8156-4999-8972-d6c007a88033 3d27b10e-725b-47a4-b11e-99a198afc496 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 5eefe436-f168-4a58-8b8d-7ceae0d11e62 6e5690795ff424264402ab9d2661b62b 229 +c55a8c97-b189-4ec7-82f2-b30c0a70ad75 d4b8fbae-759d-4d11-a8d6-c1a4dd860808.wxs.Pindel.somatic_annotation.vcf.gz e06c8c26fdfd147f31bd3b3ae66a1a1b 776052 CPTAC-3 983d95f3-1e50-4bf6-beeb-8b9ddd65181d 9a2dfd9e-6dd6-47a2-8e80-d48625d4e780,cec2f45d-c155-483f-97df-221ca574f6b9 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 1c5aa99d-4458-445e-bd08-c8d3403b7b40 2ef4962033c14f79e30c202d8790096b 791890 +e20e2949-9742-4f42-bc85-6314308cb042 14c90289-40b9-4b1c-9809-8f32e3655c9c.rna_seq.star_splice_junctions.tsv.gz 9010e20f1076bff1acb69a2ad9dd6372 2951116 CPTAC-3 e8d31ee4-804b-4557-a70c-9e6df8e25606 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425c32f8-8376-440c-9f44-e53deebcf65c,61b7727d-fa5b-4787-8df0-c1c0e0662f06 Copy Number Variation Gene Level Copy Number WGS AscatNGS e576eacd-3908-4663-8a82-3dc38793d022 7bc35a4f3b845af9a4079e1b9091f849 3443293 +9285c013-4943-4031-a5a4-8e488a1cc121 6fa9ce25-a03c-4a0b-ba4f-4f3734d98117.rna_seq.star_splice_junctions.tsv.gz 26910984c2194f71e523452b2263f264 3245370 CPTAC-3 f8614e58-809d-4496-a54e-8f1a1303c202 1f2c18d6-50d1-478d-abb5-9bfbe8b7626c Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f2e5f95a-84ea-4ada-a34d-b5bc77d1580b 2dd97e4c9d960f8c3ab0175cb2ec5a3e 3281451 +4d4bc2e1-1976-48d9-b51b-8fbcc9c1f91d c5a1c7b3-83b3-499d-98a2-c483f6eada7b.wgs.ASCAT.gene_level.copy_number_variation.tsv 2167993a800fb6cf2a4d2882143a0d03 3481183 CPTAC-3 763e0702-8379-4b5e-95d1-a84f412c51e7 c0292a50-51ae-4818-ba05-3d2a9534cf2b,bbc3e5fa-d872-4922-912a-bfc9acdb58bb Copy Number Variation Gene Level Copy Number WGS AscatNGS 0c477f5a-c29e-48c0-bcda-643b737c47e3 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d621aff7-2313-4cf3-b903-47e3694c13e5,fcd2143a-2187-492c-95fc-c6d971f11153 Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking c3d317fb-1f99-4b02-bb1c-d1fed9e5f663 b1d4d36bf9c29bfc508e4fff40d9b3b4 229283 +8cf12399-f75c-4579-972b-512342cfbef7 da08dc05-c9e9-4366-a3ed-82132299542e.wgs.BRASS.raw_structural_variation.bedpe.gz 5d618fc723c1293b811d0726951c5936 2940 CPTAC-3 715c5c66-2948-4eaa-9071-cd2150a7f6f8 11ba5a36-4f9f-4190-b5d3-0fce329153e2,a86d49fd-960f-4d9b-8a34-b865c7c18601 Somatic Structural Variation Structural Rearrangement WGS BRASS d196a968-aa10-45c8-b00b-a8ab3ba3ea60 8100f9fd6766db3ed90c743ba4b45957 8905 +1a1c9839-2fdd-4d0f-8397-8c2e720b9162 e3b562c1-4270-4b33-b8f4-6d1bf138fd59.rna_seq.chimeric.gdc_realn.bam c48842d4e98c2c52d38c47e123233d07 223417621 CPTAC-3 d2ba6170-58a2-424f-974d-403af8f2f6e5 b74acaa4-369f-4a1b-847e-a293ceaaa880 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 320ccd76-7a11-4833-aae9-935b6550fa76 fda7578afbc2318e0ea87a414eb400d4 223401662 +fa65181c-eeb9-4f7a-8a5a-2ae7c2251ecf cb31907f-5c8e-44e6-995e-ac2e1ee72dd0.rna_seq.transcriptome.gdc_realn.bam 8706d8eade66be378dbc484141069a76 9251255296 CPTAC-3 10547ce0-4d20-406f-90e2-88dc483fe81f 2a9f4bf8-04c1-4045-9d04-1ba3e5a4261a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 7e793277-30a7-4d71-8a13-cf84a29ff7dd 1aa6b183c55ea5291ffec23b1d8b40c7 10695617534 +45593229-c37d-4530-8098-4189ac48d1c1 a06f06ea-d961-48cc-a24d-71f1be6a0b46.wgs.BRASS.raw_structural_variation.bedpe.gz 32c1c08363c28a7cc62c724db4c149ce 1099 CPTAC-3 c0e5c699-9195-4312-9fa5-bac797bf7809 d76dbd49-7705-404a-a526-36c29dc4b2e5,4ae4f34f-1fdd-46ce-8b23-e7558b3f2a92 Somatic Structural Variation Structural Rearrangement WGS BRASS 23b8a9c3-dc4d-4374-bec9-a26383892235 0a7cda013b26776b73953e56753ff458 2497 +c09cd938-bbed-4564-8aab-fa34bd9b8a83 6b907109-c2b3-4a9d-be06-4569a2c97925.wgs.BRASS.raw_structural_variation.bedpe.gz 29b0955c6d928c5d7016b9e1d8fc21f0 2738 CPTAC-3 25863969-852d-408e-bd62-98e0df9e4b3a e15b8449-51aa-4dae-b6a2-091f1ce010ef,c29ed504-d297-4fc3-ad09-200319492ed4 Somatic Structural Variation Structural Rearrangement WGS BRASS 0c1f0eea-4384-4d85-8ad8-b53364cbe675 f2a9942a6a0e32db6cae52b8d2a5f11f 8651 +4e6c7248-c45a-40b9-9b28-e3a68eb43b0d 46f577f4-b83b-4acb-8cc7-1153fadf317e.wxs.MuSE.aliquot.maf.gz 54f26e9005b3f35648effaac59b9e99f 226846 CPTAC-3 579139e1-e8f9-4260-baf1-dbe7435c8aff 685d5364-aae3-4291-8104-7f616deea3ef,3bd3461d-938c-44f1-96d1-232f0174c7cf Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 3cce0285-5353-4468-b556-95067761d512 943bedb6c2e10dba1424478937425146 263406 +4723eb02-5217-432f-aa66-d36150e57550 35258f87-a335-4c62-b90f-f8f01cd39ba1.wxs.aliquot_ensemble_masked.maf.gz b6e75595b9fa9a33a305576843e24d4d 318644 CPTAC-3 0b5c15c0-6481-4906-b586-8ffb394befd1 777ac78e-f376-43e8-833c-3f1706ff74b8,a0d54515-7b4c-476e-8f0a-1bc4c22acd39 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 20a7107b-187e-4141-b132-278e79f958fd 5104387582a3b4046d2af5c83cd1eb73 389667 +ae0f7b8a-3bae-4b54-9ae0-dabb33cfe581 b4908770-0353-4715-81d3-61c8ce4278b2.wxs.SomaticSniper.aliquot.maf.gz 334774d95b639174094b80579543e7d8 1051908 CPTAC-3 2bdac74b-c588-4697-8d91-705456d205fe e6268f9c-fd73-4163-8824-eca1dab52d32,df67cd41-eab5-4d3c-9224-393ac1f0f0f2 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 1c8c719f-b55f-4d6c-a58b-4f0bc1fa3a18 9bb872e5dd6088c4490e413777d59e49 1272599 +597ad657-8253-4b27-82a2-7107ed3ff7a3 4af05c5a-74d1-475c-8509-f7450ce9d672.wxs.aliquot_ensemble_masked.maf.gz 4371b01806bef71132cb37a1e37636cf 25452 CPTAC-3 3a58efbf-2708-4f13-87ab-253d7d67ef52 89c71c22-206b-4f62-b69e-093b180053e2,05e1c388-5dbe-44bd-8309-474ce6854f2a Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 36015aa0-ffd6-4127-8fce-3e30d2392a4b 111a0ef36a4d701e0c8ee308f9056225 34273 +b1b9930d-d165-4bfd-b397-20d49c03921b 0209003e-2a15-48e7-bcd3-5ec3431db887.rna_seq.chimeric.gdc_realn.bam dd878bb0e432778736b9a5d918a6818d 46669317 CPTAC-3 c4879830-e0fe-4862-92f2-bae29f58fa47 d1818c36-854f-4699-b0a0-724a4f391245 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ae68238d-e804-422d-95a3-ccab5ba740f5 3d48d34af5404385022aa0669a1aa3c1 46658204 +4d797a95-bbfa-4798-b594-3819822c2a8b 2153b0c8-f9a0-4c5c-b2be-4674dff93a1a.rna_seq.genomic.gdc_realn.bam 042956b667013bb0c2dc5bc87b9165df 8663426819 CPTAC-3 81d68662-e30b-48fd-b659-e991a3119445 47cbc7a6-d354-483d-a044-5a02bdb74cf4 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome b1998b06-6644-48ea-a9b3-6764c107107b 2fd8890f9975c26a9f4c4eeb1f24a1e4 8665657351 +08c4eae8-825d-4407-a4e4-b0efadfa99f8 4de4cfd7-275c-49e5-adaf-aa42eb40a008.arriba.rna_fusion.bedpe b64ce8a7b3a5658d5e54a964441a7df9 1174 CPTAC-3 68daae26-f752-43de-bf53-a0737e50d00e 952d3262-f49b-4361-9f32-697c75935506 Structural Variation Transcript Fusion RNA-Seq Arriba ec1b135a-abf7-4164-ac18-a184bf6c8062 7418e5140dd133736526fab2ab28b454 1173 +8405524e-836e-4ba6-a47f-3c973ca46e2d 9afbb12d-0694-4974-9e4a-25ab2fa3d008.wxs.VarScan2.somatic_annotation.vcf.gz f77194111bb4cad0e5ba960d171bdaa8 1368698 CPTAC-3 8710ce04-6b7f-4e37-adc0-0df1f2798b30 d75c8fba-a99e-4930-b9fe-514d1e6db377,8e390124-ff80-417f-b8c3-a611f6e4fcbe Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 3efa81e5-b5b5-46b3-93e4-ac6bf06ea370 9c95acbebef60cdf7e6110055e2e0cff 1474230 +899c2fdd-012e-48e3-902e-e10df0757185 0460879d-44d0-420d-9e3a-641a0c7820d2.wxs.aliquot_ensemble_masked.maf.gz b42d9a15ddcf55fa1060a127eaad0459 19218 CPTAC-3 d2ba6170-58a2-424f-974d-403af8f2f6e5 42e07145-2697-49bc-b54a-a0b8d6252b63,93bfb3d4-6285-4819-b54b-96c9994f54d4 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 293ead28-42ec-44b5-a771-3e447ccb1d0b 485718cff108fd7c0bccfae82a5dc103 24080 +0beb252b-5e31-4514-9ef5-dce4e6c07d0a 8d9cecb7-aa42-42af-8371-e3d7abc4aeec.wxs.Pindel.aliquot.maf.gz c7ecfbc61185ec23d93e308c440a98fd 22522 CPTAC-3 8bbe311a-bcb7-409c-9bf4-999ee9c3416b 1b6a186d-ab81-4f64-9195-de05919416c5,4d3b3837-9e79-472a-addf-9f37a7e0deeb Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 783b8b73-5d98-4b34-9f6d-f6930fabd0fd 9cf4ee281f6694e2cfc77ba4109ec323 25419 +fa7fb2de-1cfe-4f93-b493-b34973820a80 aca76809-73e1-4f49-9f5c-0d03ff5888e3.arriba.rna_fusion.bedpe c8d0ccea78d09b8ce917ce3f946a59a8 2674 CPTAC-3 d3c23e4c-b635-4416-b026-368b82fb1883 284507b5-32e7-4e2a-ba74-07d3ec53a487 Structural Variation Transcript Fusion RNA-Seq Arriba ecda3771-5e22-46be-9244-9981c2a953f5 c990470025860291cd00aeb1c126c131 1726 +90929e86-3951-4825-8b62-7d251ec5f19f 6c4b22b4-1255-44a1-a14d-28cb47b7fdce.rna_seq.chimeric.gdc_realn.bam 0d805c6256bdb143e203bff6044962ff 61628764 CPTAC-3 aec84142-419a-45c2-8aff-dfeec5065447 96e347cf-b5c6-46af-a8c6-8ffc8cb0288e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 04200873-03c3-482f-b737-a2701fdc6561 2d21053528fb9290e7d442837b8e9d81 61593527 +3893539a-5d11-482c-9405-7c84a09cd0e7 16abc828-c334-4ed2-b805-6f7b41420515.wxs.SomaticSniper.aliquot.maf.gz 7da089fffc8e330666fde09b45143b54 291309 CPTAC-3 8bbe311a-bcb7-409c-9bf4-999ee9c3416b 1b6a186d-ab81-4f64-9195-de05919416c5,4d3b3837-9e79-472a-addf-9f37a7e0deeb Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 50e46820-78bb-4488-b761-02f5ab2f610d c167834517e95bb0b7e5fe053d07097b 380229 +dd5359f7-ff6e-4ca6-b883-9635006a7f85 7a6ad782-f84a-4fbd-826b-7f755a23b92c.wxs.MuTect2.somatic_annotation.vcf.gz 8587f39c6f43490719ad423a2401a03d 9528314 CPTAC-3 c273a592-f1e0-4d30-a373-afa880533a65 49ca41e9-c06a-4b28-8420-6ac7dcc8dcbc,5f6180da-9f43-41a4-ac5b-816dd3297285 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 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Variation Annotated Somatic Mutation WXS MuSE Annotation 4560d0f0-3989-4bba-92f9-cef5eec92634 ef37890ea6d71b8944df268b1008a199 227063 +f72b9da9-9853-4c37-82fd-e99cf44514d4 057d49be-0d96-4a77-863d-ddf44cc46ae8.rna_seq.chimeric.gdc_realn.bam 13bb2c2f0c18c0a4c0e67049e5ddd914 173196406 CPTAC-3 d86c3d4a-861b-4211-9bcd-c9669fcc480b d55af09e-b76d-4dfb-be95-b77afa6083c5 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric fd684963-2daf-42c9-be62-f01de81d73e8 422e14cf5d9765d1949f00ab8d9c39e7 173147188 +d070aa90-79e9-4777-b5a0-a4e379b0431f 0d23d839-4880-47cc-952b-a38967844d07.rna_seq.chimeric.gdc_realn.bam 4e58f139525e063d6a009ca5585ea35a 204736145 CPTAC-3 6e5e5bb1-b76d-42f6-bd2b-c2f325d79122 d624b662-0c8b-46ab-9648-30e6e55c6bfb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 8cffda36-8d58-4f14-bf5f-3061c8efb967 c1e3c2688c6d6f46a653852528921479 204715848 +7065e93b-e660-4150-9cc0-e7dd38ef0cef f05931e3-4b04-48c4-aa93-6e8fb9f83dbc.rna_seq.star_splice_junctions.tsv.gz 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Annotated Somatic Mutation WXS VarScan2 Annotation f81d59a7-e3c1-40c0-a98e-a1bc0d1e0469 75ab58421b7af0bebc9d4e3d2cdb81d4 490379 +b4085f10-a6ff-4f78-a725-a6244eb07d80 0d1e2fdc-6246-4c05-a4af-967e338acec6.rna_seq.chimeric.gdc_realn.bam 68c809b2a93daf4942a01215d4492495 49385665 CPTAC-3 f5287051-d58d-4243-8a07-5fdfb5afa301 d7481d68-fcff-4ec1-a2d5-1c837aada39a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 9e78092c-adea-46cc-97ee-14f67043faed 510701c2d7d05c76a187371623036b6c 49364752 +ea9d5f4e-7fe0-4af1-829a-302924adffc9 75d70803-bab7-4191-a1ac-f722040a87a9.rna_seq.genomic.gdc_realn.bam 6ce07686776a9306b4adc32dad1b47b9 9576145439 CPTAC-3 ce1ca93c-73f2-43e8-a060-c0a6f975203d 8d551311-fc57-4c86-ab75-513812df5f04 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome f10b1d62-2705-4fd3-94af-d9f998434325 54bb1cc024670bfb8e950e88845fd645 9576947026 +f527fb5c-e7e6-433a-8796-e1c0075d7e70 4d070fec-0bc1-481c-b108-51ca8344f5bd.wxs.SomaticSniper.somatic_annotation.vcf.gz 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Reads Aligned Reads RNA-Seq STAR 2-Pass Genome b8db8e03-ac7a-42ef-bde5-4f7bacabb567 bd1695c02e4249e0dae2e74a17d17c29 7753794291 +7bc783c3-c516-4df4-a522-0346378744e9 7f6fa1a7-049c-41b0-b212-848a00cab02f.rna_seq.transcriptome.gdc_realn.bam 1c6f093f810ff2673cb402a4d50e9931 9974519938 CPTAC-3 2219ac15-3505-4a31-bf22-72f17c670f3e ef936a66-c615-40f8-a453-5a9fd3a6c66a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 32d2bb16-2140-4029-8493-a0d242799189 12d1dc6089222dbf6a1ee2cdcd2db988 11360843616 +54543ef4-cec7-4555-a5d6-487a3f8a01c0 7950f03a-3905-4b57-8c83-2a49925d01bb.wxs.SomaticSniper.aliquot.maf.gz b68c0d7d69391b4a329a6a8196102793 278713 CPTAC-3 1f370a2d-7fbd-4fa5-8bb8-bdaa94c1ba9f 1bce2290-d038-47b2-92ac-a20cfc946a0f,ddd24fc1-29d9-4388-9e4f-df69a9ba3818 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 7de446ae-0348-462d-9a52-3711fe2d913d 275ed14fe5c412a835b2a83a95ae513e 350958 +e8e41cfc-b37a-48c2-bf08-1c909230dac1 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Mutation WXS MuTect2 Annotation 15aa1a9d-ef49-4f12-9801-b54328349f06 9515d5979f33453cca121485d2e3b82d 3234362 +37d01578-960c-40ce-b793-54780c35bba0 0c348081-4923-46e7-8a31-6fed88a0a79b.wxs.VarScan2.aliquot.maf.gz 975316251f68efdd2d09c0b6fe959d04 328585 CPTAC-3 ec5802af-a27e-42b2-afe5-c6378d78c997 b4dc9536-147b-46cf-b704-dc9244cb3980,300522b0-ac2f-4ec7-a5ae-cd55519df19c Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation c4506ec8-f76c-4dba-a702-5922c458e48c fdca9cd63f98fab109ecb54d4918c733 403727 +81f7e58a-54f8-4f92-99a7-fd468b5b3744 0878cef4-98b9-4df9-853f-0be38deb2d53.wxs.MuTect2.aliquot.maf.gz 88a4b9dcb0f836c0641da6efb4f3ffd1 4899225 CPTAC-3 761cab85-b6f0-474c-b6ee-ddcd6e36a425 309ea7b2-acb9-483e-b522-14e1bcc1518f,f5b3f122-436a-45d1-bb80-ee76ceaf7d48 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation e995b28f-0ba5-4d02-b431-29430dd93765 8d8a49a2370eeee8285ed8b0b50bbdce 6025106 +e8b6c424-f56f-4dfb-a908-c1a4c5292a67 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Annotation bb419edd-0834-49fc-be51-17d99061a54a 9d029d5e996a5685b8034dadf2e53f67 454744 +c4b9d5e4-45f5-4e93-85eb-1cf3b9262e65 b018dfdc-2137-4c34-b4bf-05cd7ab27e2c.rna_seq.star_splice_junctions.tsv.gz 53df452aa4c04136db9e66fe8207eac0 3657476 CPTAC-3 805792e9-858e-4e9e-84cf-3578f7470889 552cc1f8-5fa6-42b9-86e2-f175ecb1aac7 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 4f1dfdcf-d157-4cbb-8a15-0102877a2abb db6e3b31b8f41f358d465c7b7eeaefca 3700421 +83bad7dd-20bf-4202-9aae-b048c6be263a 76dee45a-6193-4811-b224-6b3bb37db946.rna_seq.star_splice_junctions.tsv.gz 8efb571a6726417c1ea93cebd4a27eed 3280080 CPTAC-3 ed9c82fb-ed4d-4254-a078-20a34cf82283 e6b6728a-f563-4926-b61d-f68ac7450ff3 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 00dff6ad-64e1-4ec9-ba6e-b2095b887d51 21179dd662d523997daa865b94f7e091 3324530 +ecff465b-ad3f-4a42-a457-9be9d24b1e75 dc882f60-e559-4dc0-aba9-ec523d4ea173.wxs.MuTect2.aliquot.maf.gz 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Variant Merging and Masking c6971967-6b3e-4c68-9d5a-1de28fd8166e 1705892db582558e67a1042952c75891 107186 +b714a6c9-671d-4a6f-9e6b-9fa0fdb83918 1c160290-aad3-4da4-a0a3-f9904af6374b.wxs.aliquot_ensemble_masked.maf.gz 04d42e38736b036ed345133947d9b5dd 17199 CPTAC-3 410b95b4-6d38-4c25-91ad-c09f2c34325b d47d42c5-c6c1-4788-b66f-9e4eb2854c67,abd00977-e5b2-4ea2-9840-a0cbcc03e13c Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking b5a42175-f481-4dc5-abae-8bc11f373dc3 8cd7ba1bcaaf0e4c01033678a5770bf5 20273 +e26c7262-ea17-4615-9402-9b6c0e9f41a0 88bcc0e0-cace-4364-a62b-297596274401.rna_seq.star_gene_counts.tsv.gz a5c9b84eced55e657ebcd6bfc4572acb 418742 CPTAC-3 3d4e2776-4e38-42bf-b3b7-5c15b5a9a201 7ef9601d-289f-47bf-9c03-a85cfd6627a4 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts e7d80d32-1d9d-4cad-9688-a2be3b5898e1 d830ef21b4ebb008197a90fc3cb1465a 4232368 +e75748d7-3a23-4659-a88f-75bfdbe1b9d1 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CPTAC-3 c0607363-1082-4ce9-a642-e9b2b903ae88 20730bb0-a420-4cc3-91ea-80c765ccd3cf,b56bd2bb-ba83-4a80-835e-1c42b477fb0a Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking e4233f89-5f64-4dc1-b994-239a22b1349c eed7c4cca1bb3b24215077b1c0f425e6 3112526 +1f899051-054b-4226-8d77-3e55612225b5 d101eddd-ad00-4a42-9a95-ece5bd2332a2.wgs.BRASS.raw_structural_variation.bedpe.gz 76c5c9ce06f4a8f932bd6ceaa80a63fe 13702 CPTAC-3 3a58efbf-2708-4f13-87ab-253d7d67ef52 89c71c22-206b-4f62-b69e-093b180053e2,05e1c388-5dbe-44bd-8309-474ce6854f2a Somatic Structural Variation Structural Rearrangement WGS BRASS 25d7308b-cbbc-4b34-9c8e-24fe64b7928b 59804bb9e161d16b240be1458c0ceec7 50756 +76c33c71-4cee-4f99-b648-e53c2aca9c36 513bfb22-98ed-4f63-aa69-46273695313e.wxs.MuTect2.aliquot.maf.gz a2de8e965a4191995769fefd4bbff3ec 6663815 CPTAC-3 f4a6f999-60a3-40e3-858b-6e7aa1738c3a 1835754d-479f-4784-9083-921104cb7a68,5af7cd9f-e8dd-49af-ac6a-6badeed9fd8d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 6d35903c-4733-43e5-9f50-340d0630551f bca88442f4d593c02bb19f4c1e589233 8213798 +7be0cddd-bb5c-4707-a2cd-7f5cc94a4af2 dc6f45cf-3fd0-463e-8611-4d8b962e5309.wxs.aliquot_ensemble_raw.maf.gz b4d9f5b03cc0c801ff0e21849f183600 153663 CPTAC-3 832d8529-0cb1-427d-a613-adb7cb8f33bc 061cfc9d-8a34-4f3a-a9e8-c5d5720a4e35,5f0475ea-0fad-44a4-a58b-24fe7c42a5db Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 32807d97-6770-4271-b59c-f93e05513840 56e20908b930c01514fed00c8fb5add7 215594 +5f36da57-727a-4187-ad00-a86fe32b8b11 c409ea8b-c7f9-4eab-9cb1-72ef1c06704f.rna_seq.star_gene_counts.tsv.gz 5d9a4056ac361783e70d90ae950b5530 419259 CPTAC-3 fd2ff719-f1d6-43d1-a7b3-8e4e67da89ee 5399457f-af35-4a63-b286-cb9d6253a0bf Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7591edea-ffb0-4d69-a2c8-2dd1d8e4a9ae 6abeeac9974a7852b4eb2f224c208ac0 4233437 +3119dfea-181b-4b26-b84e-cc22cb836e55 322c17a7-242d-49e3-a6c6-b465f98806c5.wxs.MuSE.aliquot.maf.gz 8f2f5198216c4be178e56e710adbd84b 100068 CPTAC-3 ba037761-7166-40e1-8f27-1c1561a18b9c 425c32f8-8376-440c-9f44-e53deebcf65c,61b7727d-fa5b-4787-8df0-c1c0e0662f06 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 8a27d2a5-89a9-484c-8c91-035244b5a777 cb59dd0ba25bf4225ec63ce05555470f 117831 +c6014153-d89e-4ec6-8ee9-f557fc7876b1 c187993f-0c59-4d13-af02-2c21327dde04.rna_seq.genomic.gdc_realn.bam 4616629a0cb490b7eae28deda574fef3 10052090807 CPTAC-3 d2f97b9f-30fc-48cf-8120-e7d1d3c4f71f 5fffd144-574e-454e-abe3-b73e2514c048 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome eb2035e0-7aeb-420d-8a25-0f94ca80bce3 010d10bae578eba36319447f3a67ee05 10053463791 +90c82446-f5ef-4829-819c-5c6be6c30d1b 24d5d4c0-1770-4369-8062-1553358b34db.wxs.MuSE.aliquot.maf.gz 0b2ebb91fdb5ba9466e96b9824af0bad 124061 CPTAC-3 cf806878-386b-4416-a840-96d104ecb123 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0f2a1807201e8525c84b7b1ef494c867 286139 +8c7860cf-c1fb-41c2-acfd-1e2683b51749 a20377bc-c3c0-4079-b1b0-c3d47d76c583.star_fusion.rna_fusion.bedpe 5b5e15aaed175a31aa70b6bbf7f3d07b 456 CPTAC-3 126507c3-c0d7-41fb-9093-7deed5baf431 02eb896a-7db9-4cf5-a8f4-b685afe026df Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 7fe52b9e-dd04-474b-b749-8451a1d58669 6e5690795ff424264402ab9d2661b62b 229 +82db1ca8-2415-444e-a5ad-497e584d0209 b13b944c-cbb8-4400-8e6c-4ebdeac56021.rna_seq.star_splice_junctions.tsv.gz d60d5a2d2a3c813e032630473f009b99 3421451 CPTAC-3 b914a2f6-5b6c-4d76-ae72-c73b9f27fd10 49f12657-2d1f-4314-995d-9bc42c8709cd Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 53ae2a06-2fa4-4f05-93a6-5f36c4e83247 8054e3d1ea78b81bade19c9a5fa386db 3463720 +1a5b5ad0-05f3-4292-af67-c1fd39b877a0 3adefeae-8c71-47a0-a9d5-3d0005aa0ef4.wgs.BRASS.raw_structural_variation.bedpe.gz a1b22d92df5a606547cff2d25be8f587 27956 CPTAC-3 8b0ed6bd-7eea-4a99-b901-a0a8a858d97a e50eb6e0-6790-44d4-a6e8-6f9f4f561ee2,030a80ff-6a29-4599-b87a-c0811c028057 Somatic Structural Variation Structural Rearrangement WGS BRASS 8342ca19-9b8a-43fe-b83b-2282493145c7 511261b15ac0671a4b7aa0ed317a189f 104138 +dec8a230-263b-4089-b76e-df75d019f6db 98b2ae47-0353-4729-bdd3-b4562841aa50.rna_seq.star_gene_counts.tsv.gz 0862725b571ca66c1d17a58b6bb5c6e3 424548 CPTAC-3 6c28fff9-68e9-465f-bebb-7574901e333c b5086f1b-67ac-47ec-8d66-ecfed8b01e75 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts f0a095e0-ecda-44a9-8126-e1cd9c0a7b93 c43b34d7028ea0bf3880a9ba059f5e9e 4237832 +786153f4-8cda-4602-ad98-432041add960 061402ae-51ca-4b5e-b9e5-914be66b9100.wxs.SomaticSniper.aliquot.maf.gz 8b927760d2586e32e91e944990a679d3 2130288 CPTAC-3 54803fe4-6b87-4a4d-bb22-de20342e8929 d621aff7-2313-4cf3-b903-47e3694c13e5,fcd2143a-2187-492c-95fc-c6d971f11153 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 132d2e63-6c01-4aa6-a967-508cab782fbd 26e6fa5bc76a7cfcd1ad81880b3d37f9 2597787 +b595a556-dc46-4eb7-994b-7c377655839c 2c60499c-a0a5-4cb2-9db8-57d16f23e441.arriba.rna_fusion.bedpe 0a437d5e4f015ea6ca2479b9754b775f 1562 CPTAC-3 a25d1047-ac0f-40db-b6aa-c6f219eb48da fd1884ab-888d-4545-bc62-888642b4ad29 Structural Variation Transcript Fusion RNA-Seq Arriba 50f4f961-519f-4f18-b6bd-ad3ac3f56dce d629190f524058feded07e3932cea8db 1182 +f808bdb6-8e02-4d40-a7a8-ec5a03c0ec2c 12a81952-6965-4fbe-bde0-edd2e8960823.wxs.VarScan2.aliquot.maf.gz 0d6e9d312fcb5b00596cfb22ec14bfdd 111271 CPTAC-3 eac6ceca-d905-4a4d-ae89-ea533370aea8 999b4985-3f54-41a7-bdd3-8ecf55ba1669,ecb04ff6-c2a9-4dd2-a7ad-4003f7602332 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 62e4c712-8d9a-4f6b-bf9b-75b8f9c9fb1f fc9493c19f7117114e101c289c7f21ea 140089 +e38683f9-2b39-47f4-b9f1-22c0e506298c 01050f5c-6e5b-460e-8e0b-13c56781f725.wxs.VarScan2.aliquot.maf.gz 2d59ca803d03e1f10ffbd4660800df92 1435809 CPTAC-3 32b8c7c3-0a0d-4d93-b765-dedeb74b537d 27358361-30f1-497e-aec1-95d130c16820,360ce993-b06e-488c-8d6b-645b93688df0 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 25a8d927-4abe-448c-8539-cc091886a7de 34072e9937f8575a66172c815510e8ce 1682848 +b931f1a3-f333-41d5-bc77-7bd53a98dd4a 7a103500-7eb7-4c8c-8cc1-795bf8904215.wxs.aliquot_ensemble_masked.maf.gz 8c9b754f15e2c3954f248abf49e9cf95 75452 CPTAC-3 e1f35725-da71-42cf-b05e-fac2296d4d6a 42bb41e3-aee2-4728-8bb6-2b80fd76c3fd,a807633b-a292-40f9-870b-b6b9bffeac1f Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking e02f8198-e6a9-4ad5-ba2a-b59635f70c23 4bb4d5e2c8f4ec87571cbd19c85807a6 94200 +019b8e47-5d6f-4b7b-91e3-de437c819666 760802eb-d314-4d7a-96b2-c98da03cf6a9.rna_seq.chimeric.gdc_realn.bam 1eb8db17a467c4793e15796d67a07d19 40159663 CPTAC-3 3302fb9a-3122-449d-b718-74769aee97af ed82f2d1-eec1-4b9c-b734-bbdd0269b5c2 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e2497a1b-9ce0-437a-af72-5931bf3365a0 fd59a502b286a5cc1ed424af706a0e0d 40154720 +0b46ad87-fac4-4ba9-81df-ebb247c494a3 22f5b2f6-b445-4568-ae5c-e88da5c2c009.wxs.MuTect2.aliquot.maf.gz 5432dbfe0193ad47bb9dd8030ee80213 3979203 CPTAC-3 de1701fa-ca4c-4104-b8e2-ca3c10bf516e 6909d633-6f16-4a7d-8c32-e336c7aac09c,1e3bbe99-f650-4ccf-ae6c-b3808b778c5e Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 2aa1cb43-d785-45b7-b1e5-b0d01163a6b1 55f615d301317d4d74e0e8f8a1005d05 4954665 +8f59d3e4-56d3-4bd4-965f-bdbd04749e4c cd4d3f72-bb74-4b13-a118-c9fec6c7581d.wxs.MuTect2.aliquot.maf.gz c42fe91e079766b729e8eb041169c460 3155609 CPTAC-3 ed9c82fb-ed4d-4254-a078-20a34cf82283 91d5eca6-731f-4bf2-9e06-c0985c9a7d05,403a82f6-1996-4dc4-807e-60dfeb23d36c Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 95e907d1-2c03-4561-8ee1-8c1ba58e667a 7356f4a8aa55251c5b3fac060a370c5b 3557371 +90e0384a-4c54-4efd-a3f1-0ead92a305cd 9af4f4e1-24b2-4535-9d73-323d1f6cca8b.rna_seq.chimeric.gdc_realn.bam 991a82b2071ff293599ec88775682eb9 341145751 CPTAC-3 1dcf0d2d-d119-4654-a7b7-28d1eac23772 6809cfbd-961f-4c61-8ef8-ba373224d3fd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 8aac3009-a874-4044-b78c-a6bb1d525df5 353ddfd216ae738982843ba920c23582 341112205 +21b5f7d3-d053-4ac4-91e2-48147ed31ba8 582ae08f-09e6-46e2-94d5-b5ef4a9d14b2.wxs.Pindel.somatic_annotation.vcf.gz 6e9d8ae6c1bd6710a58ca2c02ee60bd8 72813 CPTAC-3 82cb0e8b-584d-422f-a00d-81dc5892c406 d65d3c63-2d38-4f5d-bc55-24ecea87bd4a,0a1ff17e-ea71-4c3f-93dc-61f1e4a527a4 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation c2d97e04-6bd1-48d1-a89c-6179988466c2 db841f9451a8c8d9293c017b90151b5f 72928 +62cdd803-7944-4d52-88de-ca81255dbd03 a3071ec0-00db-4f7d-9366-6f2629b0ddf0.rna_seq.star_splice_junctions.tsv.gz 79250fe95d103d7ab60d1de78d16242b 3507589 CPTAC-3 aa62b9ec-062b-41c9-abb4-c7217f259c06 c1279fe0-477e-4cd6-a74b-8bafe92fa5ac Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts d8533a17-a0f2-40c4-9ebb-79fcb6ef8431 0e387a66ee6b1ed4ce74f4d7729bf5e4 3549455 +cabf8434-d593-4774-84f8-57574fd4ba4a 966aaab9-2f26-43ff-8085-0aaf70775644.wxs.MuTect2.aliquot.maf.gz 9fd322bb743bd212fca5975da05a3ec4 6158568 CPTAC-3 bb2f14a7-c52f-4a2b-8224-c747a3daa488 e57bbda9-d5ab-49b3-a731-7b3050424f62,09adfee1-caef-414c-b95a-68ed0ce391a8 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 2025f0fb-0cee-414d-a9d3-bbda890bae2d 2e754c5200b7a40163cd35e96e24f10a 7303291 +387fa30a-f44c-4af8-affd-cf5d4dc3a390 672172a4-d939-489b-a17f-c57bb9dcda30.wxs.MuSE.somatic_annotation.vcf.gz 382fd8a5a234720d812b9422ce47db33 119855 CPTAC-3 91f09875-d14f-4fc5-8187-91a29ad32450 915456b8-74cf-4951-b705-d7f887227032,4948ec26-0968-4423-9d77-9857cd193437 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 234da414-3d60-4634-85d5-db06e3e8c21e 8e1f65642477f95796f0ef98896a9c8a 124780 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Annotated Somatic Mutation WXS MuTect2 Annotation bb4158f8-ac91-4096-bd00-ca36b3b7f922 4f08efb56d17f2d3dfe386dda3b7e414 3766061 +931fb9bc-3da1-4f1b-a08a-8704a312f16d e9589a10-1052-4015-a2ff-e64a54182180.arriba.rna_fusion.bedpe 4eed291fda28fe435d6b49188b840c40 1694 CPTAC-3 e002d33a-86c4-4e19-acde-d542096f5fdb bb421dec-3cf1-49b2-8ac4-478dd4812a1a Structural Variation Transcript Fusion RNA-Seq Arriba e441f719-3d03-43ce-b642-e96d3ce31e85 8564d54fd71fe7107dfa6f6c2f2ad0bd 2443 +4677d3ee-fd86-4fb7-8776-e21c1923fe9f 004f6064-3f44-41d1-b20e-6851b304c62d.wgs.BRASS.raw_structural_variation.bedpe.gz ec71bb87dfb50586099b66e76fbd39c7 4250 CPTAC-3 4a6039f3-ac9f-4034-a91f-ee90bee63f27 e7f1b14d-4706-4e02-8833-4e72f56a82c0,a8a006ee-1db0-4b57-9437-85d29dc1084e Somatic Structural Variation Structural Rearrangement WGS BRASS 4c24245a-f8d9-4e5b-bb26-a4723899214d d6dc92101b3c9e0ccc8cfeb202e8f6d0 13457 +5214e54d-8840-413b-b034-0931e166c343 45752650-9ad1-4b90-8368-6fc7a9069fd0.rna_seq.star_splice_junctions.tsv.gz 4baed9a6221bb6b01a60bc9e4fb9912b 3249650 CPTAC-3 3569f880-3672-4b78-b675-c1c2c0a43d1a 83b73a69-429c-4bcd-a1a3-b10278a2bbaa Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 12aa66bb-e3a4-4a4d-b16d-5aa8c406ff26 6e9bb30d28d1736ad3f4001b2482d23c 3287102 +870d955d-b8d9-4b29-9beb-0d8437efa0ef c6f91c0a-22ed-459e-9cf1-3db32e16520b.wxs.Pindel.aliquot.maf.gz 1252150b9f30608211a04dcd430ab35f 753569 CPTAC-3 e8f5fa81-4478-456f-bea3-fba6d48e5b11 791db96f-984d-4482-bd0c-5691bef0b600,c043b586-b3c2-4a81-a4f3-ccc22a2ec00d Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation c60e0664-653a-4e17-b355-ec38afefbbee be99ee0f5e9e1e72dcf392b445a2ef48 787255 +631cb13f-b53d-4186-a27d-c86845f507da 95b45231-8c10-4be4-8113-522bf8c0c23e.rna_seq.chimeric.gdc_realn.bam 62b0e8403a5fc224e1bb5ba8e895bb98 29794128 CPTAC-3 cf958f8c-f1c7-4adb-ad0f-fab5133042ed a962a8dd-31dc-4489-a272-455822f6b5ba Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 633ff37c-9313-4da2-960f-0156a8329878 9d12d300c3814f965cac81f573c4cbdf 29788071 +33911cc1-aaa4-4590-9cee-3396a652277f 32542cc9-25c7-46dc-a36e-be8a36eeb804.star_fusion.rna_fusion.bedpe f3b45dcb248ce6ea01ae67e09df40a3e 1722 CPTAC-3 51f39708-5443-4037-90b0-864e25c20388 5829500d-3be7-4dc3-a300-4fbdf0d513e0 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 2da50fe5-b85e-41c2-80b8-d3fc3844d200 aed128510a78f99679d0fdd5b2194922 459 +050460ea-6b34-4fcf-8c67-81323fae8e71 242a2ff6-a9c7-4bfb-9316-0214c015c015.rna_seq.genomic.gdc_realn.bam ff8e2a781bf8d8bec3b9af7fd12883c3 10077580481 CPTAC-3 de1701fa-ca4c-4104-b8e2-ca3c10bf516e fde92faa-7c74-4f79-bac9-6be631daf1e1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 2da5a254-fbe1-443d-b18c-21cc3295c32a 270e68e9c497edf20d5b44eff8981964 10079730004 +215b6747-ead3-4e2f-8bcd-4a4f99e4777c 826aea1f-961c-469e-8496-3828113f3b64.arriba.rna_fusion.bedpe 2872d78c93894547f878562ee18928c1 5204 CPTAC-3 6857e6bf-2a4d-4fb7-a891-04911c72d1f7 021faa88-c804-417e-841e-63ff35e1db2b Structural Variation Transcript Fusion RNA-Seq Arriba b0724cf0-83ee-4d41-9e33-af45ccdb424a 90cf16677cc227bcf28627ccdb7271bd 5845 +b72ae43e-f2fc-4a80-b160-fef924dd88ef 41145ac8-5a02-47e0-8511-a85c7caead8d.wxs.MuSE.aliquot.maf.gz 5567e3e8506bd4d388a0112e3fc398b3 129186 CPTAC-3 ec1b3344-5165-4303-baf7-7b06019738a5 3e109583-a3ce-4b0b-8b85-a92d038457f1,eef16b63-5ce4-4ee8-89b9-d0992a129bbf Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 03432e69-14b9-4106-bbc6-a36208022665 c09c0b4883eb00ebaae8ae5543c9fb81 167264 +80c06d3c-992e-4c74-8391-b48c82880a37 0b12b3e1-c797-403c-931a-ded1f7179eb9.rna_seq.star_gene_counts.tsv.gz 3082e1871e9115d6fa9c6550bce4c81b 418768 CPTAC-3 8dca2f9c-208b-4d06-a588-0cafd175be7e f8e84d81-7190-47c0-8639-bbf625e221a4 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 76edf649-9ae5-41e6-ac2c-197fb5fc9760 2c5a815ac3b871968c0af675bb222c9e 4230823 +c7214850-1871-4a59-ad4d-a2253e8f1e59 f774487a-0ca2-441d-9148-5e0cba9f042c.star_fusion.rna_fusion.bedpe b255c9e05b113a5642f1d79a92bdf7cf 663 CPTAC-3 f8a5b06c-653d-4a39-a3cd-72ad2784ebd7 16746a0b-86d7-4ea3-a1b6-ac0546c9817f Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 345fb9b7-af4c-4eb9-ba7f-0737ae57fd59 8d7ac61ba695e9621c988693ce547063 659 +50fd35a1-9547-4db4-b555-ec65dd610dcc df698bd0-1a30-4d81-930a-921d81737f52.arriba.rna_fusion.bedpe 04ee9abe1bcbc50f026b86cb483becc8 1754 CPTAC-3 41078a19-092c-4930-a3f4-eca47256622e 8516be4d-b654-421c-8f5e-a20796c22586 Structural Variation Transcript Fusion RNA-Seq Arriba b4294868-1baf-4fe9-9011-943bd68214f9 f93b3d566f4d3fe019f10ae14188de9b 1002 +c2ec03b0-f599-4f85-9ccf-6c0bba41b644 b633c89d-e01f-46d2-b5c6-577351f897ff.rna_seq.genomic.gdc_realn.bam 0faf3209af15861465e387c0e6ad4528 10001019050 CPTAC-3 192571db-fc43-46e9-9f25-d2db46aadba6 741a2a7a-3f4e-4b72-bb89-fedb87a19526 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 5d47b10f-b838-4bb0-acf5-84a82a0b70c0 6bc223012113825440c5e8318e53646a 10003188284 +cb8060d0-5a1e-4a46-90ca-47e9070ff5c2 71058e27-7869-4d14-b71c-b4827e75ee4b.wxs.Pindel.aliquot.maf.gz ebd61d07256031a68e98064283671557 38340 CPTAC-3 7e317f34-e8a7-4803-beb2-470d5c2ee93f eea6f712-9bd3-4c3e-af23-f9e3ad5e012e,aabb4a27-736d-45c1-b5d2-e22def394b17 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 5a8c6ee2-79a9-46d7-8939-8d8637783cb6 a9d74d5e2c5bb049d8b726bc750044e9 41735 +0758838d-7f53-46d1-b338-496e23939e6c e22277e2-d404-4581-8985-1aa537b3d5be.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 ad688008-ae8d-4bfd-99ab-24998a2c248c ed31bdbf-f13f-4d3a-bd4c-e6ed56bcda7a Structural Variation Transcript Fusion RNA-Seq STAR-Fusion c38872ea-8bb9-4af3-8669-0a8343beab62 6e5690795ff424264402ab9d2661b62b 229 +9eee82af-2c94-46a4-94e0-79191e638705 e3934dd5-3846-42e7-847f-5972431f49d5.rna_seq.star_gene_counts.tsv.gz eb0bc28f1e1a837f11b677229bc806ae 406584 CPTAC-3 e8d31ee4-804b-4557-a70c-9e6df8e25606 329e0523-ffcb-4ab6-ae07-db3ce2b6a586 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 7c42870e-d318-452a-8e9f-84029160a77a aed9300b86d3ad2bc6040c171907d97a 4222203 +832636c7-1c30-48cb-8699-7e411cb67bd3 0381924f-3719-41d0-86fa-a1b47c3ddfde.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 6e1a997b-bd33-4702-8556-58f17ac0fa4f ed2a110d-9362-44e8-b380-2b4949818e27 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 0ca0b538-1f27-44ca-84e1-02116fa08a57 6e5690795ff424264402ab9d2661b62b 229 +5dd1579a-3ec2-450d-8c2d-661acb6db10f 0eca752c-7d21-4f0e-b716-1bf00524d417.wxs.SomaticSniper.aliquot.maf.gz b31323c9e5a6e20a22a160440f46e410 879914 CPTAC-3 c471fc2f-f9b6-41c1-81d3-0f572595dc14 f5139e18-95b6-4359-8018-f511b3cdbac5,2bb0a549-fd8e-448c-a32f-dc0d41a25a53 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 11f1a3c2-97f7-4ad5-b214-eb283741df10 337d71bb7ffa9d71eb2967baad7384f7 1184621 +427fd35a-40df-45b9-930b-68b58ea90e81 38520d04-f833-4c2d-bb0f-f672efc3f948.wgs.BRASS.raw_structural_variation.bedpe.gz 551199ab102db3a817fc4712a488ef3a 5112 CPTAC-3 46be30d5-b623-4469-a1d3-fbc76a62cca5 ab486740-7504-4009-8fa1-5b36b5ae988e,e1adcb02-b22a-4ee5-bf75-701907f3d2a0 Somatic Structural Variation Structural Rearrangement WGS BRASS 9c691b44-9a53-43e2-8e18-b4f894ef19ea 4879414a679133a1575e14862b07fd95 16212 +15f1a083-0f7d-4c47-85fb-bb09cebc8dfc 12052c6a-fd7b-450d-b8a4-5210e7bd677e.wxs.aliquot_ensemble_masked.maf.gz 04b2f76cc99f7f35e962fd0290355556 15848 CPTAC-3 25863969-852d-408e-bd62-98e0df9e4b3a c29ed504-d297-4fc3-ad09-200319492ed4,2ad75cb1-668a-4d5a-b62c-254e0b82d045 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 7c07bd1e-93fd-4dbe-9455-e6250e946e39 edfca8051e6e733949f7055f386039fa 19749 +131973c8-1e28-45b8-a2f0-87a24caff91c e160734d-daf9-47d7-a552-36b21eaf6046.wxs.VarScan2.aliquot.maf.gz 590c575e4e6a15e0e303e7468a46f5ea 782324 CPTAC-3 51f39708-5443-4037-90b0-864e25c20388 d7d49f54-2e47-4f16-a3ee-48c85116d4ca,6ff5d3f7-220b-41fc-9a8b-71827ce106df Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation f0950dd6-2720-4fc1-96ac-1d6cc5a30036 42ad972582a3218870eb74825c5cd89b 908923 +5da1d1a8-9b32-4963-b0f1-2dea1a90f5df ae66ea9e-686c-4d8e-bd84-8726972b6930.rna_seq.chimeric.gdc_realn.bam 9c476467a403079716b26a17cb6a373c 90100259 CPTAC-3 2f9e1f15-769a-43e3-a68d-dde243883422 fcd433c7-1b54-4b52-b566-50a0983a1810 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 8f41e2eb-892b-4c05-bdf2-59aa9ee24538 eaccd3fb9e764d5d2cbbf33b3cefbb5d 90081201 +a4508a70-a34e-485b-b557-684d4c532bad 71f3dcab-b871-4e7f-b68a-43d27e5840e1.rna_seq.star_splice_junctions.tsv.gz d19893723dd095f3a8010d6e60b8bf31 3424177 CPTAC-3 ba4f0ba9-f184-458e-81ba-9c4b1c521336 3c4160dd-7b99-4540-ba81-87bd64d21188 Transcriptome 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Annotated Somatic Mutation WXS Pindel Annotation f9ce498b-836f-4c18-bc30-83a521875d8b 546e275dd0f38a0dca8fe2224b33ea7c 332990 +582ce6fc-e6b0-47fa-adf7-11ba980abe14 749bc05b-ffc7-48b4-b7c7-1e5278a5d83f.arriba.rna_fusion.bedpe 47eec88670d29cb86821600d6560973e 1890 CPTAC-3 f674a0fe-66bc-4b0f-a12c-e025655f8a64 94ba8a1a-7c34-4f6f-afdc-d7a439375533 Structural Variation Transcript Fusion RNA-Seq Arriba 29a184b5-69eb-471f-99ec-c6ab15ec916b eb65708374c22c91fa70f26c45d3fadf 939 +1a599a0b-0f52-4f30-8047-4fab695c823b 06d74e32-c25f-4ab0-a2e4-acb089053344.wxs.SomaticSniper.somatic_annotation.vcf.gz dd366e659815f77008ffa590a2285d3a 1271147 CPTAC-3 8e910c4c-482d-4d9e-b481-b0ab52985b51 f3517079-507e-475a-9fd1-b355d59be341,c38b9acb-52d8-4fd9-8ee7-2e4ac8175fcc Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation cc7e2e3a-c20e-41c9-a6f9-78c995b2ab73 9f6afbb587c8cac4efd45085a21093a9 1310081 +00bdd704-c025-454c-a213-bd2a9e5eaa4d 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97ec897b-c7b9-4ccb-8bd0-caa209d71254,269ffccf-de74-4303-8d2f-0b737598d9f9 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 8d15ef19-9de5-4761-a28a-95792bc6371b 9bfadbca5731f34188b155ead925e3c2 76888 +ec759b50-ccc3-446d-b7fe-380b7db2405f 3264e869-0084-4f8a-a6cf-8efbec299caa.wxs.MuTect2.aliquot.maf.gz 4280a16f10989e8333ffa48c9b7f9035 5524695 CPTAC-3 5705efcc-b48f-435c-8a28-9e0d407ecadd 552d7534-1fd1-490b-8751-9dff1bf55569,6b8b5928-258f-4f93-9e52-516db4562c2d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation d1a3bf86-5365-4158-aa1a-86d6ecda8be3 3eddc9368dd3d1ac3158fdd5173f0dc3 6716400 +c4c0610d-cf33-4120-9d4e-45fed7f0d175 5be55fa5-2ba0-4ee3-86ae-3e5bf892a89c.rna_seq.genomic.gdc_realn.bam 203a8fa4e83469c65a91d9085bf1d192 8711311413 CPTAC-3 0900fe7b-1872-4214-bb2f-efb16234db23 83465edf-0b84-4b6b-b2c2-492324ec2c4c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 2abe0ed8-84d2-4d90-922e-030d7a97d7f3 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Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 1bac177a-7f99-457a-88b3-d8cb03736f7f e910a17c58baef4f5d9ce0b95d97ab42 4686032 +7e0e72a2-2321-4b39-aa96-6c71fff61cf7 027640f0-023c-4374-8206-5e6922d694fc.rna_seq.star_splice_junctions.tsv.gz 6d7d2bf0c88a09387186a2443e1b38d5 3562701 CPTAC-3 a3d3b5eb-500d-4859-97c5-71b6111326d3 b2fdfbde-d43d-46fe-99cc-1553b4ca36a5 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts edcbefa6-b33e-4760-94fe-88191d97da94 99d0f2e73e294054bf49434e66eabb25 3602296 +21942094-29db-43ae-9c06-86f3d2452a8c 13eb22f0-c76c-472b-bc08-e76b243b6dac.wgs.BRASS.raw_structural_variation.bedpe.gz 236f69155d16ecf21859f667c0e5608a 10097 CPTAC-3 dbab1830-176e-4f3a-a094-1a4301a70a7d 43f0a061-d864-4aa8-b2c3-00780f10c69c,a1556574-d2cb-40aa-b24a-c803a70fe646 Somatic Structural Variation Structural Rearrangement WGS BRASS d3164b4f-3924-4983-bce9-a01a6b06f881 14a57fc1b13426d00f384887b05b1e1c 34652 +fced8765-dd6e-441c-8ff4-5b46183c8a28 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Mutation WXS MuTect2 Annotation 4504dc99-c21d-4df7-97a4-b80c806f7cf5 9e0f8b724095a8349b0c4bf6f638d0b9 6291983 +8cf510a3-fe61-4922-bb91-c7cd8fb0c7dc c6dd4776-6565-45ec-a714-fc08ffac918d.wxs.MuTect2.somatic_annotation.vcf.gz c5500f8c715f1a22057439f9b5b5ce9c 2378683 CPTAC-3 1570eaf1-9b92-4506-9df0-9ae9a704a731 89529584-f16b-447e-aad4-e01b365c8e52,c1eb9e6d-669b-4d1c-83c6-9710f4c80717 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 36a1745d-3fdb-44df-b34d-f6138a21a437 31badea0d861f8052c76c1fd8ff12cf1 2510148 +0ba0e5f4-3557-426f-bb65-27bda2fde323 5f166d2d-55fc-4299-80d3-c1cc322956e5.star_fusion.rna_fusion.bedpe c4a5c9962d7e3e4d82c68830a0aac6c7 890 CPTAC-3 52153098-f1b2-47fe-ba4e-88ce6d51a6ca 02fc9aea-63e7-4918-b494-82ab3ac41599 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 68f63ee6-b59e-4536-9a7b-cd68f4db71e1 1fa72212bdfa0616593521b8b02007fc 890 +1511d5e7-ec8b-462a-8b1f-c6af3922372e 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Counts c001bc00-d841-458c-ad4b-6855d782bbbb 8fcd31091fdeba699a09a764c099169c 3165657 +f56e9a8e-48c8-41dd-946d-fc8ef4ca0a90 be19f8ce-9800-4009-93a7-0d8c6c297aa0.wxs.MuTect2.somatic_annotation.vcf.gz f78279f2dc0bbd706cffe632a13a49f2 2175113 CPTAC-3 538424a8-0d56-4d6f-806a-19a0630c9d83 c92a1f84-f7a3-4332-8ab9-b64859f501cf,5ed32977-dc68-4499-91a2-14b00a4c0c9e Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 3c7d6ed9-1fe5-4af7-bc65-015c55271bbd b210f7bb071d8a8110abc69325b52519 2292271 +28e1fcf3-2cef-42ee-b810-2d546a6de685 7901a01e-44f2-4136-9bec-63735cc70b83.wxs.VarScan2.aliquot.maf.gz 604c69bb426cd378fe3d8b915aa38721 218141 CPTAC-3 c94de5fb-4fcf-46f0-a4f1-41a88f557770 d2d78e06-7a68-485f-a67e-256986fb3006,86ea43f0-a9c9-47de-959c-d96c72272713 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 29486e25-a442-48b2-82de-c489ac8dd692 92253f0fad6ae6cf5cc01d27110fd615 265776 +0017f5a9-ce43-415f-bd97-5a613a3a7f53 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Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 8bf5d7be-ab62-446a-9e3c-9c95dd1d0b43 b96fec229a1cd9fe9ff97dd824b77e6a 6440375 +bb249f7f-e4b1-40b2-a89d-0f0452e11dc0 0fbdfd1c-a656-4e33-94b3-552e50d3c827.rna_seq.star_splice_junctions.tsv.gz 0cdb88fe03b91b62603514b8c5f92893 3617135 CPTAC-3 f9b986ec-8cee-4a2e-8722-947f6919f05b 3de035a5-6825-478c-8656-623997ec45ef Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 4ff34ecc-9359-491d-8bf0-3becbaae49a9 77ea4178277dc73a95b2e7a92ec90065 3659339 +8506d15f-88c0-465a-bea5-14dd9c7bf3a9 4cafd6db-d0f6-4924-84cf-4449c9c5869d.rna_seq.transcriptome.gdc_realn.bam 4b896828b32635a3e122594685cb90b6 6504850811 CPTAC-3 6145ec3f-90c8-4fc9-8f49-9f2d699da65a d998ce1d-7cb9-47b9-8356-de655a634745 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome f927c4cd-bbfa-40ac-b759-75f91cb402b5 094048dd80c81479a5c88b1c1466cc0c 7366262123 +5b1132a8-5f8f-4669-aba5-a13286aac401 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Annotated Somatic Mutation WXS VarScan2 Annotation 92e975f7-5a2c-493f-8366-e46df49b0ded 2c68b5acdd5a590a857034e4d915b411 717272 +4fd3bbb8-78a9-4826-ba91-a206963a42b6 ea1aed9c-1c9d-4042-baaf-fa9f7eae9a90.rna_seq.transcriptome.gdc_realn.bam 6a7767f37945270f575a7f20ffc70307 9485806112 CPTAC-3 669a57c7-0ecd-4b39-8a2e-a98a830bebed dae74986-4350-4915-9e62-860604ac81f1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome adcace2f-32ad-4f6a-aab8-c4bb9f12649d 2dcec49c2603166caaaa00a142b40f95 10671266014 +548661cd-35a8-4b1c-a062-6b2689e742cd f5ecd85f-0862-42a1-84c9-67e2a9f961b1.wxs.MuSE.aliquot.maf.gz 5430b84374c6b8371ce2e91069f820f1 483455 CPTAC-3 070f4283-176a-492e-b418-ebf292cd37d6 0815b3bb-c9ee-4804-9f51-05014a8e5fbe,b686ec16-3532-4c19-83d2-0f7c2a36000b Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 32d08ca6-3a8c-4e10-9e07-9fd3a371a077 1d12fccfd381716c9936ff7d7ad8a224 549446 +5303ba23-363f-432d-a5c4-7aebdbc1b93e 42fbd86c-46cc-4f26-ac0c-03d9889b2138.wxs.aliquot_ensemble_masked.maf.gz 8f1c3338812fc0c6e8d7ab73167e2ae1 21763 CPTAC-3 609a220b-498e-4f7e-b30e-224755de1090 c1b6681d-491b-4738-a2a7-d3363b2b9f4e,f41b6b00-bcda-49b7-81c6-5660d2da8d56 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 5a0bea65-c419-4e28-af38-57e162daa239 48ab0c65179fc90248cbada1aeccb28d 28814 +ce2aa073-acfe-4300-96e8-8dfa7010c68b 45cd7244-0a72-4def-81be-7a07a15e617f.arriba.rna_fusion.bedpe 5e9116a696259d4c8631569d87b1f2bc 2357 CPTAC-3 1f04dddd-e6be-4bd9-b269-6425e648af18 0e51f041-efdc-4658-8d5f-4e5cdd9e2f08 Structural Variation Transcript Fusion RNA-Seq Arriba 51664f5f-5e89-484c-9299-93fa53cbf2d0 6aa20491a16374a8dec5bcf355eeb72f 1712 +17f3b25e-4dce-411e-af54-f05bfa47c0a5 2d7605aa-3908-4bbd-a90e-1e422ec0c64b.rna_seq.chimeric.gdc_realn.bam 011df9f6518397ca9dfaf4bf7358e85d 76398971 CPTAC-3 9969f301-603b-477c-8236-b4ac5227fa52 1769e0a6-3b34-4b5b-9926-e7a090743eef Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 143b8440-5470-4245-98e0-5ee9cff58d1b 8ee3d879e5745a14ddfb99bbe4cf6e68 76384445 +15b7dc70-5077-456d-8ed2-4a01fcfaef97 b58649a3-d6e3-45fd-96ea-01f7b6b51dc3.rna_seq.chimeric.gdc_realn.bam e7a02f6af96aa5cfe7078c55503f3c68 40977557 CPTAC-3 a68d6b4a-141d-4c05-8835-e1c0a264625d de54dfcb-f221-402a-9e22-4913de4d2859 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b7b4781c-1ddb-4c7e-9f54-a11270b0e8c1 224057da30f7ca3a020e8f1bced6e9bd 40971506 +5d69f582-431d-4507-bcc9-ba205ad87ec8 7572071d-2cf6-49e9-aef8-cc5a304e0777.rna_seq.star_gene_counts.tsv.gz a109cc3de0bfefc65b57ea220d9b7e18 426351 CPTAC-3 d55137b1-a388-4f21-a50f-3b3ddeb2edba 260017b1-18d9-4d3f-bcf9-285017d013d1 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 8637197e-fd2b-48de-a99b-83be756da985 0ac049c1efd12d75d7e2e460a28937d4 4238489 +f049af9b-2f70-44cb-a12e-ffe07c221140 b664d441-ca74-41ec-b4a3-a84f9cb22617.wxs.MuSE.aliquot.maf.gz 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Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 27cee589-0985-45bf-9c33-b2867b8e36b0 b8f2374f90bb78b2438fc2f1c7a19354 4220697 +b686265a-95a1-4a70-95b2-6ffa402a3abc 8dd6c98d-7aa8-4574-8c31-9e802f4b3817.arriba.rna_fusion.bedpe fc05f1f268e290b9f99081ce0c0da54f 1481 CPTAC-3 746b10e2-5824-45e5-b85d-fdecffef3e1a f9d430ec-d512-47e0-adb5-ee100a901b12 Structural Variation Transcript Fusion RNA-Seq Arriba fed36b5d-60ad-4968-b883-095d64d9eb5b 174f783cd05b4ab95a58a99bd612a6db 1063 +53372ed6-5b96-4074-b5bc-3472a6423b13 7be8c1b4-eabe-4224-8163-3134668d148a.wgs.ASCAT.gene_level.copy_number_variation.tsv abf662e7579d2c13932415e240da1d80 3482627 CPTAC-3 8919013d-01db-4469-b0a6-553dd25fda6d 73ee6f62-37dc-43b0-8ff4-0a8c1c1a2f17,84458a40-db8a-4990-b3c0-3a22f842e9b3 Copy Number Variation Gene Level Copy Number WGS AscatNGS dc7b9d4c-ea01-4171-988e-468af38c89df 122ba228ba788efcfede22e61787cabb 3442679 +5874da52-451c-4088-9641-fc074d6547be 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Arriba 93c327fb-918c-49b7-97b7-acea75603c09 97ce9f0a1574d9b591aa3563d71fdede 2096 +3dcad12f-0880-41a4-8d79-734f91b4f962 3deae8f9-5ae7-44c8-b5ff-8ca06c11b455.rna_seq.star_gene_counts.tsv.gz db55eadc2804d52ee5a9b68c2a16aa0c 413869 CPTAC-3 5d9f9c9d-2188-4106-b75b-6add5e560855 fc159fd8-d225-45bb-81d4-323e75e77156 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts f7f46527-516a-4b15-9055-4ddcacd83fbb 158caead412325c53458b15ba28bee04 4225597 +99f7d734-5c28-4bad-90c5-7edd876164c8 25a20c4f-1c7c-40d4-b799-57163c36e14b.rna_seq.transcriptome.gdc_realn.bam 1758d287f806ca7d598c371a9ba0d12a 8813914231 CPTAC-3 f5407aed-7150-41dd-82f0-f28975ee028a 4fc50a93-10d2-412b-a54b-7d79c27d3f86 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 67e80ee4-cb24-4439-9f3c-aa14470556f5 02520de4c4cbebac6e3f2ce82d91d4cd 9917902583 +465464cd-fb02-48b8-8103-60c6ca422126 0acb3838-839e-4db3-9314-9998bed44f47.wxs.Pindel.aliquot.maf.gz 25d28ce3de2e3c74910b8dc32a199e53 318724 CPTAC-3 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Quantification RNA-Seq STAR - Counts ce25fd85-7b64-4e38-a870-fabefb13aa34 ac0bb50ff0b4f5935f4e936381d0088e 4229149 +dd588d13-0583-4976-b208-73f163384aac 805d0a5d-b4aa-4fac-9dfe-453b3f275ab0.arriba.rna_fusion.bedpe 494e545b3a14c380fb654d742889481d 2184 CPTAC-3 67c1aa6e-0bc7-40e2-9742-8f73be3ed450 56141fbf-9f28-49f5-be3b-4b85cabcca1e Structural Variation Transcript Fusion RNA-Seq Arriba e73f679b-1ee9-401e-8ca2-d2ab7cf2c7e6 7e9d853117aec6b07eb6fa947c04e3e1 2132 +041d92b7-990c-40c8-81d1-1905b0bf5e9d 98da284c-bdf8-4e1d-93c1-66ddf97f06ab.wxs.SomaticSniper.aliquot.maf.gz 4cf8eb2704cb54f6fd54ec3d869ea8d9 1074118 CPTAC-3 964ad18c-9452-405d-969f-c9f40af48b4c 850bd0cf-dd68-40b6-a6b6-83e42e76fd32,9872eab8-63d3-4882-877b-7b4de75bba37 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation cdd4f33d-7a51-4b69-b094-3ee0a40d7b2d 3c6b000f0bdcd55423f17e625236bf88 1423748 +a4923d63-1082-4f77-9c34-5756d56aae4b 40214361-ec93-4ad1-af1c-f16cf8785e86.rna_seq.chimeric.gdc_realn.bam 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a0663966-8097-4057-95ab-8535dd2bbd1c 7e0aaa824deb5997d4074bd1d297e711 804287 +dce7f411-ea16-4202-8ec0-a74311c0cbde e7b27e88-470c-467d-964c-cc01de2ea073.wgs.BRASS.raw_structural_variation.bedpe.gz a08d2f09eba3d6445a7dafcce881aefa 12433 CPTAC-3 84ccbb07-5434-47e2-ba17-57d64331b8e2 e0e4eca2-5f90-4ae4-924f-4e5548af49b1,758bb858-fb40-4be5-b69f-a1c4bc0f8f98 Somatic Structural Variation Structural Rearrangement WGS BRASS 281718ef-b641-4093-93eb-d316dec82f23 4a609dd01de9d0dc2750dab6959d5859 43552 +f27219eb-a9ce-45e7-b4b6-b38f66b2a016 3cf70789-880c-4ce8-9b13-a61fe9fa1d46.wxs.MuTect2.aliquot.maf.gz b60123d2f8df57f1c74feaf09d85d8e4 1940524 CPTAC-3 724477c3-2a3c-48cb-8a3d-38782f5225db d3898b9b-e275-4f84-b7ad-808669463672,f05424ce-b910-4564-b808-a01185fe69cf Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation abcd10ab-a92c-4c3c-9ab5-69a4e1ac153b ece37a87e3a7b4d633783f3301e025ce 2243778 +a604b55c-9ae1-40a6-afd2-e7ccdf962280 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Somatic Mutation WXS VarScan2 Annotation b63023a2-ecc9-42e6-86f4-26424a3f7c4a 9698e17d53b77ab7c87d1cca1b87c41f 243776 +8ffd2d09-dbfd-44cb-b231-458a33d486cd 8d1a2814-4cfe-4e06-a780-57c2c2d335db.star_fusion.rna_fusion.bedpe 50c45ae2106c19ddd368e8128006c747 791 CPTAC-3 5657645b-d839-4035-8e69-2a9c78232cdf 37f79464-7dea-4477-a95c-4d7f553dd9bb Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 64ac009d-eb0b-4654-be21-abaca9022aa0 6e5690795ff424264402ab9d2661b62b 229 +bb14ba59-9a15-4643-899c-35a7fd962c11 87b54ad1-47b4-4627-8468-19f656be5422.wxs.SomaticSniper.somatic_annotation.vcf.gz aeaf74062517687382195277b1f19fcc 1008679 CPTAC-3 5d66be2e-e3a3-460d-ac80-0ac8112ba9c6 c2c323c4-a8f3-46e7-8eaf-28154ed2dbd9,e370556f-98bc-4182-8a75-9ef866159d07 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation dde81a5c-c49e-45bf-ad50-5b5c682e5ae9 77af7126052a6cdff58baec51f0ef309 1051062 +1aa856d7-898c-4047-9820-23fa16e04c70 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Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 0f75c406-22ed-4051-b654-1727e79210d4 02004fbe926b3467ae0eebbd4264d33e 37296 +dd630f3c-5ccc-48ff-9b5b-51b2547b8700 edae1beb-83fc-4640-9c62-4060290934c0.wxs.MuTect2.somatic_annotation.vcf.gz 8eef9a93837b4636b84edf2492b09129 6853250 CPTAC-3 8d1b6812-9c39-4e83-b6d4-8091f9ff6018 b47a302c-4e31-4c79-85e3-ead148c0237b,e7aeabbd-a8b9-4804-a19d-a02b58cb27d7 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation d7059267-5bff-4ba6-a1dd-f624dcb6845e 20d8456930ac691ab6276fe53b7ce284 7544874 +fb7544c2-fdfe-41ee-8220-c95987e91efd 3bdceef9-ed65-4887-ba40-462a72e849c4.wxs.Pindel.aliquot.maf.gz fca7717cb542dd033eef0887582718e4 407101 CPTAC-3 8ac75c82-eb1a-4e9b-bbe9-131a78a9f540 b7314944-d4d1-4f1c-9359-5c631f7c5041,5fcf480f-d48f-4fd6-940b-051912cd9943 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 98f33c0d-ba33-4260-96dc-8874dd0481dd a62a84d597d783884aa3b387c38e27da 408791 +4023cfce-f320-40c7-8fc3-4dacb7125afb f3ad237d-b424-4ca4-9659-2ff88a42e584.wgs.ASCAT.gene_level.copy_number_variation.tsv 6e644de87a9ef26c5e32a22e8d12ad9d 3481540 CPTAC-3 4c055580-81e1-48e6-bb81-f607b393b053 bd96ecbf-17b9-4dac-8090-05191cf90ee5,ede2c262-e52f-4ba3-a802-058195b89e64 Copy Number Variation Gene Level Copy Number WGS AscatNGS f462f5c2-c6a1-4a3a-a99e-5b89e77d1978 d82ec6137792f09ecb618519b617cd1d 3441633 +5aabad49-caeb-45e9-93bc-efc22d16d4fb c37aa590-5ba9-4268-89eb-b5ec66664e5b.wxs.aliquot_ensemble_masked.maf.gz 689cc27bb71db83a23deb0ae1219f3f4 47590 CPTAC-3 8d1b6812-9c39-4e83-b6d4-8091f9ff6018 b47a302c-4e31-4c79-85e3-ead148c0237b,e7aeabbd-a8b9-4804-a19d-a02b58cb27d7 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking e69dc22c-2bf1-44a0-a05e-d424cf7876ab 6fa63c3944d5fea6700a35c1b29f46d7 61640 +c1e68d40-c02e-4933-b205-12ceb39b67fa e3037fca-cccf-49b4-9b50-3593f80c915d.wgs.BRASS.raw_structural_variation.bedpe.gz 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RNA-Seq STAR - Counts e918b472-8550-4504-b475-f0675c1b4fcd f28383bd53f09628a42473d444404f85 3672480 +0fc4e5a7-0fea-43a4-a1b3-d22b0ad66119 94b728ad-a7ea-4646-a0c9-6ce2034bec13.wgs.BRASS.raw_structural_variation.bedpe.gz 24cfa0e9cf3df0e5617e11160815990e 3602 CPTAC-3 61c4a631-c7cd-4411-b5d6-f55e584faf6d d2db9a6c-ad14-496e-accd-afcbf09093e7,7b5613c5-fbe2-4c47-8aba-ef678ce19f29 Somatic Structural Variation Structural Rearrangement WGS BRASS 7b4af9dd-a1c2-4afb-bf36-b0eaf83321e0 1f3401b31583f5fc7ee7899905d8a484 11874 +3ba20e25-4941-4860-9654-ca713e63179e cd651bb3-be8e-4d86-9459-858ccffdc62c.star_fusion.rna_fusion.bedpe 46e6a0318152b09f1c0ba87c13c4b4d0 1034 CPTAC-3 715f4c03-f9ba-4cd7-867c-a4e69a1d2f7c 73ad72e3-88fa-49f4-86ed-ce0823b7c590 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 36ac9635-f914-4580-ae10-e66681d9ce8a 6e5690795ff424264402ab9d2661b62b 229 +b71791b1-d7df-492d-b9b9-940f2b29932f 40acac5a-886c-430e-bbfd-dedec62aa0bb.rna_seq.chimeric.gdc_realn.bam 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1588b6a785f2199535e0418d34bf8839 253977 +aaf7f81d-abd0-4659-a610-407cfc62e184 626ba386-f1f5-4658-80eb-190a8698ab5e.wxs.MuSE.somatic_annotation.vcf.gz 0d2964417de0a2976ef94bf51e9ce494 214114 CPTAC-3 c1898677-7a92-48cf-a09f-71d91c1cf8dc 2a4a409b-1e69-4ada-82ca-aa5fb68d80e2,2f5a49e9-c6f0-445e-80b9-b66e560c5255 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 49bf61f7-d402-4fcd-a288-42b06a168b04 48eedeb7f05497048cb8413472d9304c 216341 +9417420b-e52e-4f4c-bc22-68c0e48c6d46 455c40d7-8579-4a27-8504-2c3910ad014b.wxs.SomaticSniper.somatic_annotation.vcf.gz ebdcb040db3be8cf8e2ba7fb37ee54e8 1067391 CPTAC-3 55fd764e-86cd-4b01-a229-16d050dc2f42 aaf33d60-8d89-4373-9f8e-1514cf2bf2ec,4b0c9eb2-41c6-4dee-8f50-05493e5cae42 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 9d8343b3-c8c8-4947-b4f7-6380a39b42b1 83620b4b279051da5fbfa199a0b5807b 1097020 +85c79d5b-7e24-4f78-9a4f-6a249a932d3f 720d789d-f333-4cb4-8459-c7fd1487c4bf.rna_seq.star_gene_counts.tsv.gz 26e0903b1385fa08eff2bb118f6f52df 421498 CPTAC-3 ae481eb3-8f9d-42cd-a431-6f289c8a8779 eeeff780-3306-4ff3-8420-ff4f4024d228 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 51a6acfb-6470-472e-926e-4e231076e8c9 d06c148424a0a3edaf9b5a18983b9fa8 4234192 +c7d4b2bd-0483-412b-94c4-845a4f20237c cb7510eb-7d7e-44a4-852b-826db5f316f8.arriba.rna_fusion.bedpe f197d3226e8955c23af086eaabe58871 899 CPTAC-3 f223ac50-c620-46b6-a194-381e40e429a2 dd5f8bd8-28d2-4fa0-bb1c-a1ceb26dfd16 Structural Variation Transcript Fusion RNA-Seq Arriba 8581be43-c19c-4418-aecd-4c61d93d584d 0e3b93796fd8a91628f1043b6eae78a7 961 +ef307ee5-4bca-4010-a4b3-c9bb329e2c5b d8da8871-b082-47d9-b688-845b424d5b26.rna_seq.star_splice_junctions.tsv.gz 7ea4dffbba0e854ffb1fcdb7a62dab81 3162515 CPTAC-3 e8f4be0c-5d75-4c8f-a67b-6d7302c9c372 eac8c70e-50cf-4c55-84da-0b782bb9d4b9 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 59c42625-d8e7-4592-9124-8b18bab026cd 09507164caaf2a65b5be0cbb8a20fc7e 3199671 +e524ae35-878c-4c2a-9c0f-a006537f0113 1833f9da-de2a-41aa-bfea-7d2bde8606bb.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 3a420b74-ac84-470e-99f1-811cbc37ac5e eca4739f-1713-4344-863d-f52e4e86d332 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 6c4ad547-9618-4c58-92c5-6804efe49973 6e5690795ff424264402ab9d2661b62b 229 +4c3f0631-2613-46ba-af78-0a2e43b05a14 240a8490-6879-4b28-a5a9-cb95c12b9f82.wxs.aliquot_ensemble_raw.maf.gz 3474c2b6cd87e647b9450aa125d17a25 180890 CPTAC-3 ac8ce1f4-d475-4da0-89cb-30067c2a37d6 32d6f5b7-d2af-405b-9e18-3d437fbcfeab,2603d898-8eb1-4f1d-93cb-c401918fb57f Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 6c11a432-7796-4d1e-b7b2-f30c3842bf40 4d3beab030c37140631663d5e03910ef 220542 +688d0efc-f670-4d02-b9a2-9a21e8c07d15 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050dfd8d-facd-4fc7-ac6a-0d19885cd64d,7d0b4208-55d0-42a3-95f8-9dde72c4009c Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 76ad92fd-8bac-4c26-871b-828bd84f848b c0609a3afeb5c7fc1c87ed5d76f5caa0 304264 +7d7b776b-4067-4b1f-98c8-33c8bb511e8e c3f628dc-fee0-4bea-a27f-8ebb8ab2e5fd.rna_seq.transcriptome.gdc_realn.bam 5a27aae1c5ab4a58b8db6c8969bb50f8 7578052610 CPTAC-3 530b32cc-06f7-4a32-bc01-086f9447f9b0 d02b2b71-63c2-4fe5-a4b6-3d52de3a9c50 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b825a72a-b9d8-46ff-a002-93d2be1ba0b6 3b34101e567cd2f9e7cfb4157de80ce3 8502010166 +76a5ef7f-cbc6-430a-8b16-4827e220f540 53d41184-2050-4997-9371-8c5097050656.rna_seq.star_splice_junctions.tsv.gz cc88d8c3b0b9570c79ac7d4807db5622 3150614 CPTAC-3 c43e357e-8156-4999-8972-d6c007a88033 79c4bebf-0333-45a4-af42-6b21aa4e0863 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e177f246-7ccc-45b2-b9a0-ec06c4f6a8c0 e1cbcbc699335c96e56697d397a10c02 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Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation e54319d2-6596-4820-b619-50a99ad5e6aa 816a9816041fe663ff53a72a456199fe 2863739 +e05276de-d7fe-4ecc-8c26-72f3c23aad07 c8e3741f-ce20-421d-b816-0950c93abb08.wxs.Pindel.somatic_annotation.vcf.gz aa9ef397606ac73150cdbc9f54dda10a 1159638 CPTAC-3 3da7fd40-f066-4057-b5b6-24f5f4877f8a 556af585-1b23-404c-ae5f-9a74ebc5356b,a5b555c2-cf25-4110-829e-6d4d6ba23e1e Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation eb7a816b-2094-48ab-8597-5422fd0c0031 622bbdfc39d16dfde8c4c8691c350b95 1211811 +a6fa8475-f930-4fd0-8df0-9e3446133391 76fccfeb-7c83-40ec-a785-1c9a97323853.arriba.rna_fusion.bedpe 2fbea877581ec2b10db20835b2927eb0 1417 CPTAC-3 f53d22a7-314a-48c0-b8b1-9799149ccc1e 975c97b1-d946-4d40-8e1b-627fa5b359e4 Structural Variation Transcript Fusion RNA-Seq Arriba 183998d7-8b19-4432-8a67-ebde5962af75 349db9666a85ef0bea901032bcd83040 1171 +0d5ed370-da4b-43ef-a9c7-73e106c12cce 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Variation Annotated Somatic Mutation WXS MuTect2 Annotation 389b7432-6717-41cb-8451-232df0df7cad 77f3050fc7c112d1f9803efa84d28616 2264184 +2bd0f5b3-1f9b-4fdf-ac91-4629a7bcfbdd 7c3eca62-0f31-4b8f-9a3e-588ca9e0ae40.rna_seq.genomic.gdc_realn.bam e57c416cff587d6fc8a32ec589d498cf 8757025568 CPTAC-3 3892e1d7-a1a3-40d6-bce6-1785cfa599d1 972e8bb4-5fec-49fd-bd6d-6b093a08df46 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 5452e6e5-1afb-4dac-8d31-ecb664675ee1 822a050770e6b7c5ba56c5c4c47e1e63 8757986045 +3f4f45d2-c17e-4283-be67-bdf2ac93ef12 1d7d022d-7ae7-4b9d-8ace-14f48b30dc68.wxs.Pindel.aliquot.maf.gz 8df6b673ca9c8ad7e7fa733bab713572 356483 CPTAC-3 ad265919-d589-4b8a-a9fb-77cca95c59f7 c702097d-4a63-4f18-9928-c89d27fcfaaf,330ca867-0583-4f3f-bd1b-03969b6a3ad3 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 905c7e68-74e1-4976-a014-2d48677c6fb0 bee9ff7308762f7ab05933cf4443e3c7 379049 +ad0219a9-119d-49da-952c-b90c425069ac 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Transcript Fusion RNA-Seq Arriba 776cce15-88cf-47c9-b2b4-cb2ba9dbd255 78fed56c49ea51ba5477097665513dd1 4622 +5679dd35-110e-4099-9a4a-4bdbb8a38b12 fc9801f7-f6bb-4a15-a8a9-1986b499393b.rna_seq.genomic.gdc_realn.bam 24eab8cfa255cf2fe03d05967bb220fe 8155861250 CPTAC-3 5690ba19-ef88-4bce-b275-27f715cc44d4 c78059d0-f010-4e55-bdb4-7a8c7cb61d65 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 3c703143-8b8d-4fc9-880a-534f83d6f579 5f9da83d37a9d52dc447d416d9d0d545 8157494376 +4ac2fd9f-7bb9-4f6a-8661-c3d10e24c0a2 b1caea76-fffa-42a4-8147-c0135dc5368e.rna_seq.star_splice_junctions.tsv.gz a5fb4cb771d244fbb712b7e35013e310 3396423 CPTAC-3 15f6cafe-10fd-4505-8f88-383f9474c493 91cd5d29-e69b-4c71-9acd-3dd8cf7408c0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 177459aa-af72-45dd-a29e-e6790a0a09d8 e4e6029fa9997e8a6d62a549477370db 3438826 +cfae4461-234d-4008-8c74-405d0d4dc0eb 7f2666e7-680a-48c4-9ad7-857a82c9a5f1.rna_seq.transcriptome.gdc_realn.bam 377066f20201e43b4225af5d680488c2 6995007651 CPTAC-3 bd69e879-9ee0-415d-90ef-ccddd9feaf92 0978a8f5-c49c-44f0-a311-d4f89acd522e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 1bf96578-4352-48ca-b131-c77f4095744a 988984a1394d31e9fe747e30884d84d3 8054263551 +d956d2f7-b031-43e9-a9dd-c721a4b50c98 a3d3e991-13ff-43bb-9b17-ec82f73d05ae.wxs.VarScan2.aliquot.maf.gz 4be3e91b3d7d6749cdd19cf63551e275 682239 CPTAC-3 5b767817-54ae-459f-b1cf-837e09025e99 5b71b4cf-7f14-42ec-bbe6-58842e3efd3f,fb83df64-bb73-499c-a57a-9436e26aa093 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 6e225379-7986-4cf6-bbec-17ca29b3044e 323ffc8c6870c9826e02982f94d5a814 823938 +4975fad4-3bba-407d-bfa7-745fc53867de 2d7232c9-23d3-4ec3-a0db-86c0f4ed1268.arriba.rna_fusion.bedpe dfb22fcb4daf2b1e711aa66f868ce65f 1708 CPTAC-3 31ceaaeb-8186-4d4f-8981-d192368ad39a dbd51823-d415-4d6c-97eb-abec7b6349ac Structural Variation Transcript Fusion RNA-Seq Arriba ff0b0897-3074-427e-a226-1aab6ed5935e 65dcccfbe001709a344311d451e3d2c9 1327 +293ad4dd-f359-45ac-9f86-07e5ddbc1f5b 0efa3e79-11e3-4b8a-92fb-8a0448dafddd.rna_seq.transcriptome.gdc_realn.bam c13d12f3bca21d472800cf606961b9bf 8482537485 CPTAC-3 598b1977-3935-41eb-96bc-ac3938cc4e05 49106ac7-b595-409e-8731-343873ff382b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b07522df-a529-48b8-b68e-c95971ec35ac 8e345c33e9b8e78cc6194bec4cd156d9 9577712664 +f46c106f-2395-4ce2-a3fb-fdddc6235f89 1e2f7f07-e667-41b1-9ff7-0a745cfe38a7.wgs.ASCAT.gene_level.copy_number_variation.tsv 9adb4ec9727c13994cc9412c11b6f922 3482791 CPTAC-3 070f4283-176a-492e-b418-ebf292cd37d6 0815b3bb-c9ee-4804-9f51-05014a8e5fbe,b686ec16-3532-4c19-83d2-0f7c2a36000b Copy Number Variation Gene Level Copy Number WGS AscatNGS 55c2558a-7cc4-4d44-85ae-f971a29ca2c7 65edce233574eb63ffe8518958dcf5ca 3442784 +fd615bd9-cf3c-41d2-b0be-d48242b0d280 5254679d-4175-4186-bad1-373586024d27.wxs.SomaticSniper.somatic_annotation.vcf.gz 6b687e27aa17c20ed338f5ebeee571be 805971 CPTAC-3 2171413a-4d2c-4ad5-b539-f231a3d0a2de 4a02531c-43ca-4755-b48a-f9732230695f,0ccfe2e3-b8d8-46f7-9330-adeb25be08e0 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation f3c1d7d0-03fb-4817-aa39-898366deb7d0 79bb258ae9f4346864422d506b5248ac 848202 +e02d934b-75d2-45e2-918c-0b02968d1d2b 7613f8b7-c663-494e-8f8f-21d9c96d6499.wgs.BRASS.raw_structural_variation.bedpe.gz 54942ffcda6bec96ef7c6ee942a8164c 1989 CPTAC-3 3c055f6e-751a-430d-8549-ce873c0e64b5 3ec666f3-df1c-438d-bcc1-555e4c7db92b,e85c33bd-3b8d-4bad-9735-e48f81491019 Somatic Structural Variation Structural Rearrangement WGS BRASS 9218966c-ac67-4514-962e-7940e8ad1564 6497758b511f94bf1f72bd77eee28ffb 5412 +be8ae52c-ae9a-4956-9e1f-98052e43a137 f15d872a-7e31-4111-9d92-5ac813a8bc4f.wgs.ASCAT.gene_level.copy_number_variation.tsv 81484093bb89b8271c79b92bedb7853a 3482764 CPTAC-3 5735655b-b57a-4a27-8fbe-4e4a24150b1c 2425979c-83fa-4c6b-a510-2efbadb018aa,15a8ff7c-4a6d-4c89-ba29-1ddc51583f5c Copy Number Variation Gene Level Copy Number WGS AscatNGS b700bcbf-015c-4523-b073-537591a53c19 ef66f8b2e1597d4a8fb9f224adf1f51e 3442766 +eaf14183-b955-40d5-973f-3054c7369098 30779908-9bb3-4668-88ac-7503c1d475c3.wgs.BRASS.raw_structural_variation.bedpe.gz 3358d0617d8525c36bbe09c1f8274aea 11335 CPTAC-3 5a2a4f11-e9bb-4291-9089-24b5e77d285b 1303ac4b-aff0-4982-a3ba-8c792a57db03,161b063d-d8ab-4135-aad8-d40fc65b7a2c Somatic Structural Variation Structural Rearrangement WGS BRASS 533c9d5b-80d2-4ddc-98b5-71d3d0c402e7 8f9e1766c7c21b0483854f447fa558a1 40174 +b5774a93-6f12-45dc-b2b6-821c5f1d3c8d 704ca5be-cada-455b-8fe4-b84fccd79f86.rna_seq.genomic.gdc_realn.bam 34b48cb96ec31eb9ed085c3fd082b34a 8915063796 CPTAC-3 58024352-41ea-400e-82d6-592f1d7677a6 4902e5f2-7c34-4702-bfb7-b13f494510ab Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 00d40583-1558-492c-82d4-e3a3cd91063a 6f552834369a4709e0f5d20d9a6abf25 8915454516 +44b492b9-5991-4ad6-918a-fec7f6fa6286 1951179a-33f4-4871-b507-f2a449811c94.wxs.Pindel.aliquot.maf.gz 48dc85dfa682a801e0a4532f2320a80e 351625 CPTAC-3 6857e6bf-2a4d-4fb7-a891-04911c72d1f7 7959d3f4-80cb-45f5-99ea-248ac2059877,cfc5140e-1c15-4b9f-83e0-5613e427870e Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation a81755de-e8f1-4528-9c78-017134c4b27f add9f928e22a225daeed872f9e4889cc 371106 +3ff7805a-6b83-4e95-965d-102433495934 c176f25f-5df2-4b4f-8dfc-d74bf1f5b516.rna_seq.genomic.gdc_realn.bam b18ea4b5f8cfaec31463fd3c3c87cfba 8375751610 CPTAC-3 6116ed25-e657-440d-a5b5-24dcd90b0bb5 02356a70-ccea-42e5-9607-33e049aa6bcf Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 9e197a28-a818-42ca-85a5-44f25cda2b31 7106fe12e6ed3855fe39c6fb6181452b 8377515544 +6b7c0f7e-2627-479a-afc8-917876369107 7647659b-f8ee-4a3b-afed-c8d52e674362.wgs.BRASS.raw_structural_variation.bedpe.gz 29c070b0b7350475756fd5a1195197eb 23377 CPTAC-3 a68d6b4a-141d-4c05-8835-e1c0a264625d 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+981b632e-23ed-426b-815a-777f15b2d8c2 bf389316-906a-428c-a0d6-634ed52aca25.rna_seq.transcriptome.gdc_realn.bam a11c274bb28e7d7ec62c0199beac0a35 5562192840 CPTAC-3 d16c18db-df31-4394-a146-c3964ad9b49b 6db0d707-35a1-4925-8605-53f68a97d861 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 5b25cc74-293d-460d-a09b-f26abded9a5e 916e5d665670de63307af39300a1ad21 6301660694 +d9c1e01c-f45c-4915-abbd-29b0862feb11 d29d87d9-4a40-493c-9c8c-bb98e90ee41f.wgs.BRASS.raw_structural_variation.bedpe.gz 176977a575c2e7252bd2b0ef0017ee15 9506 CPTAC-3 be0f4ef1-7ce9-48aa-931c-6c8cf99c4687 bfe5b115-f317-44bc-ae72-595d9a0fe7ad,eb856f0f-f9f8-4ef3-bcd7-824049ed9109 Somatic Structural Variation Structural Rearrangement WGS BRASS fa75479b-6ef7-479c-8088-3add1860d14d 81131a4ec9a5250a5c73fc9049d1efa0 32311 +1a3b22c7-b57e-4492-8ff8-af9389786b8a 5d23d84d-29be-488a-9f63-485154c17218.wxs.MuTect2.somatic_annotation.vcf.gz 117141eb283598aa8a18d17cbcf59967 4283315 CPTAC-3 920b70b3-265f-4c67-afe5-079b073cab03 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RNA-Seq STAR - Counts 5ba4130b-7224-4853-b847-16fdf3f5b883 24380b122974faee5344f0af21d6e568 2987733 +915c1531-539d-4dbf-826f-b0a5bcc318b5 01db841d-9552-4f98-b4f0-b1a0b14da2d6.wxs.VarScan2.aliquot.maf.gz b842fd56c7a6c12c9fd24544e2146f3e 467398 CPTAC-3 3eac8f1b-790c-44e8-80b3-dd3180155ba3 9eb60886-10fc-4637-8745-d721a4f514e5,295863ad-93e1-4be4-b13e-0bbd4ca64aff Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation a7367db9-963c-40c8-8ec9-6e8c23a0800e 3307bed8902ec32f7134bee978ab9f3f 539320 +733313b8-33b1-4ac9-87af-8019a640e986 c7d71541-41a8-4147-9f14-067b0e0809f7.wxs.Pindel.aliquot.maf.gz 16e868dc9fe19b0f1e5173255d46f278 540559 CPTAC-3 f9f0c320-a695-4e5c-b1e9-8b6d013a0a9b e1a71e63-7248-4ca7-a7a5-be2a7c90de9f,c1d8b688-7c23-466a-8885-f6fa38811bac Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation bd56689b-5a1e-429b-b1d7-8969aebf152f 30114ca1f622d068b19b2a09e24fe527 557572 +d32a8a8c-b4c3-40e6-9c2e-550ed0861a3d 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+1b9ab738-1394-4d0f-8861-2db677d16c0c 04dff73d-c1e9-4a9f-8460-511c9636cc31.wxs.SomaticSniper.aliquot.maf.gz 4a7c09758b28e5f914a7bc49dfbe2ed6 331760 CPTAC-3 bab46316-532b-4444-9a46-d70b63b878fb eb7b05e5-5bdf-4428-86dc-c3db5026f54d,cb70b1fc-f720-49a2-bc24-0f14fe2a09d1 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 33371e7f-cb2d-4508-ab5b-de34cb8ddb90 725952f4694b0571b815a8e6d6ded32c 442137 +a3c8ee4c-3f58-4128-833d-e17251776f1d 7dd32aa9-bc81-4c0e-b1cf-d808b0c5d232.seurat.deg.tsv 185afe0300a30817d82658b931fe3446 2202779 CPTAC-3 f9b811e5-9ff0-4aba-aee6-e1d3d71da900 f185a23c-2478-4b0f-b8fa-72d83df685b3 Transcriptome Profiling Differential Gene Expression scRNA-Seq Seurat - 10x Chromium a42ab7ee-4116-4ee4-a072-984dd0d5bee5 3d7c7189609b06dc78a54060468b9594 2818964 +7a0e3457-8602-40fe-a064-c2706b4d735f 3bf0ea33-43a7-4f7f-beb7-1b2556cbdaa6.rna_seq.genomic.gdc_realn.bam d1e4cc08feb8b617b48d6a61e68fab99 9025909179 CPTAC-3 5249c627-50f9-4dea-a90d-d2ea66e2a8e1 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8539e18b-9fd7-48fa-aa10-04ee069d612c 58d98b0d4f37c388826bb9e0fc29b25d 469837 +fa16fe4a-de25-41ea-beaa-e714f774aac5 847e066d-565d-4f22-b906-879092cca658.wxs.Pindel.aliquot.maf.gz b740a95c06e5b2c65d833ef32ed4f0d2 1210236 CPTAC-3 176ac1b2-7111-4950-a7bc-1edc3254854f 875fe663-c1d0-4ea7-825e-a718f4a7c4a2,84a2ecc7-55f4-4985-810f-c38e9258e6bb Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 62065f54-5de0-4a18-abca-d39ca49d254b 7c9e40bd5a9ec40dd7e4edb0e729f909 1239633 +f4be9e5d-dfc1-4902-a1af-7b84cbf10c49 c653bf3e-f73f-486f-b5b9-0917347dfde8.wgs.BRASS.raw_structural_variation.bedpe.gz d3f4cae0cc7c22425f530502c2c1f7dc 5331 CPTAC-3 a3d3b5eb-500d-4859-97c5-71b6111326d3 a8847ec8-8718-435a-a1df-77690c4a60f1,c643b5b9-f774-44bb-bb8c-a6ab9d1e0d29 Somatic Structural Variation Structural Rearrangement WGS BRASS 50abbe31-1675-44b6-9ae4-e02ec189cecc 21405a1edb150a209d953241de1e4ca9 17315 +741bbaa5-4460-4bb8-aba1-dde092299859 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Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 36c31100-9d48-4f43-bac5-376c0337a667 83d0c0b0c56d8114b938999ef3adc31e 36453 +fbe304d8-7715-4b45-8a50-396f7a3d3f3e b44988b3-2906-455f-9a03-98e881ec0826.rna_seq.transcriptome.gdc_realn.bam db8cbf5e22255b1fc8e5767cddb8d3e4 9245106889 CPTAC-3 0c38f553-6892-4f67-b306-40503b8842b5 12930ba9-7a07-49a0-b399-419c7f2e972f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 3f7a96f5-7cf3-4865-9d77-596dc181c697 19842b89cfa9da71effdc7e2fd947b02 10531131546 +2aa8059c-fc12-469d-b258-64a8787e415b 7d3d78f2-04c1-46bb-b1d9-a7c0452c1436.wgs.BRASS.raw_structural_variation.bedpe.gz ec6cb0684041e5bfe5f09972a0c9ea45 4958 CPTAC-3 c6c75c5d-b3c9-4918-8dc2-02849933cd3c 43ec9bee-5438-4c71-9c45-fad51cabea55,9d8605f9-6281-4ce5-a4fa-4399e1902769 Somatic Structural Variation Structural Rearrangement WGS BRASS 686afa9e-467e-4ff9-94ab-59cf7b69e897 566813429b95a614aff1a2c8bf31e6c9 16236 +4de011b5-8f5a-43b9-a5fa-bda41eebd964 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Annotation 1824dadc-b91b-4279-9067-0056be2767db 19e867125422773b7241b4d207125493 736774 +7487da30-dc7b-4813-94e1-72d89d5c484b 84016924-64cc-4deb-a2f0-9f7ab4f0f0e6.wxs.SomaticSniper.aliquot.maf.gz b0014b1ec08dbb2d2413a39f44edd780 746658 CPTAC-3 95ab4d14-342d-45d7-96c1-cdd37165b761 397dec2a-b730-4e76-9f22-cf04d07980c0,08423635-fe99-41bf-96a0-cdea06897bde Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation cf2748fe-1228-4965-bf8a-bc64cb35ca39 cc3cca354e6175c6eb88dd509f951b0c 985636 +b30bd9d6-84d6-43df-9de9-392ec5d81039 c199c1d9-4c08-4a58-9ec1-900a7e67154a.wxs.SomaticSniper.aliquot.maf.gz 26877d53084828d4199b072131283bf9 353866 CPTAC-3 9163a2fc-913d-4fab-b988-5955bee93843 30ae1a29-cd48-4ee5-81be-215510402651,28c09c40-a98f-4641-af84-2405ce473f60 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 695e7a58-080b-4b4c-9485-6c3fd09d773d 43ab16fb5a30cc63066330d98d8998df 426913 +4870297f-21a1-464b-8667-7f566cf8170a eb2b6ba7-114e-4eb9-ad77-7b9b7b71ad95.wgs.ASCAT.gene_level.copy_number_variation.tsv 28f7f41edad41b41ac305f0249fe848e 3481183 CPTAC-3 12246e82-cb5f-4b7e-a6bd-a120e000db49 b8fe112b-ae62-4c1f-8856-7599e851035c,d9ec0e40-42e1-48d3-a525-cf03f9c4aab8 Copy Number Variation Gene Level Copy Number WGS AscatNGS d0c4096c-8a70-4901-bdac-7d1324660e43 d2ba1999dd62d0470c6bc52228b4be7f 3441263 +897492e4-734c-45ea-bdce-c075b6d0757f 091e72d9-1724-4ba0-b062-3cb1e6454d70.rna_seq.chimeric.gdc_realn.bam a8bcf0e9b70ce5ff427a73f21cbebb0a 56395663 CPTAC-3 070f4283-176a-492e-b418-ebf292cd37d6 bc3063e0-2ca9-44e1-858f-13fb74d8dfcf Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 7bd87519-87f1-4d89-a89c-f61440512af3 c8ed8a5a17de0871e51f0a28be3e0e85 56390524 +8b72e513-b1e7-4fa7-bb5f-e88ca32cb1a6 8fbbd712-a59c-44cf-9b83-66b9ae5e2f74.wxs.Pindel.aliquot.maf.gz fe17e761c2732865c2a52106948136f7 151658 CPTAC-3 5705efcc-b48f-435c-8a28-9e0d407ecadd 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36acd2c4-a3e1-4640-b785-50b70b4904cb edb54afadf929ada7d4059e1e311b7fd 450036 +c9b3f6f8-d1df-4070-9f93-0b8dc1eca68a ea1aed9c-1c9d-4042-baaf-fa9f7eae9a90.rna_seq.chimeric.gdc_realn.bam 9a6d10816d2eeff2e2dc1bd22493cbc4 213807358 CPTAC-3 669a57c7-0ecd-4b39-8a2e-a98a830bebed dae74986-4350-4915-9e62-860604ac81f1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 53e19a78-bbe5-418f-92b1-abccb59e5d35 46936f8a8cc36e1d91a727588d3e2dde 213785879 +a70666ca-fa10-47ae-9fe2-da60f5cf59b8 774d7424-c5bd-4a91-b1e2-54b4eb24852a.wxs.SomaticSniper.aliquot.maf.gz 7a7a922a83a2524fdfa8c8373eab8089 963589 CPTAC-3 45669b98-2d82-41e1-9c1d-0de3f98cebe1 596f83a1-5e9c-451b-9087-fbb18efe8447,58cdfc92-0d6b-46b3-94dd-28f1a5a247dd Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation c58ad5e7-8914-469c-9a50-5f551214a450 f007fc0786e55c63817a9f40198b48b1 1258600 +c228e622-632b-46be-9e6b-d5b3d09ad84c 41846815-8f27-4373-b3ae-1dcfbc2efee5.wxs.MuTect2.somatic_annotation.vcf.gz 1731fab0432e18e026aec8985c7da270 8522021 CPTAC-3 ad9a7ce1-9f9e-4092-8eae-493297289022 03f0c034-cfab-4864-bfcf-fcdeabec1493,91a5b1e6-a1b8-4402-b8ce-842c721fdbcc Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation c7db959b-8324-40e8-8fc5-eb3f43649bfc 48176bd9e27238202f6123185418c0e0 9434142 +f0eaccce-a2f0-4afe-bc81-ebdd47497b48 f9369e9d-24e9-4204-8912-8dc66a51008c.wxs.MuTect2.aliquot.maf.gz 12b9ab3ea075a9c7aa3260b8a653f3cb 1883493 CPTAC-3 ac8ce1f4-d475-4da0-89cb-30067c2a37d6 32d6f5b7-d2af-405b-9e18-3d437fbcfeab,2603d898-8eb1-4f1d-93cb-c401918fb57f Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation a6a25b7b-a57b-4295-b759-4a5c68a005e8 c0baf0b54efe3f9d501178e5859d42e7 2192503 +7b57cefa-5507-4195-a685-dc6b52afac56 730cefc0-049a-4677-9f41-6b55c74fdd79.wxs.MuTect2.aliquot.maf.gz 30f53aa068eb7cdd5073704b6c476bd4 1687175 CPTAC-3 1afc3a78-4e91-485c-93e1-43f17738f530 f14f7aeb-9755-4228-9d3a-8d6404e4b3a6,a0658f29-2a4f-43c0-8d17-e351ea2f073f Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 37ca73b7-366e-4297-89fa-0c35cc2fad08 900375e013fb87d35505e2423dd6ec87 1993945 +3b9ba39b-fc86-43f3-a860-d58f9d84ee6a a6ffabd6-4f50-4265-b8df-1c8c3976de7b.star_fusion.rna_fusion.bedpe 86198b09e2f557d48a21b5c2032611db 447 CPTAC-3 0625c920-3378-4eee-b53f-650e4192d29b 35ae3dd2-7236-46b7-9c39-f112ca2d561e Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 318fa17d-7155-40e0-a898-2330bb43e10c 6e5690795ff424264402ab9d2661b62b 229 +7237c114-afd7-4f81-96b0-cf4a9d168c84 82e0394a-eaed-4f88-b53b-12aac9ac6f3f.wxs.MuTect2.aliquot.maf.gz 56636221d5357490a525617176b0c887 7342040 CPTAC-3 2c779d6c-f661-4621-9e3b-f9705da342a1 f5ae7b0e-9213-4424-a10e-7f1383d33b5b,ef72c57f-f998-4e9a-a563-b5969a93bcd8 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 0f827025-4790-40b2-b14f-ae828887ed3f 8baf47f805b923b28aea119912330642 8744309 +fef4c53e-7e1a-4a3d-a050-b044a36dae5d e9502559-d22d-4e64-996f-4e818f3bf3a9.wxs.aliquot_ensemble_masked.maf.gz dbad070fb7dea2a484ec51ebc32bfb3b 91735 CPTAC-3 07eacca6-8691-436b-8a5b-b595b6388b5a de5ff6c5-79fc-4c44-9d16-79b73e2e8e06,24b56530-504e-4423-a833-238e49cb0d18 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 50ebae32-45eb-41df-9a1b-79cfd31a069f db7b91b29b1785f21f9d09cd72211398 112909 +2edd84a5-d8c9-44db-8d59-6c4a3f066445 8f308362-88b2-43b0-a3bc-3d993330b430.wxs.Pindel.aliquot.maf.gz d96df47a3549939c28a8d48a2ac72e0b 441268 CPTAC-3 0d0cffd8-81b5-4c1d-8012-658c0f6f0c42 2949e6ba-cb37-40b5-a7cf-09978da51025,24dbe8dc-e176-464f-94a0-006aa43bee59 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation f8a5108f-9041-441c-b1d7-acc3ce83ce4a 11f558d287026d2eaed4e7d2140fd5db 474846 +d1e792f1-27c0-4488-b711-162f6be3619b e5ceeaeb-b44a-4470-a471-4e554dd0b81b.wxs.aliquot_ensemble_masked.maf.gz 43900b00e1cf2c9b5702ec87d27247f1 21728 CPTAC-3 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11a60ad1-3e66-42ff-bc59-aa30f5d6a3e8 3049f9240f414d8b747b3a6c9824fb4e 30603819 +90bb9b5f-d499-4895-b178-2704e32accc7 ef5c22d3-4bea-404f-a68d-08e194064a70.wgs.BRASS.raw_structural_variation.bedpe.gz d6982a332c5f72fad3c8fb8f75f57aba 1428 CPTAC-3 f674a0fe-66bc-4b0f-a12c-e025655f8a64 68ccdeb9-9c90-4895-b97d-80761d49f19c,a558ec6d-c1bb-4c9f-ba16-9522c7292919 Somatic Structural Variation Structural Rearrangement WGS BRASS 16bc98e3-2a55-4579-8d6e-81fdfe54441c d34583f6252b7efe70e607ef974f51d2 3836 +d05d89ee-888b-4dce-83e4-a01f35a8ae37 86dd24bd-9594-4a82-9332-10e00fcbedb8.rna_seq.star_splice_junctions.tsv.gz c06c52c63af81ca81f570999141a3dd6 2820051 CPTAC-3 30d5de9e-822e-4794-9a3e-cf1bccf1dab7 cf1391e9-db3f-45a3-8f76-73a2c2da72b7 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 84075c29-fe06-4a51-b31a-a07e90d42429 1e43987073bb7e6818a078783186dcad 2850764 +19b2337c-5ff7-4f25-ba36-4c39f6b4240d b2be1d48-d72c-41f6-84f6-2f3e2f7a627a.wxs.aliquot_ensemble_raw.maf.gz 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Rearrangement WGS BRASS b5ee3328-ff7c-4b9b-a3dd-e215b3312dab 93e704b4a5fa6873b373496db820e0f7 15222 +b1eeb808-3471-49fe-8469-1522572c5a86 1fa6b845-0e08-42d2-8760-21194afbff17.wxs.VarScan2.aliquot.maf.gz dccdba4f5f1f0cfd8814279635971cbc 421449 CPTAC-3 baf87a40-f648-4491-b84f-53284a654d76 19259be0-acf2-4826-b674-fea6f2fe6889,34a91d65-a389-4d30-ba52-722d20799fa8 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation d0609972-9cd3-4823-aab1-78d0d8397df1 866d69b9a42c9cc5b114667974f70452 497414 +2e6ad10b-5341-4580-9f29-4d394b95955d 0a197a84-bb3d-407f-9415-25ee1deb56ef.wgs.ASCAT.gene_level.copy_number_variation.tsv c5635293a93bd6eb8c84932904ff7315 3482800 CPTAC-3 d2ba6170-58a2-424f-974d-403af8f2f6e5 991614e1-a4d3-44c4-a18a-dca3a34f009e,93bfb3d4-6285-4819-b54b-96c9994f54d4 Copy Number Variation Gene Level Copy Number WGS AscatNGS 25117db8-234e-4317-990d-7925b1a8c429 8b4fb6df6e9b9c4aa55bf0282c05096b 3442790 +6762e93d-6556-4db1-a2a4-803a94229b59 d31bec57-bb27-4dfd-aec6-09c8d855dff1.rna_seq.star_gene_counts.tsv.gz 5d1a895c690c5a6b2eb7ec451db3f397 428576 CPTAC-3 530a241d-798c-4c3b-93ba-5cff08469d25 405a77a1-3f89-43bc-aa70-9e2279a3f535 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1ed26c4c-1637-4bcd-993d-7e887ac34f71 9775a71a736254638a5ff002eaff5054 4239580 +2f6cbb2f-debf-4284-9bef-f898e76e3e11 05705163-5be3-4cf6-8b80-a39d71e465f1.star_fusion.rna_fusion.bedpe 3a0416538b0e822f661c77deabde9485 3125 CPTAC-3 1c2653e9-8ba9-40da-a0f6-f5f06508d26a 2055d83a-87e0-41fa-bfe2-1992c0317442 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 04f7cb3e-7c2f-4622-925d-78f6114fba04 44eb210a694e3d90cf53638cb5922038 441 +f97f4219-3474-4d2b-9afa-3d60427e0192 2a753a13-2fc7-416c-a274-7605590a3671.rna_seq.chimeric.gdc_realn.bam d38b0eaac376a39a0ef162a7232b5134 42438743 CPTAC-3 dd2d4fc9-3422-4548-85fe-43e5b8da5ed3 cdbee926-9a4d-4c0d-8a01-89005a32b6be Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ce282f7d-9298-48da-b378-a79d1ff3474b a76d8ebb7d5b9ad66356142d515b351f 42440802 +e67372c3-9e7c-4dc7-a3ef-beb1261b2e5c 815843f3-02fa-4b53-b147-5835654ee64d.wgs.BRASS.raw_structural_variation.bedpe.gz 3dfdc6e9a5433f6249c1fceef75bd0b2 916 CPTAC-3 7dccdaf9-f427-49e8-93fe-0a5dcf375db8 d564a1a0-e99a-4998-8fa1-df8128379f65,90388559-98b6-4014-b201-f64e4965649b Somatic Structural Variation Structural Rearrangement WGS BRASS 9969eada-cb4d-478a-a538-868f172d1d0b 18d81e87c14290f9a357c9670c0f0ed4 1973 +92cc4315-8e11-45dd-9507-d4441ace1a81 7c9aa3f7-24f1-4834-a75f-2d0ac67f8fdf.rna_seq.chimeric.gdc_realn.bam 7b04951439b4066386e03f23888a4f04 38754977 CPTAC-3 a60cf9e4-f150-4a9a-a9b7-4083431e4bb2 d885eae0-6714-4ca3-9cff-bef883ea6b1c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e42e0e24-9dfb-4ab3-8e7a-c0fb69a11166 624a49084e6c29dcc37cab4bd408d690 38744954 +02a88a2b-9c37-4cc0-9e94-9126e844c4b5 13152278-8a22-4a99-bdbf-2ef4d59b63c5.rna_seq.star_splice_junctions.tsv.gz 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Variation Structural Rearrangement WGS BRASS 7c7d2b15-c796-4f99-9913-fb3010831ced 800e269c22c953168495bbb7df1c92d0 2190 +edcdbf96-65d9-4965-9d83-0e39b9839f13 fae5dbee-7b93-404d-b014-4b6e7ee7dcd0.wxs.MuTect2.aliquot.maf.gz 0cfebc51c209d9d699d957dca0e7e19d 9352957 CPTAC-3 52153098-f1b2-47fe-ba4e-88ce6d51a6ca 82ccdf4e-4527-47ca-8151-7e1248f1da09,1561b97d-8c8f-4fe6-a244-06452760074d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation f5805ff0-31d2-4409-94fd-7000e2c95390 eadb1ec3bd3eedb96c5433cfc94c8875 11153939 +8965636d-6d20-4bed-b4c5-4ff15d447143 4bb167e1-3136-4a01-8efc-595a7ec6ece1.wxs.MuSE.aliquot.maf.gz b5a73d97725a2cf9cf79e34e5eb5ee60 178253 CPTAC-3 52153098-f1b2-47fe-ba4e-88ce6d51a6ca 82ccdf4e-4527-47ca-8151-7e1248f1da09,1561b97d-8c8f-4fe6-a244-06452760074d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation f5c6ca1e-7c1d-40b3-8e0a-8ac0e39f9bd6 149c3ddf6b39d700e0f48cb3c759dad0 227264 +70fbf891-2c23-4067-8249-c52ecd3ec20e 2e68a490-516a-4cd9-b98d-9923759fd955.wxs.SomaticSniper.aliquot.maf.gz e473c61c23c6a55348c34b37365abf75 1168649 CPTAC-3 d52a195d-7d63-4eb6-81c2-3c473ba57979 18e6a6e7-b473-42cb-adb5-e8745643eca7,5baa4fd3-9295-4f75-aab3-d51914261e92 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 40dab487-283e-4d98-96af-286565adc894 137c8bd5086483bc774d4adb8a3b1a95 1572657 +e44e04da-0095-47a3-8898-806b07b89ab7 8adff636-319b-4494-a7c5-dd36b39856db.wxs.aliquot_ensemble_masked.maf.gz cf6a95149f528071ed078e85ee0c6273 24240 CPTAC-3 bdd09566-f2ba-4771-82eb-9c30563dc669 73d8e268-db73-4fa5-b943-4e99a762e81a,5a75740b-ad5b-4f29-8b9e-1d011f50aac7 Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking e01041e7-f573-4cbc-8cb8-7023ebb65114 1ae04e8bbc42b8395b728e6282257676 32851 +ff1c5bf2-247d-4cf2-a897-34e28ef2f736 8df8e3c7-f33f-4bc0-8e2a-a1d0549e9106.wxs.MuSE.aliquot.maf.gz bb54b6585a5c9dc75e2e96a6c0d5e3fc 145641 CPTAC-3 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Annotation d4c684cc-9822-4459-9c8c-c55a396999e7 0997680a7e6d4420f7e4e918f59d18eb 554062 +1595b37b-eb31-46d7-8b8b-e47e8cb7d9c7 aee8dd8f-1d5c-467a-8e89-105dadc0ee23.wgs.BRASS.raw_structural_variation.bedpe.gz fc60348f437868797a3926338cea01e0 2025 CPTAC-3 40311512-c531-402f-900a-222e4572296e 925f395c-dddd-4771-834b-3cfde3dc615b,e56a3c11-9494-43fb-899a-fddd5544db14 Somatic Structural Variation Structural Rearrangement WGS BRASS dcf91c0a-f1f0-4b74-a446-aa3229115dfe 2fb064a880c5d307d70078527d2fa070 5683 +918e94b1-3589-41cf-abdb-bc816cc5aa7d 277a859c-a47b-4829-9d31-e19c92be12ce.wxs.VarScan2.aliquot.maf.gz e432192668f0c87d7b7ab55a9996c98b 97144 CPTAC-3 46fd5848-ddb3-4cbf-97ce-c94d72910679 8b168954-0caa-4c8b-8c1f-0521f4da89ec,41359c2a-31d1-41b7-8c7e-226fdd046c56 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation f42c6b4b-01f3-44d9-a93b-ff6cebdadeaf 1dc79ae6c513cbda3f7fd05f81e0bc84 120080 +a18d2c94-ed17-400f-898c-0c9019bfba69 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Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts afe08253-b95c-48c8-a856-85e65603ae30 9cbc81fc3939e2722356f5d7ef5041c7 4240811 +e014e188-b03f-4dff-a0cb-177d2bd802ce 629f1823-fbff-429a-883c-3528d77f98f1.arriba.rna_fusion.bedpe 3150c45224e49476107e3e0924405f8f 2822 CPTAC-3 ac1dcb50-a6e2-4956-ab3e-2278d51bc4e1 6a3a5e69-3b24-439e-9603-c0e24c7736ea Structural Variation Transcript Fusion RNA-Seq Arriba 693e3e96-dc03-46bb-9be1-a4f69c4a75f0 ec4d6850aeb3899450d64dbe50e4c615 2722 +30501d04-1bf9-412a-86f4-f084b844cb8f 2193a12c-a863-41e1-9513-da7fca07dfc1.wxs.MuTect2.somatic_annotation.vcf.gz 82e88f1ff5e26d11ea909fe4953e29c9 2581122 CPTAC-3 fa75026c-662b-422d-bde0-de3155671dc0 5c9b7a28-b4f0-4576-be00-c401024ca6c6,b04281f0-de7e-4330-b977-5149689f34ef Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 615fa17a-9602-471b-8fbf-857cbca47b24 2554ac95e2d63265ca8174e82b8fc7f6 2739248 +0b2aa5a0-231a-4505-b169-843fb07bcfd0 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5f8e818e1a5305ccd31c24a135cca447 3441248 +e48de123-c250-49ab-a095-188c70d362c7 444f22e8-8f1b-410b-a51c-50d05d24a3b4.rna_seq.chimeric.gdc_realn.bam 834888cd9faeb0662b0b0d6ded991cea 26903002 CPTAC-3 4116957b-9204-4f4c-89ab-404024995258 a38f5f51-7d68-45dc-951f-015b6c604744 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 608ecee4-e391-4b59-8482-97d9c315bd91 19772f9759da203d085f7e7b5e99fe41 26883999 +02578139-aef8-4257-a6d1-5f661c3dd9d7 68fcaee0-c557-45e8-ba4c-ce18db3a617b.wxs.aliquot_ensemble_raw.maf.gz b848ef354a6fdcf3b2cc080294700540 232953 CPTAC-3 cc553c22-31a5-4b14-9d25-a38eea2ae88c f2683a7b-a49a-48af-91ee-c9185ea9ee2b,00638581-641f-489f-b9a7-e3977e1f205a Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 070f6011-cbd5-4a21-8a5d-a45253bbe472 113c30670a65c55c644ce80bdd1b2562 326596 +a9937c5e-390e-48b9-8bf4-7d75112b3069 8dfc33c6-299a-4f78-914a-40be532d191c.wxs.VarScan2.somatic_annotation.vcf.gz 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Somatic Mutation WXS SomaticSniper Annotation e5f9afe8-d513-4a51-a7c3-8d959d40be5a 6220280cf7f10732ef381ee38392d37d 615018 +ccf46896-02a0-4d6c-816d-cf266c6e0642 5e2237cc-ab96-4c1c-8d0a-19168405309a.rna_seq.chimeric.gdc_realn.bam d1f98e162b56cd272fbee6dea07857fb 76280449 CPTAC-3 208b87e8-f96f-419c-a659-c94a1b4c12b7 296a7602-6d26-4bde-80aa-b3d2002dfe9b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 7e933af3-e1c7-4825-bcba-9826a3124890 28dacd861e41352938a1fd3cc8a57478 76255951 +21be2996-62fb-4a22-a8db-50e58283eb71 ad8cdfb4-fe9e-46e5-b530-fe35808dac29.rna_seq.star_splice_junctions.tsv.gz 6ee620b0f8e715a92c4a8d4604d48d5c 3229370 CPTAC-3 32b7854e-de74-42d6-a4ce-f4b304956ee9 40c7784d-bef7-47b6-a417-74e29122e927 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 7c4121fc-a067-4577-adab-620b44c8b359 77efa732c02ae10a78523c6f7b4ebf11 3266104 +7ec0122d-7f00-45d1-8c4d-22bb5bec7c44 0ffd04fe-fc2a-4979-ad98-d37d1a1cb940.wxs.SomaticSniper.aliquot.maf.gz 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Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 55c55916-1175-49e2-8cab-b1525c18c432 de2c516f842c04514562026cb5aa662a 12159907215 +e94ddfe9-03a8-447f-85de-72eda16877ab 0708d606-04f8-4c06-83c2-f33a2385c0e8.arriba.rna_fusion.bedpe fbae29073552638870792e9a9dd7e57e 3184 CPTAC-3 90656d95-f719-478f-9538-3d1388e09a61 fc387d39-f4ce-44f9-a0ac-47007a2395a9 Structural Variation Transcript Fusion RNA-Seq Arriba e1788f90-7e08-4b25-9ccd-37005fa1101a 45e02b7d5734d4458393b5368d9c3500 3811 +ff9eca2a-21cd-4750-b01f-d501b299de01 c203c907-5bea-41c3-b5f6-5c8ff2942257.arriba.rna_fusion.bedpe 78f3479940325e1fa48d7cca45ac73da 5886 CPTAC-3 d7c0e370-f778-4995-963a-7a55525b2d76 b2f9e69e-3d83-4109-baf0-da243af87794 Structural Variation Transcript Fusion RNA-Seq Arriba 9711aa7f-d0d0-42db-8692-ab7372ec9753 96dac057740d22df3873235a3703a230 5075 +7a4d58d9-01db-4f40-9eee-823444edf6c6 71663d95-cfbc-42df-933a-7283dfc2b422.wxs.MuSE.aliquot.maf.gz 08caf4e44fe88de76077eec9c9a40fba 117023 CPTAC-3 530a241d-798c-4c3b-93ba-5cff08469d25 d74c1adc-cddf-49a1-a6ee-a6a65b6ed320,391d63f2-9a50-4c5e-99c2-de8ab4715a43 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 958f9487-12bb-4ee9-9710-5b3e6b6ceef6 6ee2051dc91b4ac610ac79e1629e2285 150815 +c1b4c82c-2c4d-4315-8a16-7df4dfd08fd4 8cf875bd-c38f-45f3-a961-8476ba9825e5.wxs.MuSE.aliquot.maf.gz b7c869dc3e356dbe84c95da446513b0e 157996 CPTAC-3 ec1b3344-5165-4303-baf7-7b06019738a5 eef16b63-5ce4-4ee8-89b9-d0992a129bbf,20b71c93-a724-4d9a-8b99-2d86c1af4005 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 1f00a9b3-fc23-40e2-8496-d0b308cf06c5 8e2f0ef4ba0ac85691939b39a61ad137 208504 +ed38ceba-5b21-4392-af77-5ca661c390a0 8877a139-ab0b-41de-8735-cfd37225febb.wxs.MuSE.aliquot.maf.gz ad1d2eb58339ef78236c182083463577 440642 CPTAC-3 178f9a51-566a-446d-a28c-2d16aee4d42a b93f9712-3ac1-4bf5-b4c0-a3f584dc872a,bdc38930-0dd6-4f39-a41d-56574c4b93ea Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation ea4e1982-4332-4acb-b2c9-f3b8f0750738 a3406fbd1c9915e57d6fb1158c42ad6a 498862 +acf6b203-dc4a-4e7e-a979-0b6e2263fd35 0989a582-2149-49e3-b164-a62c8fc54002.wxs.MuTect2.aliquot.maf.gz 8b78ed479b30facecfe17dbd6749ffed 6011091 CPTAC-3 1a53c571-af1d-4c79-be44-180cc79e0d4f 474dfea4-f2db-44d5-9f00-98c85f07f20b,d4205a17-5d31-4f86-9a43-4631df1263ab Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation d6b8c17a-7ab2-45a4-897e-4ee448c7b38d 2d85ba5ff2776574a783dd412551f629 7273353 +00d69d77-1cf5-427c-b121-09f183b7ac31 2f8da567-aecf-49fe-8d57-8d9afd95b8b5.wxs.SomaticSniper.aliquot.maf.gz 8dcaa4337b022a9168afd3783fe815fa 524240 CPTAC-3 5657645b-d839-4035-8e69-2a9c78232cdf 5d74c4a0-a436-4a24-958e-ad94a253a4bb,492c07b1-0c0c-4b13-b2d2-db8a6694d819 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation a8c39988-a395-432f-83fa-42dcc45fc694 cc494848e0e73db3746261846b272783 638486 +445bcd7a-dd3a-4519-91c8-91a4134df9eb 97ea7b91-d82b-4e7b-a3cb-7efbf379010d.wxs.aliquot_ensemble_raw.maf.gz d8a60448cbc6586d0c1e77a9d89ed6b0 227211 CPTAC-3 5690ba19-ef88-4bce-b275-27f715cc44d4 f912ddc2-0ba2-4be5-aad6-aa64ad5fa1b4,6eea291f-724e-4891-a6d7-a1244823d6c8 Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 0adc09ac-97e4-4ec3-8c48-fbfd033e3b95 d16c29ec04c98d6a3c3dcdbc7d4b7140 289239 +8499f5e8-92c1-4eee-8e58-ea6df6aa52b4 a5d0bd44-3efd-4105-a842-19c7134fcaab.wgs.ASCAT.gene_level.copy_number_variation.tsv 849f098ddfb808390b71d156366db86b 3482800 CPTAC-3 98bed41e-96ac-434b-90ad-cc7223998602 0ea25eb8-290a-4a16-a5db-b5b4c4be0e32,db37ef3d-5f8d-47c4-9f46-2ecafb8ee37b Copy Number Variation Gene Level Copy Number WGS AscatNGS 78a111fd-3887-42ba-b1ee-a5764947cc3b ef42765d6ff79c5be5375ccff990ee28 3442790 +df597779-ef59-4e6e-b705-d24a3eac8a80 22835fab-1068-4709-b804-73eac48b110b.wxs.SomaticSniper.aliquot.maf.gz c8d328036e67a6fc7e8b46bc7f456da0 1746626 CPTAC-3 0d0cffd8-81b5-4c1d-8012-658c0f6f0c42 2949e6ba-cb37-40b5-a7cf-09978da51025,24dbe8dc-e176-464f-94a0-006aa43bee59 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation 40c787b1-01a9-40bf-8c05-c6a6a55fa319 2b20f0995b13caa0f51fc5b0e9802322 2189573 +805f75cd-309a-45e8-8933-4f7d527f53a6 04a6e934-3b65-4608-af5f-4685332c2c38.rna_seq.star_splice_junctions.tsv.gz 5e5251c3a87ca2bea5552d03591399f5 3362397 CPTAC-3 3491e1f7-0c09-42f8-b20f-2a6d32426c64 374db546-5748-4389-89f6-8f9d15e9db64 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 266bced9-33d3-4205-8669-57589bd4305f 323ed204ced3f513b2abbf154bfb4b8f 3400925 +ffd481cf-d05b-433a-8b0f-3b5e500687db fe705727-6ffe-4b1f-bdef-ab05a5053492.wxs.MuSE.somatic_annotation.vcf.gz 3bdd0c6c77d9ac5c831999f96c91b8db 131006 CPTAC-3 c615b7df-0d08-47e1-81b5-0b40dc6a28b3 fe5e1dd1-ea01-4ff5-8019-c8d372a33339,3fa66b09-0381-4234-9176-e70c8b4f7338 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation bf8a364f-668d-4e83-88fb-de18f25b7cc2 4bbeeb0f4624a2f454b44d690b9579aa 133989 +2e47a41b-e3d6-4c18-93c9-f2fb916731fd 73c5a713-f894-4d8f-abb0-f466ba6559dc.wxs.MuTect2.aliquot.maf.gz 33ff7b9fff81a34bf94610e13503ac28 4592899 CPTAC-3 73f0fa81-42e4-40e4-902e-8f5a49a34d26 48f1b9b8-4725-4465-af3d-a86822eac545,90fad112-7ec0-43d1-9293-731150d95deb Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 2803e78c-a74d-48bd-8ca3-be0047a17dfe ff8f4e29ab6a87dd78c0583746c1cf5a 5807668 +f170b9d4-4de2-421b-8555-34da43ce13c2 55c6929b-2d15-401f-a217-369049835aac.rna_seq.star_splice_junctions.tsv.gz e20875067c692d63a7bfcc3f7f04caba 3022966 CPTAC-3 da4a0eed-b755-49b8-96ae-31d3d396862c 8f9416f7-24c8-4625-b035-bfcdc7c5daa0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e018f391-3dee-4b4e-ad1a-7464f21c298d 204f3e1033cd907155bd974eb7998cff 3062101 +da497dd8-b40d-49f6-97b5-f4b8b4ee5eee c889531e-1807-47ab-b880-55afe5997d75.wxs.Pindel.aliquot.maf.gz 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Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation ed223252-8c2d-4151-8f55-f876eda50699 430ee20adf481907c2685a23aeb9d5e5 2870934 +e7829d60-1155-4bf7-a400-a87065798508 84d8364c-4275-4d46-94a3-40b1de1116a5.star_fusion.rna_fusion.bedpe 2e91ef6f8cfaa14cf67cd82cff842d68 900 CPTAC-3 911b53d3-2a6c-490e-b1ea-c2990b9ad26a e21af149-a3f3-47d8-88d4-91e9fb64a536 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 34416be1-7ccc-4cac-8fa0-0c0a167de370 074090cb3c5d55431c847558ea0cde31 942 +56b86b04-b9b6-4128-9613-c799897905a1 67f9e837-2e8b-481b-bdd4-75868462ac47.wxs.MuTect2.somatic_annotation.vcf.gz 6d12563cf0e798ee489a43cd3d3f1917 2719600 CPTAC-3 ecf94643-4d27-4a4c-a19d-4f7aadf75957 07144067-5157-4e9c-87e6-ae39734624f8,3b453860-03bc-4bb3-a378-8bc60b00762e Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation dcfd3738-36b9-4fba-ab4e-88a2702601ff 08c845b3e81b9c11b5ebdddc2121d649 2945201 +8e14a2c6-e7f2-4dd8-9705-a10a61df0e04 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2-Pass Genome f31fb85f-491b-4455-a279-2606bc3754ba 0f488a4f07905e84f0c86d2350b9b775 8535126053 +948d1330-7160-4ae0-8af5-d55374224ce9 afcbbf88-9760-4a57-bce5-09ee577acdf9.wxs.MuTect2.aliquot.maf.gz 0063aa196889a24698df9bc28127b396 1888216 CPTAC-3 f3e8711f-1b67-4c71-8fbc-9834cb749fe8 5e39c390-85ac-4582-9f12-a6792994fc69,735d360a-8d51-45b9-817e-d97c12e86c0a Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation d575fe98-5b22-4082-ae64-5b6cc8204774 a0097a76aee7ef5bc77aa6e75d1f23b2 2194476 +4350a58c-0a0c-415e-aac8-0dbec50df1c2 6f16860a-aa73-4f92-b81f-a6825e336c6d.rna_seq.star_gene_counts.tsv.gz 5759b7545089c98be7a277f1095fc43a 422661 CPTAC-3 2219ac15-3505-4a31-bf22-72f17c670f3e 2f256d82-3292-46ed-895d-1dd93157b9cf Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 3419ef02-f1d6-442c-8e4b-97f94540f650 17b409f41411733f0bfa7910411e0d87 4237293 +f4af5937-10e4-4cc4-bb2d-77d9d24bea5f 81b6f0b5-4820-4e02-821a-6b47de5f4e8a.wxs.MuSE.aliquot.maf.gz 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Annotation abd4827f-0568-4cbe-8e30-d16d6b83ff39 28810fd3995ad345768565da8af5f5ab 155964 +7779c8ce-277e-4cd7-9974-2b0693710906 6a838960-e276-4873-8e0e-59d0b2f68b85.wxs.MuTect2.aliquot.maf.gz e837ae348cb85c92afec4f1041db49be 2216334 CPTAC-3 cecdc0b2-5587-4061-b290-3496fdc4dde6 161e1a4d-b9b1-42fe-8399-2bc263936720,0a7bcec4-396e-4a43-a17b-fca1aebf4e5e Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation db07ec95-550b-4ebc-b329-9044a9c93d97 18c1c7fa937b36f154bfc2bdc6d25597 2596450 +8e3e6468-cdea-401d-8da2-7a8be7db5cdb de3cef6a-ea55-435d-93ec-bac0351a0489.rna_seq.genomic.gdc_realn.bam 1378a8eafcdb2d51aad3c3b209538e08 8012173222 CPTAC-3 66a96642-003e-4c56-9a48-adc3ea90292d 4ab7c4fd-0030-4364-9000-792fe1ca535f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 4e609d4f-1156-4bc1-b3aa-aac412820bbe 8908c4a404b9496f11ae6fd498dfde4d 8013111817 +16adc6f4-4523-4b50-bbd8-113021958ae0 8a5a5e32-0af1-487c-b77c-459219fe1c38.wxs.MuSE.aliquot.maf.gz 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Annotated Somatic Mutation WXS SomaticSniper Annotation 9952a4d9-5436-4b51-896b-b61f9d4f72fd d25cc86dc391f9beefe0ae164bc12b3b 376287 +a20770e9-695c-40b2-bda0-1f999a9b9de3 e42a4996-663c-4e2c-8a2f-d0a9edd66b15.rna_seq.chimeric.gdc_realn.bam d3f2d96a81d1d080d11ae745defdf6de 46116413 CPTAC-3 8d1b1bb3-2633-4a22-a8fd-19c07931ea46 aba40a2f-6d06-4f27-88e5-132f94e4b169 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 10c840ad-128a-4902-9b06-506ac4d77b25 fb9dc71e6dd6d2d68c7f51165533216e 46108124 +43512add-4ed2-4838-93e7-9619712e3b1b 75835434-7f69-426f-a8bf-5da214015944.wxs.SomaticSniper.somatic_annotation.vcf.gz 9e2f3aa36f996f2b09d5ce716d5a12b5 666357 CPTAC-3 d2ba6170-58a2-424f-974d-403af8f2f6e5 4b842477-f45b-4b95-81fe-f99660014989,93bfb3d4-6285-4819-b54b-96c9994f54d4 Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation ca3804b7-a207-41ab-8c9c-ea60d468e985 529f1a4d60077f1ea2b78c0c18df0139 696887 +6f904d27-3d23-4d28-bc88-9987aa726378 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Annotation fff4fb65-4f2c-44d3-a1f0-aa58cd8b2115 7e85de17eba3a1c0bf8649f31c214f2e 11566591 +7905f197-6c33-443e-80f6-f80fdb5d5831 4ffd9f2b-97c6-4148-a34b-e420a9d41592.wxs.VarScan2.aliquot.maf.gz 5414d9e5e7784744165418d3e7714fbd 384383 CPTAC-3 262b9dfc-3d6e-4e7d-9469-b9bae4f82393 b55b7dd3-d87e-4112-a433-cdfe50201ed6,c934aa94-bd1f-44cb-af1f-1ef429ef6471 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 870964fa-fd8c-4546-a712-d7c85d770a32 0725cde8c51cdd69fc47b088ed06f832 472825 +cf5a8d47-5d9e-40d6-8815-f2816f3e1ef4 69ec2802-b090-4cc0-8cb0-b3eb40dc74d4.wxs.aliquot_ensemble_masked.maf.gz 4537af2fe304cf9e75123eba86d09c68 104807 CPTAC-3 bae31638-f9ed-4298-89b6-e74422d84ffc eb7cddfe-2246-4542-8756-06d1b3f872d6,0ea1f237-cdc6-4d6c-a4a1-15caadce1ebc Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking d5d5b604-391b-4f68-a954-969bfad07340 ff07cab81350540bd68ca7852c19d02b 128070 +963efbfd-621f-442c-a419-74224578a874 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Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation b33baee3-06c2-4e4c-a8f1-e4d06b8a7b2e 23216b4272214ead5c1884e1b8a9d026 133371 +b3ba5108-df62-4c99-994d-9e3a6121e15d e914b160-e919-4693-8dfd-b45430a3d54a.arriba.rna_fusion.bedpe e165160fd22f340df5762875647a2b7a 1401 CPTAC-3 67d29568-8cdf-4b73-a942-9a882dd304a4 759c4173-56fc-4b7f-b390-9e1e3bef9bac Structural Variation Transcript Fusion RNA-Seq Arriba a0ff8788-a8dc-4811-9847-23f8646e91ec f1c50df2a2e0d34bbb5359a9c671ccca 1287 +0b961d7b-feaf-4f05-85ff-79eb418e4c76 4e224932-b8d5-45cd-b797-e01459873f86.wgs.ASCAT.gene_level.copy_number_variation.tsv 1b52c56f5b7d3c32cc9708fc987e34a5 3481153 CPTAC-3 454eec93-31fa-4b28-8cce-dfaf87c6cf44 e01d567c-94df-4606-95ff-13d11ca6d24d,5b2ddfa2-94c5-4401-82cc-0234f40efbd8 Copy Number Variation Gene Level Copy Number WGS AscatNGS da8081cf-50e4-4921-ba0c-eb8a38c2ccf2 6a733cc31dc0b9ebabaf2cd74aed0636 3441239 +77232755-b8ed-45a3-aaf8-2b79f51d8ab1 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Counts 841bb285-8c99-4583-8022-238e9a68b080 ab338c7ec71ca6d7a521db91be5bbfbd 3309206 +6ec6e337-c165-4e12-9595-d76d005d81b5 fb0bf1f7-6e3b-4dc0-a779-3782a5d8e8e9.wxs.Pindel.aliquot.maf.gz 6b774bca0d37ebb643d07ad0d0fadda4 140780 CPTAC-3 6116ed25-e657-440d-a5b5-24dcd90b0bb5 9e8bf09d-6c3c-41f6-ada0-0255af5e514e,55b09b6d-156e-41c5-89a3-dcf2239933d7 Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 46f009d4-c999-47a9-ae23-bd24bb346c33 02ec47e6d6fdbe9a9f3e74c3bc68db23 152968 +5956c218-58e2-4705-99d1-38575d7370ed 72146855-1785-44aa-8f5d-eac85a052b24.wgs.BRASS.raw_structural_variation.bedpe.gz 125b7dbcc64a71acede949e48f37e5a0 710 CPTAC-3 939f730c-2fe0-4777-a067-48fdabc82f17 9c061602-847f-499d-bc0d-1761c1964373,330d5168-11d4-4bd3-924c-00a48a2e77f6 Somatic Structural Variation Structural Rearrangement WGS BRASS 259916e6-07ef-4705-84f7-ef1da627590a d16b48d8f98e4e2fc08792d7023c197f 1312 +b2e54909-1713-4c2e-8456-220a00c80c7f 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WXS MuSE Annotation 137d2641-9f4e-430d-9f88-eab8f849743f e433642e4887e8223716e591610b6cef 198770 +20f4fb51-9a01-4ace-b241-1ba6fa2b3c1d c91d0b7e-4f1f-4e58-a2e6-9d3c2e71102c.star_fusion.rna_fusion.bedpe 8a84683fe9c8e1b5dfeb9e1e5afa3c9e 2315 CPTAC-3 9339d250-6cb2-4282-b198-65ce7ae3a091 6b6f1abb-5ca7-446e-9864-c53c5211b83e Structural Variation Transcript Fusion RNA-Seq STAR-Fusion b139d851-fee2-40b9-9852-48dd642900a7 8ddfb140ab1380ed76ad0e2623dfb817 440 +20b1a4d9-fd39-4b38-b955-f8c59d03eab3 3b352e40-34b7-4f8b-a266-e3fb09bf0680.wgs.ASCAT.gene_level.copy_number_variation.tsv a4ba328822fdfc75306bcd83dd237717 3481178 CPTAC-3 a7ac541e-35c7-41a2-ba31-1d7a6b22e0ae b341203a-de92-4bb8-9749-ccb9721ec873,dc7a5978-8435-4a74-a321-9975d1b9db7f Copy Number Variation Gene Level Copy Number WGS AscatNGS 1861fc01-237a-4601-9ef6-d39f59a864eb a0f0f757a74455998ad9f2d86953b960 3441260 +9a6a27a7-bde4-4709-83e5-3b9bf5da1d9e b3bf2aa5-5c1d-46f7-af47-ab6b2f08ff0d.star_fusion.rna_fusion.bedpe 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e2ade3fcb7ec0189dea160f4b9f825e0 153215 +79412a8d-6c4d-42d8-abf7-711901f79539 08ad8673-f7f5-46e2-9bfa-7edc7223511a.wxs.VarScan2.aliquot.maf.gz 864ec2be256eb227292550a96c956ac1 340979 CPTAC-3 6fd49593-9498-4ca5-80f1-4e7ef6b75a66 2986b7c9-3b40-46f8-a85a-4160c153fb79,6374c0d5-ac85-4991-98c8-b1cc0c3160f2 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation ae5d22c0-5372-4198-819d-8bc0f89a647e 2c5f7def5ce5d57dccc1afeb8a935d06 422080 +25974d86-2f3b-47ea-bdc6-d65592216630 44c35ebd-3060-45e7-b136-d6c7b2f312f5.rna_seq.chimeric.gdc_realn.bam 09c27c08676cc40d9afd3d2719f8d310 70376761 CPTAC-3 cefebaa2-f118-40ef-8a54-7608691ebf6f c1d61e42-d4bb-455f-b8c5-e166aa1cb038 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 5a9a5276-3d88-4a59-9a14-9a061469b66d bcfcefd5310001614b4d45b745fe93cc 70366872 +ae936ba8-d2fe-45ab-b417-2b2cc10eaa09 1fe84b04-3a67-4e68-a056-508471b363e7.wxs.MuSE.aliquot.maf.gz f1757215846863edbefc2bdee788c14c 98910 CPTAC-3 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Number WGS AscatNGS 834b6205-c3ab-434e-816e-c4332f373cfc d1c7bfe6665499bf045026e2265858e9 3441248 +6b3bae14-0054-4429-b248-f96cb544e599 73746f82-9ea4-45ac-87d8-bf0e3dc0c2fe.rna_seq.transcriptome.gdc_realn.bam 318d54cbb410d68bb34ffb8c779d7064 10362999327 CPTAC-3 a231aaba-b584-42c4-96a9-f010bd1b3c66 c99f30c5-cdd0-47b7-be22-b271c6c02124 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 273e17dd-68b8-4930-8946-52b721114171 0c90eff0db42aa32269980d45822ba0a 11774516982 +11cb3724-6c47-4a5b-9748-b4876b5ae498 c3ecb817-020a-4d71-b01b-4858f50de8b3.rna_seq.star_splice_junctions.tsv.gz 95303278d4b0aa53377da0fc616378f1 2784119 CPTAC-3 947a6de8-a1fe-41f3-9568-2311f9fa341b f5ef4535-3700-4dd1-b2e3-7460e6bcadab Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 49661d6c-8ccc-4cc2-8c4c-469d0f38e6dd 733a4aeb494abcc0d5bd9304cb148108 2813138 +9bf28e8e-ee05-4e0b-b2ed-0c37ede7e056 3bec0059-5dca-4e65-959c-752dff7c57d4.star_fusion.rna_fusion.bedpe 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Counts 8c954a93-e849-49e1-af63-8bdbaef073b5 7c3088b62540ccec49f43b71faab2a4d 4240557 +5455acad-6d3c-4663-b539-188331c425b0 4677d34d-48b4-47df-86d6-6964033e47e7.wgs.BRASS.raw_structural_variation.bedpe.gz 467171d48ac0bdbb9e48d5324ad85298 1795 CPTAC-3 d2ba6170-58a2-424f-974d-403af8f2f6e5 42e07145-2697-49bc-b54a-a0b8d6252b63,93bfb3d4-6285-4819-b54b-96c9994f54d4 Somatic Structural Variation Structural Rearrangement WGS BRASS e69c4a60-32f6-425d-9eb1-b4c5ee78cb43 bfd3c1240e818c26161e43a1231af3bc 5045 +aaa69805-006a-4066-8638-0d39e23721d8 b85fd14e-2a5c-4c1b-a68b-97014965e34b.wxs.aliquot_ensemble_masked.maf.gz 507979a82e0dbe5f05cf3596c4342509 22486 CPTAC-3 763e0702-8379-4b5e-95d1-a84f412c51e7 a26217f0-b46a-4f44-b45f-afe3874e6b38,c0292a50-51ae-4818-ba05-3d2a9534cf2b Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 81d53369-e643-4447-a42e-5e8a63be5821 cdfe6fda2151600c3875c27382d90c73 28650 +5b4e192e-3a57-4174-8c8a-e1dd0b3d8133 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Transcript Fusion RNA-Seq Arriba aa096796-f9cc-4a56-a65e-9cb285b66b0f 5845fc11edc34211d08b9ae40fea0978 1895 +5311bc2b-c78b-4649-93ad-9215befa8ed7 03b03dac-f65b-4233-9d29-36cb1546941d.rna_seq.transcriptome.gdc_realn.bam e8308f1bb2778850b53b1fd2649b0e88 11011378599 CPTAC-3 3e1176ed-e49e-4d4e-abba-f7c53b635e6f d866d597-2308-4f42-8c97-ab1f9aa7a9f8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome b193b525-1d9f-41bb-b6e9-65b08a14f612 64f14ffb380c57bc6ebde9667364015c 12465037378 +efef6fbc-3560-474c-b9b3-6f3da3bf41ec 4b7eacf2-3056-4ea7-a0e0-75125d3d2f18.rna_seq.star_gene_counts.tsv.gz f23dc03947355ed159a945a032a477fd 420528 CPTAC-3 6e8176ee-74af-4682-9700-e1b2af4f1213 79a919a6-53da-41e0-8030-b4945f1a8143 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 44e443d7-96bf-409b-8428-d81f2bd4e39c 7823ae81f6fbcc402bdcb705e4cbf44c 4232663 +824007c1-0988-4eef-9f66-2d3d48fd5520 437e558e-2a52-4c12-9856-ea8d4417e45e.wxs.aliquot_ensemble_masked.maf.gz 0ed664a3beadc7f33a17900e7a3ae752 14981 CPTAC-3 a7b5ecd7-d16b-4c41-87d7-881c3d53d185 123b51a7-1551-4ff7-99d0-6feb628c4355,faa668ee-186c-4f91-9d95-174aa0475acc Simple Nucleotide Variation Masked Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 0799e19e-f0ba-4dea-ad59-1a14391c0b68 24a760bcda2ff2f93761dbb09c8b5db3 18419 +8a7bc7dc-1931-46d5-a30a-c8c1b26aea1f f6b013e7-d11a-4f22-b90a-c2b1a600c33d.wgs.BRASS.raw_structural_variation.bedpe.gz 652017096b18cec9266c4d86d97def64 1143 CPTAC-3 2e0d5e8b-b18a-49ec-8ac2-9be0c74946d9 3a523f18-8fae-4b63-ac71-d5c0b95b0170,2cc6a1c3-9405-488f-bf9c-3b10bfc84473 Somatic Structural Variation Structural Rearrangement WGS BRASS 2a44fd41-b602-4408-a753-235906ecf939 4dd25e8c7550da239badaa55196324c6 2743 +e8a90eac-1f7a-4ad1-9257-8eee844bd42c 45355e62-5c45-431c-a54a-74d9aa918193.rna_seq.genomic.gdc_realn.bam 78bbada2b70e6db388cf3678281d1ae6 8890495497 CPTAC-3 5a88652c-cc2f-44c8-9e61-e89d46222743 06467550-def2-403d-9aa3-7a3a34f02dde Sequencing 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+f37e3991-7810-4d7a-b031-779070d25c49 dfa97a9a-6af1-4f45-9a43-9d1be9d3d894.star_fusion.rna_fusion.bedpe a1194307bfa1d0042560bbdb1e9476fe 724 CPTAC-3 887df04b-32fa-4f96-abe2-3fb9128ae51f cbc4e222-8b77-43d9-8991-2ad9365e88a9 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 1f985f0c-c6ee-4ae8-be21-5bf2a29b71ab de2c8b98373ec7a3a06ba280e8a4d1e4 486 +e7978ba1-e61a-48fa-81ab-6eb68e205eb0 210dfc8a-9ab8-4dc8-8002-939823690011.rna_seq.genomic.gdc_realn.bam e66fc7947a6bfa0fea9bc140832de1a2 7963264496 CPTAC-3 75893e8d-5e50-4c19-82c2-2f2c208c216b a35c2959-10d7-47fa-b6b7-1c08cbe75231 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a114987a-c786-4695-bebd-bc80091dc09a e00eb05264bc097015b4454743afa272 7964760572 +ce095d9a-8a5d-488d-babd-1d112061798b a1e706f4-b317-438b-9ef9-9ca1262a7133.wxs.aliquot_ensemble_masked.maf.gz 2ad02160911f6cd8812f6d3f5c27dd1e 25577 CPTAC-3 9659c59a-0f56-4c97-a447-d1f8c6fe4e52 b667954b-08c5-40d6-ba47-697814f6e1b0,76279939-7003-484f-b026-9560e85eab31 Simple 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2c7bc9f11cf4c7071169791736a513e1 15155 +3debfd66-3411-424e-b73f-193fda114036 31e6d792-d209-48dd-97c7-4271d8533d12.rna_seq.star_gene_counts.tsv.gz 2a2e9a74f6c6d7aebe45c934a113f3df 426883 CPTAC-3 4447a969-e5c8-4291-b83c-53a0f7e77cbc 9132e3c7-f895-4a21-800c-dda668a465cd Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1f1eef00-cf48-4bf3-b451-1e1a10cc660d 39444e74ba055ed4680189988f78d0ba 4240414 +04bfecf0-70cf-4c13-b71d-7aeb3a2daeda 70208af2-1246-4d65-b9e3-e55de899c945.rna_seq.star_splice_junctions.tsv.gz 567b40468c820f8a832802197fcc73ff 3283744 CPTAC-3 615a0ca9-8c35-4bbd-bdda-dce68e805839 df1b38fb-069d-44f9-a6fa-a8d460ec33ec Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 8a730cda-15ff-4422-8c04-50bb5c984ce4 1cb32d71748e36661f96c6be219d7fee 3320260 +3c6390ac-a804-424a-a809-8a8b904a4812 a15eff93-ff2d-47c0-801c-95c6cab60e9d.wxs.MuTect2.somatic_annotation.vcf.gz 31d29bf3d4f5ef8285d7d1767d8b9a6a 2988375 CPTAC-3 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Aligned Reads RNA-Seq STAR 2-Pass Chimeric 3ba03655-73b1-41db-b467-9026bc7c0041 4c13738a5da4d3f830206f1477f39e37 69063375 +14f1a088-41c0-402a-937f-70474d8047f3 f16b570f-3439-4839-bc34-155649a05d0c.wxs.VarScan2.somatic_annotation.vcf.gz 072020273cbdc440b1aa604087519309 375845 CPTAC-3 ac8ce1f4-d475-4da0-89cb-30067c2a37d6 32d6f5b7-d2af-405b-9e18-3d437fbcfeab,2603d898-8eb1-4f1d-93cb-c401918fb57f Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 4504fd05-69ce-4c83-8346-db704241cb33 7c7a014939cd414865c3aef96deba114 389846 +79c05f82-c8fa-47e4-b3ff-0bd7a4814ce5 e455719d-fdbe-42ab-9a4d-b9acfef2a3a2.star_fusion.rna_fusion.bedpe 937a5d58ba65f39c18a79b880892863a 661 CPTAC-3 aec3c953-dd96-402f-807f-9be99d8a8aeb 1712f055-afd7-4a31-bdce-6ea9b55c36a3 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion 519e9fc2-d2a9-48ab-859c-84ae06ac6e94 926b53d77a8ffb112a768c3427ef7c15 443 +897d7567-fc0b-466b-be8c-94f9df07b5bc 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9b223a82-9714-4c39-a5c1-6115fd320234.wxs.MuTect2.somatic_annotation.vcf.gz 8fcaa7ca9e1e6b7ae8666bdafc012cc9 7208910 CPTAC-3 d79d4830-d55e-4efe-bf00-9543461c7af4 ded35b91-a827-4d01-aba8-765d7ba7e4ac,6acbde3c-8e88-4c38-85d5-8868552a6441 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 4285c35b-6018-4275-b488-dd6c250f23cc 701531810fff3fe41eccab8b23438221 7892532 +169adf16-a041-48f6-8c41-99723cd9e265 9a4e22f4-10e4-4811-bb13-b8ee8a8de68d.wgs.ASCAT.gene_level.copy_number_variation.tsv e220867b83e783bcc74019f8848c1241 3481183 CPTAC-3 c0607363-1082-4ce9-a642-e9b2b903ae88 20730bb0-a420-4cc3-91ea-80c765ccd3cf,b56bd2bb-ba83-4a80-835e-1c42b477fb0a Copy Number Variation Gene Level Copy Number WGS AscatNGS af3204a0-129b-4c4b-a5dc-f327bca5ac0e dad542178509754e8ec728fc6d5ba812 3441263 +ad3a3258-3c0f-4149-a5bb-ef860a22cfec 0f3950f6-d961-4b65-934c-d80e5b3e1e13.wgs.ASCAT.gene_level.copy_number_variation.tsv 4c763b53b67509ca6c816ab18bc2f0dc 3482782 CPTAC-3 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Mutation WXS VarScan2 Annotation 1460681f-9918-4fb8-9772-6e493eff1844 16582da887902c77b5691c41c8241d23 280263 +6e320f16-3047-43bd-846c-92c78658e359 ec4e74d1-e4a9-4304-8bbc-e20d45e7f19d.rna_seq.star_splice_junctions.tsv.gz e633f5dcaa82ce05b3222bd4afbb57a9 2823392 CPTAC-3 5119c0a8-d0ef-4ec2-b58c-0ff9e0c8f1db f68e23ce-f8c2-40af-a8f2-0fb851d699dd Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 96c8572b-ac2f-4269-be65-5b7505b4a458 c30b6b0a5405657f1f6c9d8e699ad068 2856562 +3cc7c35f-bf72-4787-811f-cfdcad61dca9 90f90a98-224a-4926-98d3-acf47caf4bf3.rna_seq.transcriptome.gdc_realn.bam f7dae2e6eb34d5fb7536240341972ede 7705448733 CPTAC-3 5ecaec09-4b90-4b14-beeb-1d419d299a83 21185157-b396-46ad-a069-5962cd59fef3 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2d2d2607-06da-47e5-a70c-ddcf4f9ba1ba 8a049949c181761970f4c22e0838ee95 8818970873 +72604955-4654-46d5-8f09-ccd175db6008 e40b9be0-b281-408d-91ae-d4442e161568.wxs.MuTect2.somatic_annotation.vcf.gz 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WXS VarScan2 Annotation 14992154-b526-49b0-9b51-1999ba018d6b 00a5951f7d1e45d2fe3877758f07640b 380561 +852c5919-354d-4c01-b38d-3bc822d2e18b 79c9828d-6aa9-41df-a608-e9132d8030ea.wxs.SomaticSniper.somatic_annotation.vcf.gz 3553b062db06358c0a2d77c1fb82b877 1115769 CPTAC-3 b9aedaec-788a-4f8f-8d56-773745b802b9 e6e1c2a6-27c3-4d55-87ed-6cd0ab0fd6b6,0d1a19ed-b1f4-4d0f-9eff-5922afcb6cbe Simple Nucleotide Variation Annotated Somatic Mutation WXS SomaticSniper Annotation d6239122-2c46-4a72-8b16-dc947c82c494 544e503ffd0bf9decbcf3b0a0dab4fb2 1123790 +27cb1383-3201-4e07-b25d-fc15060e45f1 08e34e38-aac1-43b4-b243-9d30c58226b7.rna_seq.star_splice_junctions.tsv.gz 9821a252ed9e2fc0f15a2757bbf4ac6a 3253005 CPTAC-3 3569f880-3672-4b78-b675-c1c2c0a43d1a 2bc43f48-0905-4772-8196-4c44362af840 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts b1109906-3d11-40e6-9724-30210044596f 3d2d3b2fad5fbc95781872be57d1c12c 3293040 +1d137c53-f623-465e-89fd-493b07b5d4c8 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RNA-Seq Arriba 5c95c0ad-66fe-4129-8ac2-d621a8112a6a c41c6a7a832b9ead06885817f6d684e7 1356 +d62fe518-ea99-4b81-92e9-6d054dfa9967 85e72beb-f199-4cfd-bd2c-242dc094f89f.wgs.BRASS.raw_structural_variation.bedpe.gz d41ed08e2957231890e4e865c2cd435f 2357 CPTAC-3 28d777f2-f4c8-4853-bd28-1bba94f2bfa6 65378d04-9290-4314-80ef-7fa63d18b0dc,dfd8f485-55b8-4973-9abb-f79f190eddb3 Somatic Structural Variation Structural Rearrangement WGS BRASS d99e64e6-4ec8-46a8-81cd-fdd9b47b43b8 a8adad98d180612d54f845030d972e1a 6818 +38d1f4e7-44fa-49ab-b345-d57abb715ecc 315aafd7-94b8-463c-9fc1-7f05dc43b395.rna_seq.star_gene_counts.tsv.gz 9e671ecd227cb9be9b73f3c61e28502c 411789 CPTAC-3 e2b3a9c3-a646-4f73-95ca-40cba74f8084 696abcce-ec1a-4b95-9f94-f199f2c0565d Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 04a95ed6-a66b-4a95-9b12-da3b48ab7ff6 8367c4ec3a8d2ea148a4504493c880eb 4223494 +7e8a0005-1a28-4339-b4a2-82fe8d7d177a 5a8ff570-b770-464e-911b-99d78104d9a5.wxs.MuTect2.aliquot.maf.gz 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WXS Pindel Annotation af59a9c5-cb83-47c7-9546-723131d11d6e 293e6690f52244a18340f24a26aa791c 725195 +e7c61d78-1660-41cc-92a2-7c1abe703728 416acb5d-e620-486b-a109-fddf5030b5d8.wxs.MuSE.aliquot.maf.gz d82b1ccdcf78ff7c98599bc008d11e82 340573 CPTAC-3 3c0035cc-7cf7-4319-a5d2-79c79c4fe9f5 7d8b1cc7-e9d2-406f-ad58-80a02eb2ad47,2998d128-cf02-44f9-a832-ee94ce2d4d56 Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation 3814f4b5-b2e2-4f1a-b3b8-9f92df2edaca 0073aa61bac0b85c5f9ed3bf7d12a722 394311 +1aca72d6-8ca3-43f6-a5bb-c6fdff138a3c e8120835-d5df-44d4-a475-63a46e7dbe28.wxs.VarScan2.aliquot.maf.gz 97abe665c7d2dbf01dfcc9e59f1bf373 1375699 CPTAC-3 ddaab412-1171-4704-8960-85d85835e219 8c244af7-4d0a-447d-8da2-af9d147718aa,7df399c7-9281-4eb1-8e1b-9d88c80e5881 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 47ec377d-09d2-469a-9fbf-4ca3b3e16230 adefe4929b76768361c2490637daf291 1638778 +99573c16-1a9a-49ff-8d2f-b9d8581da688 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5b0ca67cff65a0884b3b8ab4d71544bf 4244178 +9cf1c41d-a42d-4f62-88f9-349163868c5a 55c6929b-2d15-401f-a217-369049835aac.rna_seq.genomic.gdc_realn.bam 8b8ab8f86fa9308ca594b5caaa70976d 7754530812 CPTAC-3 da4a0eed-b755-49b8-96ae-31d3d396862c 8f9416f7-24c8-4625-b035-bfcdc7c5daa0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 2a24a34f-8f94-438e-9c80-122aac9d5e92 2f3a020b372a653f43fe1771850ab74e 7754072494 +43802f4e-224a-4889-a301-a7f19a71708e 1ffd043b-9c83-49c1-a302-ca93b95ed085.wgs.BRASS.raw_structural_variation.bedpe.gz 41f2b8deb48b910ace9de60bfb6be0e8 2152 CPTAC-3 dbc7d02b-6c63-4961-a8c2-8a8b811d8d7d 04647a29-ea3a-414e-9087-cbc7da3dc358,3fd5c3cb-602b-45a6-af9d-08dbd550b3ed Somatic Structural Variation Structural Rearrangement WGS BRASS 5b522af9-3797-4cc8-afc1-a5f864cfb789 d74458497e4b9990eb23f5e0143100c6 5836 +dae6d01d-3b85-4025-acf3-b8c5bd5e3082 98bc321a-f1de-41b4-9584-77f02c142cc2.wgs.ASCAT.gene_level.copy_number_variation.tsv 95cd5ae7340afbf515b010cff981291d 3482737 CPTAC-3 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Somatic Mutation WXS MuTect2 Annotation 44da81fc-788f-4141-b007-34baf82393f7 89780d796a23ac9ecd403db2dec02203 3743659 +31d7dc7e-0035-42f7-82e8-2bef93e1cafb 1081074a-a14b-4b2d-9f6f-9726c0be6eb1.arriba.rna_fusion.bedpe bc0c394ce9538266dcc60dacc73dcb90 2944 CPTAC-3 8a2a211f-4ef7-4aa8-bef3-ba3c2803661d 9e98a4b6-d3c1-4be6-abf7-8c3b23660024 Structural Variation Transcript Fusion RNA-Seq Arriba 77cbb43d-3447-446a-a7fc-9c49ea9d0b01 bff601b6393ba817ee37c3be12271400 2043 +86496ff7-997d-4e3b-b4b6-496d071dbd7a 9d180de4-6412-43e5-898d-4f61f1f8cecb.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 6f0fb9d7-64b5-4737-913c-1ac7d2a116a9 aa4b1d34-d650-4d6d-beb1-29960c9bde17 Structural Variation Transcript Fusion RNA-Seq STAR-Fusion ddc9ab87-81dc-4c50-8c3c-3acf22b029f0 6e5690795ff424264402ab9d2661b62b 229 +2561f06a-315b-4cb9-a136-c4ca93171ca6 140686fc-9fbb-4de5-b634-0e0f924efcb4.rna_seq.star_gene_counts.tsv.gz 48b7cdf91084f47d990d3f13220286bf 420098 CPTAC-3 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Somatic Mutation WXS SomaticSniper Annotation 16b880b8-10f2-4e3c-99bf-461763709746 3a38baeb2d06411aeb0d062c18c2d2d6 1164033 +fbc818b6-ddef-4266-8e86-250f77dc75a1 44c61555-ff38-44a1-b308-062fbb9c4291.wgs.ASCAT.gene_level.copy_number_variation.tsv ac1b23eee0386386395384689dbbe1a3 3483026 CPTAC-3 5023cef4-3bba-44ef-ae7e-8ac30bd19412 30383780-fec1-44e6-90a3-ef9c68d6ff62,0d55ab95-104a-4c9f-bb3e-db6ec1ccc1dc Copy Number Variation Gene Level Copy Number WGS AscatNGS 85ecfadd-648f-4e5c-8244-e9d8337b0c23 e585a62e59e3565cbb390d12c68b3843 3443064 +dcfcbea5-cf9b-427f-a84c-f32fe6dc38ed 53291716-0c8d-4540-a355-b34975ad046e.star_fusion.rna_fusion.bedpe 6e5690795ff424264402ab9d2661b62b 229 CPTAC-3 1afc3a78-4e91-485c-93e1-43f17738f530 99d7de39-a684-4871-9642-fa73ff1a33fa Structural Variation Transcript Fusion RNA-Seq STAR-Fusion c74fe789-8b62-40f7-b16c-2f83237a7410 6e5690795ff424264402ab9d2661b62b 229 +4d47be48-c4cb-4e34-b701-07ecef9e1249 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Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 3d70d90a-247f-4d8f-af0f-77647570bbb5 0f11fe0361681f4195815271ace40ba1 9896505295 +eb11421d-4dac-4048-b8c8-049a6c5f2bc1 cb690e8c-ecc7-4d6a-846e-9b8f371ed4ac.wgs.BRASS.raw_structural_variation.bedpe.gz 49d382369e57ef02a11182c48e23d63b 13741 CPTAC-3 14a063c2-41c6-4fc0-b334-22b4a0c4c1d5 01090fc3-17f9-467a-bee3-662bb4e57820,977a93e6-4351-45fa-96de-8cc607966272 Somatic Structural Variation Structural Rearrangement WGS BRASS 583cb1b4-6790-49d6-88e6-866cb1f803c9 626c7bfa583eca037a0ac89121bfca8e 49154 +6a73aa07-ed2c-4c89-8734-6fe36abbe44e 7bcd9af4-57da-4721-929c-4d41cf5ec475.wxs.aliquot_ensemble_raw.maf.gz a21d956c353b0dd88bca9c0350b8ae6e 173375 CPTAC-3 295393ef-f637-4783-89c2-c9ce7635c030 8b735522-06d1-4074-adb7-0f326c2842b4,9616e8d2-5da6-4585-877b-be3056794e29 Simple Nucleotide Variation Aggregated Somatic Mutation WXS Aliquot Ensemble Somatic Variant Merging and Masking 77f23609-cd0a-4a6f-8674-7c0dca0a98e7 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and Masking 3a5d7e97-318b-4e35-9555-4faeb479dcbc 78ff40ec2bcf106d6acf867940945e74 102602 +f3a77f9d-8a76-4993-9e25-b331799817ae df7dc0d5-ce18-4b94-bceb-d5488a8b1240.wxs.Pindel.aliquot.maf.gz cabeee892e4c0ad04b1281e5a4388b14 39879 CPTAC-3 a7b5ecd7-d16b-4c41-87d7-881c3d53d185 db1a7dad-b66d-4d4f-811c-4692fdf6fbcd,faa668ee-186c-4f91-9d95-174aa0475acc Simple Nucleotide Variation Annotated Somatic Mutation WXS Pindel Annotation 6c35bc17-e0b1-4f62-bccc-d115aff730e6 08b4fe8edc0fb699a2f938296ada0e28 46277 +bd15b1a6-748d-4561-b410-35c66663f789 2a1ae9ce-af3d-4f95-8f7e-4f51a9094895.rna_seq.transcriptome.gdc_realn.bam fc718601b541fc69e2750d667759f0ed 9761683876 CPTAC-3 7646aff6-ee01-4e5f-b08c-71404b817cd7 fc67a81a-e459-4391-b965-b3734bc593a3 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome ab655e77-80b7-4fe5-8014-538f00f27fe0 4b25a9c7d2f4586457825e9c8f2f4ac4 11206180008 +e1656692-8d3e-48af-b54c-03a412358862 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Quantification RNA-Seq STAR - Counts 145264e2-26cf-4014-9a26-4b8c2a685f21 0a5c70d2ef5403d8814afeb4b2237e2b 4235093 +948745f7-fc11-443a-86ad-3bc0bed22eba 44c35ebd-3060-45e7-b136-d6c7b2f312f5.rna_seq.star_gene_counts.tsv.gz 8b7d1b49a1064229b6ed0546327c6f15 431875 CPTAC-3 cefebaa2-f118-40ef-8a54-7608691ebf6f c1d61e42-d4bb-455f-b8c5-e166aa1cb038 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts c6200c1a-383f-455f-bccd-16da70eb78bf 2f5c154b0d7dc88989a431942d68d576 4242961 +7b530c9f-c714-4a1a-ab05-570dc16366e2 6927ddad-f09f-493a-b8d4-e74aa82d3d61.wxs.VarScan2.aliquot.maf.gz d1b020b2c3b87d47e21f520d92f7a8c4 290554 CPTAC-3 2b1894fb-b168-42ca-942f-a5def0bb8309 e1743cdd-69f2-4643-810d-4f1c677560ac,f38738f1-ed43-4824-9c84-b23a66d122b2 Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 2774a4ac-0c4f-442a-a4d8-8fea11282a3b 2e20b5fdcaa59f3735280761009527a1 350623 +6c60adec-eb21-4c5a-944c-8441e5d0ba82 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Annotation 03d657e7-c5ab-449d-a31b-2646c5013c25 b53fe632b49948eab4a8802127a90f2c 201674 +e5392104-5786-4c18-bf65-2e41851d366b 0641eae8-6ec2-4ecf-a9f2-2c2ace98004e.wxs.VarScan2.aliquot.maf.gz dd442d3ac8cd3b20886b2dc68ffee0fa 85865 CPTAC-3 dbc7d02b-6c63-4961-a8c2-8a8b811d8d7d 04647a29-ea3a-414e-9087-cbc7da3dc358,3fd5c3cb-602b-45a6-af9d-08dbd550b3ed Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation 24e8c13a-101d-4392-a3c2-24f3c3dd26fc 05b1c8592aae09a56789d687a90f75fc 109764 +2ab13c73-1e37-414f-b791-041e2c81aaed ee8aeefa-9eab-43fc-a077-e94177558892.wgs.BRASS.raw_structural_variation.bedpe.gz 1d162a97d126dac4ff33dee0cd157065 2304 CPTAC-3 410b95b4-6d38-4c25-91ad-c09f2c34325b d47d42c5-c6c1-4788-b66f-9e4eb2854c67,abd00977-e5b2-4ea2-9840-a0cbcc03e13c Somatic Structural Variation Structural Rearrangement WGS BRASS 047cf17b-79f9-4ffc-b297-2fffd3c3200c 3cb5771a3a61cdca172d92863afc198a 6695 +f293099a-5f5f-4cea-acbd-0145bb45fc2d 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Simple Nucleotide Variation Annotated Somatic Mutation WXS MuTect2 Annotation 219a39ee-d318-4521-aa1c-a2f72a3fe5f7 7505f760ef63b4b67123fbac0851c218 2122302 +2f0ee30a-c387-4984-aa01-3b151f3fc30f 514ab55f-b19d-4b83-8ef2-e506164cb1de.wgs.ASCAT.gene_level.copy_number_variation.tsv 77419e0cb4d1eab8c27dded7a20b34da 3488125 CPTAC-3 8d1b6812-9c39-4e83-b6d4-8091f9ff6018 b47a302c-4e31-4c79-85e3-ead148c0237b,e7aeabbd-a8b9-4804-a19d-a02b58cb27d7 Copy Number Variation Gene Level Copy Number WGS AscatNGS 13cc8ef3-724e-493b-a1b8-d63ae76330dd f7936dd311a17eb383499cbdc6eafc1d 3448066 +f57c19e5-ff55-4db0-b3af-c0d95af73a9c e7dd3386-eb3a-4bb0-b333-c64620fc7a29.rna_seq.star_splice_junctions.tsv.gz 15c8f2e8a17f4b99d825d207b92f4d1e 3328483 CPTAC-3 d4cf7bc6-5c0e-432f-9db7-659c3a2f40b5 ae6e9617-2369-4201-a9f1-0fbe5e1da88e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f54ce723-91a9-4803-9d98-2863d1213e9b f2023bb66f0344c889b368d89c8502db 3365714 +5640a961-2e6a-463e-aa35-3a3bf56e2822 710d34c2-7886-4588-8d86-973684d2e31d.rna_seq.chimeric.gdc_realn.bam 374fa75ca1607f559c3602a3c56b32f8 113797367 CPTAC-3 f15523ea-976e-4724-a26c-45a65ca7fb8e 4cd8df3f-175e-4c8a-bf32-dfc9490fb54b Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 0a8a85df-a671-4bf0-b32c-250b11e8ff78 adc1cb586de0605a76ebdd106561c8d2 113806740 +8a1e9aed-e7a7-432b-947e-54003344c973 19e63235-2fe4-444c-b968-3598ef682234.wgs.BRASS.raw_structural_variation.bedpe.gz c13b90f467aee82667cd54cfc7c7b472 2430 CPTAC-3 1272f46b-0d75-496b-8f06-cb659d9e22a7 e3b971ec-48d2-431f-ae8b-719525fa1716,f52882fc-8b4f-47c1-bd89-bf72d116b7e6 Somatic Structural Variation Structural Rearrangement WGS BRASS 4507cc7e-79a1-4c9f-92af-45954d2011a0 6f2da3f2f89eb2d782e4897af087fccc 8210 +6557b5b8-134a-4d3c-a800-d9ffcb7160ff 739138de-c675-4c07-9e5e-ec9568abdcd8.rna_seq.star_splice_junctions.tsv.gz 14e3b1b5ac7171d37404e63b9da760ec 3299260 CPTAC-3 8cce8ac6-b14f-4ead-a0c9-d8a56c3dcf90 41ca1f33-edb1-4bfc-8b82-93e061046f03 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts c9d0dde6-fd47-4614-b64a-9783af87b610 9c2706b9259f692a05ed72d06b1c2ade 3333610 +4479c227-16c3-4517-9b39-6958f8378aa0 61b40f91-af8f-4024-b8ed-0cb2e145c3ac.wxs.MuSE.aliquot.maf.gz d36c7013cea92442d4d23d84ae58ad7a 97508 CPTAC-3 17b9c881-5f0c-44e8-8b59-2dfcab443513 ab4e3671-ff37-4ec3-8a7a-9d46b33633e3,6890c26c-2da6-4867-aece-58b9af97bd4d Simple Nucleotide Variation Annotated Somatic Mutation WXS MuSE Annotation e9418ae1-12db-41b7-bb17-654440d2c708 6b19644508c694eb58e9f0943f535555 118301 +fedce434-bc33-4abe-9c15-95ddb1143de9 f236ddfd-7f06-48ad-a283-88136eb715b6.rna_seq.chimeric.gdc_realn.bam 26a6114e04545ae602c06f02c6c18beb 25091872 CPTAC-3 75196629-c99b-475e-ac48-da4385b66b2f 7d00c1eb-9dc9-430a-93e6-dcef4d869fca Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 00ca68d2-a1cb-489d-9e18-aa55763f0306 6762b77ea81f50ed815594f5d22ba116 25085483 +3c42d6e6-0331-48d5-b03a-bdcf9573a35a 16327b34-2cc5-4052-9105-23fc90474acf.wxs.VarScan2.aliquot.maf.gz cc39872048c2fea734f1e457daf91454 672011 CPTAC-3 c894d4a5-42f7-45c3-88b1-901deca8e3b2 c791c2be-5334-4d7b-9ab0-91a698b7efb9,240bbd6e-5410-4449-a9c1-85d5148ce48d Simple Nucleotide Variation Annotated Somatic Mutation WXS VarScan2 Annotation bc968b65-cb04-4bfb-b2a3-91e9e1f74594 f8ec1d6a0a490c9a6e2a8c0fc36e4f23 764511 +27c7b944-6f35-485a-a45d-91b6e328df59 df96e469-df46-4ac9-86ab-86206ee5bdee.wgs.BRASS.raw_structural_variation.bedpe.gz 0c619008939ff822677ede5f30c36633 954 CPTAC-3 239a5fbb-0145-46f6-8ec3-2a96a04011dd 4b79b8a6-8476-41b1-a6c7-92304a41007e,77c492cd-10e7-45f0-a55d-68b7ca8101ff Somatic Structural Variation Structural Rearrangement WGS BRASS ede05985-b015-44be-a3c3-2e34a58e23fa f0f20ab8a11b7e7916c2adb42f17fe20 2331 +c239f094-2f77-4865-8ae2-fe419fe27b64 3329ef13-fd0b-40c7-82c6-6bad8ce7411b.rna_seq.chimeric.gdc_realn.bam bcf23b29698ad4d495ccb144cc223a5c 32755386 CPTAC-3 7e896789-d5ab-4ea7-96d5-9c62b26b116f 86f5958b-f491-408e-a9f1-6d79fb4cb40d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 194b64be-8c68-4a9e-89cf-df9cd544ad82 5f4fa78f22055baf22bc7ae95eadfb24 32739224 +7e9dc05b-bf8b-4934-8cf1-bdfcf7fb4203 03a16b2a-4861-4f78-8fe3-4dd43cf0c6bb.arriba.rna_fusion.bedpe fa4807c3ae5207b993b232316f671c3d 1294 CPTAC-3 8bbfa9fc-6d12-4376-8c42-5cd436ee260b df557db2-ee18-42b6-84d9-e178bcdc3981 Structural Variation Transcript Fusion RNA-Seq Arriba ba779214-8cc1-484e-9105-79be9901b88f cabd8970a54309e9568f98bb8bf8669a 2161 +3e1ba2e5-25fa-48d3-9c83-26deec9434ed 2da81290-5c94-488b-81d2-a4946527c30e.rna_seq.star_splice_junctions.tsv.gz 69ab398c0311b942ef33058c78ab5bc5 3461921 CPTAC-3 2171413a-4d2c-4ad5-b539-f231a3d0a2de 6f5bcb38-412c-45d0-b669-dac7e38dca33 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 66036cc0-edcd-4f61-8e2b-0e3a7b5736f1 39541cb3496c0e2d45730476b141786e 3499624 +3b388590-a819-4aca-b263-3f2dd2e8e5a6 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30c43dfb-efd9-498f-a0b1-4e4f04a96372 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome e95681dc-65a8-43b7-8a38-64134a4f326a 979851b43be7f75acad5c8494d7cf4e2 11013307784 +34a072e1-2f7d-45ee-974f-43537d6f24b0 c5e5ee89-3692-4a68-ac12-a957fff4b430.rna_seq.genomic.gdc_realn.bam f5f06900186f34dd1353e1741db1fe3f 11750022462 CTSP-DLBCL1 f4eae82f-bd27-4fc1-b244-890608724ed0 30c43dfb-efd9-498f-a0b1-4e4f04a96372 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 1db03148-4bf2-4572-bb63-853535a9d73f a7930b36976c49b8c0c760e059c9f98e 11750212623 +c603b62c-b14b-46d8-bd07-a734827923a0 681e2db5-032f-41e2-9142-dd1c398fedad.rna_seq.transcriptome.gdc_realn.bam 60524af3deae26664cc44769ddd7e012 14032637868 CTSP-DLBCL1 7d855b3b-2ebc-4ab6-ba70-00a951bb16b1 9b09c715-be8f-4766-bdc0-15cb84db0d7e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 042789d6-b1bc-4668-9c52-ae8a1f6c0c38 ae9e7376d49db2088041e8fc939c185b 15876654200 +30dc1eb5-252b-4ffe-a165-ddb96b037906 27f73608-27df-40c8-8070-3cc95e5ccece.rna_seq.star_splice_junctions.tsv.gz 6b1a332918b31ae7ba0380d2d811d89b 2278433 CTSP-DLBCL1 aa7c507e-0d0f-49aa-a497-507a43bdeed2 38ca66e1-66b9-4bf3-b345-5308bac4a94c Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts dbfd355a-caf7-4c26-860d-f57bb93bbed4 ec9d127660590bed9066747945c46f9f 2292817 +6ca898be-0422-4c9c-adc5-781dacd87328 2f85441b-0e65-4d79-8ffd-eabec0e548c4.rna_seq.star_gene_counts.tsv.gz 0119c25d3b0dfd8aa505c7c33360b824 398163 CTSP-DLBCL1 f9c586d5-cc4b-46f6-bdea-067ecbb870a4 b0e16770-1ca5-4fb5-970b-8b97912d35fa Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 49e27b2c-a240-4e24-b2f4-02bda6662307 7754c654a6d5b8dbc954308f499780d0 4223475 +9b84e84e-126e-4eaa-bd66-8095e5eb1749 c8dcb848-9069-4c4b-85be-292eb0eea455.rna_seq.genomic.gdc_realn.bam 518fb46a282add5285bde96287a5c8fc 12465036463 CTSP-DLBCL1 9b42ae91-9921-48a0-8cac-e6b637804b3d e10a9e1f-c33f-4125-9260-5b937da2e01d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 9a463b75-e36d-4266-b690-d8473e759ded 285bae2dc125cde8843277d2efe0ef33 12465854445 +1332e9b1-cc81-48c8-a94f-5fabbf116f33 681e2db5-032f-41e2-9142-dd1c398fedad.rna_seq.star_gene_counts.tsv.gz 5ee47af62e58c43487e3c808e01b53af 406612 CTSP-DLBCL1 7d855b3b-2ebc-4ab6-ba70-00a951bb16b1 9b09c715-be8f-4766-bdc0-15cb84db0d7e Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 8350b5ad-af2a-4913-b5cd-2d7b6733e798 1ce1f9f2c36cd99b4d6ff7e5cb07da0f 4230687 +87ee7337-c5c5-44ef-ac5c-73b2d99771f0 8e2fbbae-96d3-4e99-8863-dbb43b8d9a3c.rna_seq.star_splice_junctions.tsv.gz f1d5447c7f9f3856fb369b64aa0b2a53 2739350 CTSP-DLBCL1 59a39f8f-6a36-4d83-9f6d-a7460ceb8e1f f9ab981e-c7fa-44a8-a95c-0dd8ee19f47e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e6ed3b6f-d2ec-4659-97cb-05b2c895aadc 1cd4512bd6604cd938af97bffe356ce2 2758281 +13054f57-69af-4f94-803b-0010093a7777 1cb29fb6-28f5-4a0d-b3aa-a31fa9bd8c81.rna_seq.genomic.gdc_realn.bam f9784a31db3ede1f92ad089e47d18771 7853443810 CTSP-DLBCL1 19ec7505-20c7-4ba2-bf08-4a8875cb2639 4ffdce88-9cf9-4917-940f-85f1ba616bdb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 79553ed6-b038-4566-8ec4-7bff11b4e290 461ae106693eda514eae526d57b63c6b 7853797320 +904f80ca-ffa2-4e0f-a023-5b6b537d5a1b 7fbeb31f-699a-447b-b75f-6a6cd4bcd582.rna_seq.transcriptome.gdc_realn.bam 514574f74c50622376ebfd1d99091e9d 10511463999 CTSP-DLBCL1 ad38dc02-4775-49f9-bede-79e10cc2c5e7 70155e15-8a57-4bf9-9fbf-0310dd55a08e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 26dc9e5a-bcba-4c07-babb-04c138aa231a 7730ed4a52bd55717374c1501bf08048 11897586627 +5760abd9-3a3c-4488-8864-6d0a7af64373 e10bcf20-7db4-46fb-a61d-0e26f3f2e412.rna_seq.transcriptome.gdc_realn.bam 8a6ea07a618f2e5ef5e82bcb68671aae 12425869452 CTSP-DLBCL1 940fcc76-8cec-4ba0-b464-f86b04e38706 a632f675-2aa1-402d-8e41-fb7d6d7c4b72 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 94f8d30f-a895-45d8-89df-ab04822c2432 2d2234a262479556a81d141df11e0d5a 14144271013 +92d172fe-39df-4ff5-b362-8e6728a0a546 af881ac0-7652-4993-9c9d-b90df41539a8.rna_seq.star_gene_counts.tsv.gz 644385ffd783eee5f60727d7b4ada3b5 405091 CTSP-DLBCL1 1c106f72-b318-4dbf-8309-16460143321a 57e8a11b-3c35-40dd-8610-ba360c472291 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 01313c7a-1032-4e0a-adff-39ff091ff401 1e31a85c2f9ce209274461087ebbc3e7 4227371 +3f0b9cff-498d-4676-ac91-bcd861d02171 71afda6c-30eb-41f9-bccd-ea6f12776062.rna_seq.chimeric.gdc_realn.bam 88ac42cc362eea8f24bf0c385c4535e8 43355970 CTSP-DLBCL1 238f9b51-6ca4-4749-bfc8-db51421f6a68 587df096-a9f0-476c-8d6a-d0e34d1d382d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 28c95533-25b3-4073-b8f3-432bbf47a38c fca9906d0eeb87743de8f1d6d9dd689c 43354753 +febe9f57-5f60-4480-9c50-98470667084f e10bcf20-7db4-46fb-a61d-0e26f3f2e412.rna_seq.genomic.gdc_realn.bam a53179cd971a6676db953b7d305e3654 8094073013 CTSP-DLBCL1 940fcc76-8cec-4ba0-b464-f86b04e38706 a632f675-2aa1-402d-8e41-fb7d6d7c4b72 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome c8cc21f5-4a33-45ac-a5b7-67d085d19d55 53d56e1619372f5d4caf057ea4224a1b 8095305880 +5ba3c630-94b0-424d-bc08-452361dfe3b8 b9b8f975-5470-46d2-8ac9-fae47a13775b.rna_seq.star_gene_counts.tsv.gz ee2a755654b65398d00216d604a0925e 403941 CTSP-DLBCL1 1a039fa8-0ea7-4ceb-8847-8949ff47b597 9da96617-6567-4b6f-88e2-01cef6b09505 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts a87b7eeb-9606-4cbb-9ffc-82730eb4fce2 e24a06433768866cb51d0bf6c11c2642 4227976 +f91f3890-d909-4906-958c-ed3c57efafa0 612b8058-b904-4a7f-977b-43142754e805.rna_seq.transcriptome.gdc_realn.bam 602288ab3e681c071877fd8a4a8adf0b 12638560525 CTSP-DLBCL1 24d3d797-ef5d-48c3-aa4c-1631f3fbcb49 01e8e700-d9cf-44e7-9f53-6f621e6b5889 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome ed7add3b-0274-41b4-bcf4-28407f494c4d fa4214e6db3db45636a0309fae62520d 14120286442 +78de252e-8c9a-4625-8c9f-99e57f6d2d0e c467a051-c8c1-400c-a304-1c8cef015684.rna_seq.genomic.gdc_realn.bam a53aa36cd81fb754cb24298162872fe2 15049064799 CTSP-DLBCL1 d3571dfb-71e1-49ee-a0c5-5cfebc791674 5a6f75c2-64f9-4f14-b70e-f11e9b78e18a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome d0251dc3-41cd-486d-abc2-6d16d273f95d 64c317ad5f206d70798c5f60a19edef9 15053015623 +7fb5c77e-2de5-49a9-98f1-1b72bfd0e7bd 2ccd52d8-0e04-452d-a01c-6871df224846.rna_seq.transcriptome.gdc_realn.bam d2026140e3ba1b96b62d2b9180ed2c8b 10909344778 CTSP-DLBCL1 ef939e8e-8f38-43c8-8a7f-9908500632b3 a91390ae-9dd0-44fd-a063-63fae5d05f6d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 84ea0db9-b61a-46eb-b5d8-779f458f74e2 7856415908e22bb19f9ffe476e3c2a10 12489223961 +8ca29063-62e4-4fc4-99f2-0372f6946bd8 b9b8f975-5470-46d2-8ac9-fae47a13775b.rna_seq.transcriptome.gdc_realn.bam 2921b05a2abd456a3e673730f6377a8e 11146139114 CTSP-DLBCL1 1a039fa8-0ea7-4ceb-8847-8949ff47b597 9da96617-6567-4b6f-88e2-01cef6b09505 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 31adc93a-bf41-4d10-aab5-d0e172442895 5b0d637173ccd9a45776f530801f08ae 12522230768 +0836db39-a324-4f38-9a3f-2e5c443a6f0b 7fbeb31f-699a-447b-b75f-6a6cd4bcd582.rna_seq.star_splice_junctions.tsv.gz 26a1e6adf97c00822a46b38791d35339 2653784 CTSP-DLBCL1 ad38dc02-4775-49f9-bede-79e10cc2c5e7 70155e15-8a57-4bf9-9fbf-0310dd55a08e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 68d93c24-248a-419c-b3f9-f0f004e9ff5d 409a3309c1aefa0f7fce1d67e12bcaaf 2673519 +4bdadbb5-6677-4338-87af-8fd82a737d08 675a7253-5116-4bf4-993e-55187294a3e3.rna_seq.chimeric.gdc_realn.bam 964230ac8fb60b4d4273c8830572930b 158955838 CTSP-DLBCL1 4ad1f10e-b45d-4bed-bc99-f3d48254623d 46ada4c4-8368-4fb7-ae5c-2bfbb0ccae46 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 52c4e10a-4382-45b9-bb25-fd40cdc4dd16 892f907bba93c3bdfe2177f5754ba21f 159005750 +296a5ba3-53a6-45ac-9e88-04a1be8c6cf0 7197211d-f88b-4e10-b672-8d15462191cb.rna_seq.star_splice_junctions.tsv.gz 272fe763c07cee4e69a00f5a60984a10 3071241 CTSP-DLBCL1 1ea52221-8c19-41a6-88b1-7c38d9ebde18 32ce1b3a-75d2-48f2-ae76-811abd1696db Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts d558de94-f662-4d58-88ee-153079a889cc 1f61f622e92f944cd2881edc70cbb103 3090493 +1b2b4a1e-f2e3-4c13-9d0f-86341324753a 7197211d-f88b-4e10-b672-8d15462191cb.rna_seq.genomic.gdc_realn.bam a6a2497c2346be49dbf7966588be782c 10861695673 CTSP-DLBCL1 1ea52221-8c19-41a6-88b1-7c38d9ebde18 32ce1b3a-75d2-48f2-ae76-811abd1696db Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome d2d54520-7c7b-4302-a5f0-a599c391b963 0e3f93f4f2f9a1eaa8f4f8b80458524e 10861734123 +4985250f-d90e-4058-8737-63f2f8210bf8 0b486a25-ffc7-4ca1-979f-4957658e0948.rna_seq.transcriptome.gdc_realn.bam 89255e4048dc458ff9a2efb1844152df 11015559338 CTSP-DLBCL1 74ddb751-fe74-4229-bfb6-4a5b4fbd6487 3a464c6c-87b7-408f-9634-0ae6fbb36be0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 7567c666-78b6-4425-b6b8-59d7a9578f91 817db5c07a55a31b3efeb9f522cb04e6 12210784551 +955d70a0-bcee-4f21-96d2-0e2d419c05b7 c71dfd10-2cb5-45a2-9014-552bce17dfed.rna_seq.star_gene_counts.tsv.gz a84a802afdcd9a8bc1f7c0a5d3e04410 405491 CTSP-DLBCL1 8fb4e965-dba7-44ce-8652-e3792a24923e ddbea483-f4b3-473b-86de-d8f5999eaf8f Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 693d8888-f01b-4c85-adb8-3409c892644e f1fea942878ba0818c67017c1e1bb433 4229414 +71277f78-1640-478f-be31-b771a252415e 32a7a7e8-374f-4f68-87a9-8f1a8f4dced7.rna_seq.transcriptome.gdc_realn.bam ad6e99ade9e65a0e6dd3bde134de3759 12013238155 CTSP-DLBCL1 7f9bcb4d-b75f-4aca-b77c-fa163e28547d 01c65105-6305-4aef-8471-cd549882a902 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 71a756e3-0392-4a84-aed7-bda4a92e4d69 9b955778370fa842cd9d94cc4192dcbd 13444728241 +c8171d80-26da-4206-8927-de729c7651b9 7197211d-f88b-4e10-b672-8d15462191cb.rna_seq.star_gene_counts.tsv.gz 29326f0a9fab061f7c08dd1d8f417f29 411214 CTSP-DLBCL1 1ea52221-8c19-41a6-88b1-7c38d9ebde18 32ce1b3a-75d2-48f2-ae76-811abd1696db Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts bbe0e07d-f0ba-4d1c-81bd-79a18f711e53 0c5444033fb600bf58a1e3af548e8a8d 4233685 +e0d52cac-fbda-488a-ac7d-5ff563149cf9 0b486a25-ffc7-4ca1-979f-4957658e0948.rna_seq.star_gene_counts.tsv.gz d9f48e228a688cafb451aba6706c37aa 388470 CTSP-DLBCL1 74ddb751-fe74-4229-bfb6-4a5b4fbd6487 3a464c6c-87b7-408f-9634-0ae6fbb36be0 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 6fab6425-e320-4561-b8e3-ba25e2879854 f7de723d278dc6b94cb51024e0017042 4211111 +8297f7f0-950e-4877-b6e2-759e0f7d192a f141b476-2997-4fc2-b534-63ed5d025ac5.rna_seq.chimeric.gdc_realn.bam a33bda86f1ea443418ec92910fc0d100 163975068 CTSP-DLBCL1 fdc4789f-ab38-4bc8-9eae-4a699ebd5c07 6e993457-d278-4cd0-ae1a-7dd315abb20c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 0a710eb5-e190-4551-822f-193175f2aae2 ebd5c0d023007e64c147568e38a5cf5a 163988587 +91f3eee8-7e6d-4a00-801e-085627bb8931 e10bcf20-7db4-46fb-a61d-0e26f3f2e412.rna_seq.chimeric.gdc_realn.bam 700bddf1d83cd919c8c5f55bf43e7c26 68244936 CTSP-DLBCL1 940fcc76-8cec-4ba0-b464-f86b04e38706 a632f675-2aa1-402d-8e41-fb7d6d7c4b72 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 8587c546-8e31-4b0a-b0e1-ce6003267137 d009b19d3daacb3e5d7de828dca44f3c 68237765 +57fc7635-b522-4a89-9ed1-09163569a099 2f85441b-0e65-4d79-8ffd-eabec0e548c4.rna_seq.star_splice_junctions.tsv.gz cb5c5a4276ce13ff5b62ca12d8461fec 2774789 CTSP-DLBCL1 f9c586d5-cc4b-46f6-bdea-067ecbb870a4 b0e16770-1ca5-4fb5-970b-8b97912d35fa Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts af8a5627-4342-4c15-a9d8-f2368915ead4 6395e5ebc51a851d29cd20c3f9c0a0a4 2793697 +d063bdce-7bef-454a-b1ef-629df83bc882 89b59b00-040c-42c7-98b5-08655a429ac5.rna_seq.star_gene_counts.tsv.gz d0b56e3ec8444fbfa21ff780c44f38f3 411050 CTSP-DLBCL1 8ed9dd0d-da89-437a-a2f0-b03e9e29b89b 8019c334-a159-4c5b-a043-924395acc137 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts d92718a5-e7ca-4275-9e24-4f85a06d9af7 8db4b82c6c49497925d2d7703f9ad8c5 4236518 +fa899c4b-759f-4a30-b70d-49c22faf9e98 8cf908df-36e1-4639-a581-2e85fcca02ff.rna_seq.star_splice_junctions.tsv.gz 595e27dccf68386e4c047f5ccc28b86f 2423798 CTSP-DLBCL1 3abe9621-e76c-4e23-95c4-df7224e537c2 1c7a32a3-7e00-4d3d-9523-15d1918062d0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 7c33e929-b4d8-4b2f-b9d8-d310ccb627b8 07eb39e444ba6947ea01f96273f36bad 2438545 +d951c1f1-c6bb-40d8-9b0c-79c6220b92af 6d542eb2-847c-4056-ae7e-77f95d621471.rna_seq.genomic.gdc_realn.bam fa4f98efd81732d30558caaf604e6957 12068530994 CTSP-DLBCL1 d6d16d58-db69-4bed-9ecd-d728d782cebb b1e4a92c-5813-4a55-97f1-c9f1ff299046 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 5257ac90-a04f-45c6-9f68-1f060dfa5654 a148cc6f4c129005b3ebac6809256cfb 12069394562 +b05b9095-1e7b-4c1e-b2fb-9e78ca9b12c9 e943b2fa-2221-473d-bb40-2cea4b5368f3.rna_seq.star_splice_junctions.tsv.gz f0751ba50c87f33537df22a689422f70 2121216 CTSP-DLBCL1 02643d04-0cf6-4920-b7b7-849ee7b2a151 9bbe952d-c658-4cde-b4f0-e33f1fcbd5d8 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 3c086511-c156-4d9d-9b27-a890c2557ae0 4c30b72a56dcbb4a1dcfe936d8a11684 2131880 +739726ce-f444-4de8-b676-f159b14e90ae e755b027-61a9-44ad-ac75-843bcc6a8d33.rna_seq.star_splice_junctions.tsv.gz 98a5947d989567edd9c0406308bb0556 2618276 CTSP-DLBCL1 1e2211f6-0804-483f-9c37-ca140f9e2869 b424deb7-5739-40e6-bd26-485f90cf3186 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f2b5e917-c1b9-4761-bd6c-1964d4f4641c 8fdbc3bad8b1ba48b78e2775da0f6eb1 2636873 +2f43d4aa-54fd-470c-bac8-4888da9099da 675a7253-5116-4bf4-993e-55187294a3e3.rna_seq.star_gene_counts.tsv.gz 3b9f856d1bda29724c33b7af503b2a62 405482 CTSP-DLBCL1 4ad1f10e-b45d-4bed-bc99-f3d48254623d 46ada4c4-8368-4fb7-ae5c-2bfbb0ccae46 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts d5e9342b-0436-4893-8168-5dea1c86aa9d 28ab3c6c2496561f86c6912abbffdeda 4222383 +d8cc4852-841a-4d24-8d06-217701ea88dc 8cf908df-36e1-4639-a581-2e85fcca02ff.rna_seq.genomic.gdc_realn.bam 5c8b6e6bb992ff9a1b51ba9792e1ce27 12636699705 CTSP-DLBCL1 3abe9621-e76c-4e23-95c4-df7224e537c2 1c7a32a3-7e00-4d3d-9523-15d1918062d0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome d9af450a-0c06-4bd2-926e-e9ecafce9f35 da2e0a11afac635932e07d894d4029ae 12641300103 +718ec816-f124-4199-ab17-c9f8cf2c28ae 5a2a72ad-53f2-423b-a033-e2f71c134f81.rna_seq.chimeric.gdc_realn.bam 1a28cc4fb9551de4d593936d4dbfb2df 134360316 CTSP-DLBCL1 78182973-d259-48da-8f55-a83bfdcf5132 c4d124bd-3f40-49f4-932a-92fb134adc20 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 616ea396-eadc-482e-9574-3052205af05d 4b3fb1a80be3f78d2ec1e6752f3406c5 134348953 +e469c650-3ac8-4019-a860-11335e51b675 7fbeb31f-699a-447b-b75f-6a6cd4bcd582.rna_seq.chimeric.gdc_realn.bam 6f77fe112a2c11b4bd865aae41b0d9ad 39912248 CTSP-DLBCL1 ad38dc02-4775-49f9-bede-79e10cc2c5e7 70155e15-8a57-4bf9-9fbf-0310dd55a08e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e5fd546d-29ea-4708-aaf5-5266c984f9d3 09aeaaf95a0b812ad647c8f07f323f2d 39910978 +16704e95-bf29-4a81-81f4-e8266db24ab6 276569e1-e7c3-4e44-bbe8-d39a6697ca2e.rna_seq.star_gene_counts.tsv.gz 590639cef2abc5633a0270b8a32193bd 385384 CTSP-DLBCL1 f5446fd4-c684-4693-8e2a-3e32a58bff76 0a81b54a-8ca9-460c-bf5d-8589e14862ef Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 836f7476-b2e0-49a5-b17c-269cc1bca8f6 566146f6506226ecfbe05f6506474703 4204287 +6b088eb7-e705-42f9-9bf0-7c3f35cd3e5a 32a7a7e8-374f-4f68-87a9-8f1a8f4dced7.rna_seq.star_splice_junctions.tsv.gz dad5a30b540c644397f7aa5a9d50713a 2935648 CTSP-DLBCL1 7f9bcb4d-b75f-4aca-b77c-fa163e28547d 01c65105-6305-4aef-8471-cd549882a902 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 42776607-83c5-4e1a-afca-6ac1aaf1204f b4643ba12b9070664c7e2421e1651a2c 2958195 +513e5ca2-24f3-4def-8faf-6b38003099a9 e943b2fa-2221-473d-bb40-2cea4b5368f3.rna_seq.star_gene_counts.tsv.gz 607f60095a8048875032f8fadad4af6c 383863 CTSP-DLBCL1 02643d04-0cf6-4920-b7b7-849ee7b2a151 9bbe952d-c658-4cde-b4f0-e33f1fcbd5d8 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts ac3afbaf-f9ba-4165-9b0f-4e8e279a4274 4e04eb50ea1a56e53fc907560807f102 4197574 +ed78c238-07e6-497c-b93e-8697721b97bd c467a051-c8c1-400c-a304-1c8cef015684.rna_seq.chimeric.gdc_realn.bam 4e04d1150b4377ca2457e360c2c34d93 89173329 CTSP-DLBCL1 d3571dfb-71e1-49ee-a0c5-5cfebc791674 5a6f75c2-64f9-4f14-b70e-f11e9b78e18a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric ba63845a-976c-4caa-9f10-6636750dcd22 46a62e0d0ba93280bae7bd6e83123e55 89148484 +8d7dc7c3-709a-45ec-a1bf-c92014d494f1 652a015a-f40d-4ffe-978a-34314745f7a6.rna_seq.transcriptome.gdc_realn.bam 4c51e2e8cb41be0c2f8d3c871415a93f 10137048659 CTSP-DLBCL1 6ae555c0-6c58-4d03-9719-009cb96c339c 5d58c0f8-d4c6-4ee2-aca3-67d1103bda64 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome c8af10cd-bf71-4307-90fe-5e41f68054e5 687c3087831238add6148ebcc9d99842 11153111739 +b71af321-f52e-4a90-aa29-6c7acd263ae5 f698c580-c854-4ece-afd1-e7caee2d1340.rna_seq.star_splice_junctions.tsv.gz 4c6a2782dd79efaea7d5d29ee989e12b 2761935 CTSP-DLBCL1 4234a18e-c1ae-4f16-a7c4-259d7db8bab4 0fb08ea8-01f1-4647-a627-f92c3ee663d5 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts cee47702-86cf-4d4a-9ee2-90800bfabb30 b87c9d54b8fa76bdc0f86d61af1a38d9 2780983 +de681e68-18cd-499d-9234-2f42ccbb2224 0decbc4c-b959-4428-b536-795c225c6693.rna_seq.star_splice_junctions.tsv.gz 960627eaeb71b453f27820256ac9c4be 2759111 CTSP-DLBCL1 a19418d3-4a31-436b-8986-c9759a135b7f ca9db3d6-d43f-4297-94cd-bd18c7a5c205 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e8fce263-80ff-43bd-8f4c-ba842c3edf8a 79a61edd420b3e139f9ea8e797c3da36 2778235 +a543c1c1-bd83-48e4-aa22-5483b436f43a 5a2a72ad-53f2-423b-a033-e2f71c134f81.rna_seq.genomic.gdc_realn.bam 13af4a0e8288c8f20f2256feda117560 13843116109 CTSP-DLBCL1 78182973-d259-48da-8f55-a83bfdcf5132 c4d124bd-3f40-49f4-932a-92fb134adc20 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 390127b7-13ca-416c-ad26-3e3ac50ee393 f7b0186274ceca93bb6935d7c97ec3a8 13844896059 +77b9c616-0790-47a3-9868-31a7e5411947 8cf908df-36e1-4639-a581-2e85fcca02ff.rna_seq.transcriptome.gdc_realn.bam 8b6c62d096f29f78a189ebde1aa7cdc2 10029766978 CTSP-DLBCL1 3abe9621-e76c-4e23-95c4-df7224e537c2 1c7a32a3-7e00-4d3d-9523-15d1918062d0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 161c788f-415b-4ef2-b37b-38c3c5b5a9c2 8c06b5d6876822299b7c89c0e95941da 11133863242 +81741134-6156-4ba1-974b-1c0fd9ca272c 5a2a72ad-53f2-423b-a033-e2f71c134f81.rna_seq.transcriptome.gdc_realn.bam 347c128807d3be4a60204b05260e7542 17744548423 CTSP-DLBCL1 78182973-d259-48da-8f55-a83bfdcf5132 c4d124bd-3f40-49f4-932a-92fb134adc20 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 22fe2862-d665-4042-b9eb-762ab4703282 e6869961bc9400d825faaebac0fb8b82 19825084385 +68ad931b-8347-4893-8280-4e36ab9d8e89 c467a051-c8c1-400c-a304-1c8cef015684.rna_seq.star_gene_counts.tsv.gz 9ac7bc4af0b496ab885589d2337eac68 406512 CTSP-DLBCL1 d3571dfb-71e1-49ee-a0c5-5cfebc791674 5a6f75c2-64f9-4f14-b70e-f11e9b78e18a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 5b787f1b-e2ac-452c-bf32-dc328e85484f 61084ad214f78074d6b8d98b44d3e3d6 4232019 +bd06a000-7ac3-4d66-8b57-36a7f0673f83 2f85441b-0e65-4d79-8ffd-eabec0e548c4.rna_seq.genomic.gdc_realn.bam 8d217cbcdff048a7a19c4572646ff36a 10656176141 CTSP-DLBCL1 f9c586d5-cc4b-46f6-bdea-067ecbb870a4 b0e16770-1ca5-4fb5-970b-8b97912d35fa Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 254b3d41-2e42-4fd8-aab9-227f0fa3eeff c4d9ffda7bd7106e544b56444a9251b7 10656780340 +bead43c0-722d-4cf2-ac19-f03a46624951 0decbc4c-b959-4428-b536-795c225c6693.rna_seq.transcriptome.gdc_realn.bam edc58e08584236a4a4a1f3ecda8e5f30 11950088849 CTSP-DLBCL1 a19418d3-4a31-436b-8986-c9759a135b7f ca9db3d6-d43f-4297-94cd-bd18c7a5c205 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome c3e12d8f-f61d-40df-a38d-91c694efa604 ebf6bcd33315cc8909aac07c11fcc2fc 13341675134 +d4a8a4e8-ce7f-47f4-a300-286801f4f805 c8dcb848-9069-4c4b-85be-292eb0eea455.rna_seq.star_splice_junctions.tsv.gz add00aa279e922aa2a1c432ce5358719 3117029 CTSP-DLBCL1 9b42ae91-9921-48a0-8cac-e6b637804b3d e10a9e1f-c33f-4125-9260-5b937da2e01d Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 3a13c70a-e082-4b15-b41b-f088605408a3 2689e597f4a8f651b375842200258425 3136625 +535fb429-a258-4631-8ef9-c60958015f21 f698c580-c854-4ece-afd1-e7caee2d1340.rna_seq.star_gene_counts.tsv.gz 47f23729b9d85874ae28dfdda3634f49 400646 CTSP-DLBCL1 4234a18e-c1ae-4f16-a7c4-259d7db8bab4 0fb08ea8-01f1-4647-a627-f92c3ee663d5 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 9cfecce5-d7bf-46bb-b4f8-e63f0789fc95 8345cf6daf1e84088e7bf8df48ecd1fa 4224429 +3132b314-d684-46b8-9719-99e7f595ec72 0b486a25-ffc7-4ca1-979f-4957658e0948.rna_seq.star_splice_junctions.tsv.gz 99cb5871252b217c86e70959d8d3c4e7 2540420 CTSP-DLBCL1 74ddb751-fe74-4229-bfb6-4a5b4fbd6487 3a464c6c-87b7-408f-9634-0ae6fbb36be0 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 21ae7548-1ffb-4b51-a7bc-099b15284c8b e5a0426a07d71e45a4aba18e5fadfe10 2557219 +35e438f2-9ff7-4b2f-b06d-f8137f7e80ff 681e2db5-032f-41e2-9142-dd1c398fedad.rna_seq.chimeric.gdc_realn.bam 98661b671aad649dbba4787639d68eb5 119589878 CTSP-DLBCL1 7d855b3b-2ebc-4ab6-ba70-00a951bb16b1 9b09c715-be8f-4766-bdc0-15cb84db0d7e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 66568043-0adb-44e5-a418-7a3d20bcb04e ba4ae23e033d02d666b3ebeabc97741d 119566606 +3e8c34f6-5c5e-48e4-b8de-7a64b79ff9d7 71afda6c-30eb-41f9-bccd-ea6f12776062.rna_seq.transcriptome.gdc_realn.bam 872b632db55998f5aae6910cadc0978b 10337483020 CTSP-DLBCL1 238f9b51-6ca4-4749-bfc8-db51421f6a68 587df096-a9f0-476c-8d6a-d0e34d1d382d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 9b45f911-0990-40ce-bd99-a1abb2a3bd69 b6576bd59b4648381e0c9da6753fb57e 11554349050 +c41ddaf8-0da6-4d96-981f-072e0675e638 2ccd52d8-0e04-452d-a01c-6871df224846.rna_seq.star_gene_counts.tsv.gz 2150f02923d23b53d5df406bee2a04f8 394606 CTSP-DLBCL1 ef939e8e-8f38-43c8-8a7f-9908500632b3 a91390ae-9dd0-44fd-a063-63fae5d05f6d Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 1e776d52-714c-41ef-b1e8-ba5dd8bd94c3 983868a115806c3057a8d2bafaf485bb 4219036 +320cc4f7-5e9d-4c6d-9f73-3d4a658e6d9c 3ba1bde4-a77d-4cf1-8c68-0de5de354895.rna_seq.genomic.gdc_realn.bam 40ec2ebdfe4508ecbf499d168b777d4b 13308886971 CTSP-DLBCL1 e198a237-2675-4e8e-a903-d76b66da8a61 b9464d1c-1139-4acd-810a-f835c0173f50 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 760bae29-00d5-42d8-87f9-9b8e6f3e0e7a 92145380a759f1dbf68f845d625ca0f0 13308915589 +cd98a719-22bf-4b49-9673-3f28fd59aae6 27f73608-27df-40c8-8070-3cc95e5ccece.rna_seq.genomic.gdc_realn.bam 121b559502ab4c22f90540af1d6c59b0 12776124807 CTSP-DLBCL1 aa7c507e-0d0f-49aa-a497-507a43bdeed2 38ca66e1-66b9-4bf3-b345-5308bac4a94c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a44fc860-9b25-41b6-a07c-c0bf0b7a23f1 961935814a85b9a8c1df4b9605bf496f 12777052177 +837b99ad-b960-41ef-b00f-fb484437053b e42faefa-02df-4769-ac74-cfb872add1dd.rna_seq.chimeric.gdc_realn.bam d1af09685f15e368f8452ecb7894fa49 65999137 CTSP-DLBCL1 bd18c252-e23c-40d9-a9b0-98ebe7146f89 8da91347-aed2-4cf9-8843-f784459105bd Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 5b375867-2815-4bf2-a04b-53808ba5b44d 5182916aabb297d2cabe67d841574219 65979245 +86d05452-6dd3-49a8-828a-84be9622f367 227f4026-6261-41cc-bd90-d8e7e2c6a6c5.rna_seq.star_gene_counts.tsv.gz 580154074bf8269078d6b6734773a743 380760 CTSP-DLBCL1 1cfe090d-9a34-4984-a0d8-392ab83635b3 233eb561-f830-481a-9be6-b879d7a2804a Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts c107b120-63cf-499f-851e-ab2a0e8d7f04 e82ff7a2237667da5a485405fe148dc1 4202050 +bceff38c-0f31-4820-9ea9-7dd800a71022 0b486a25-ffc7-4ca1-979f-4957658e0948.rna_seq.genomic.gdc_realn.bam 7dc25bc507355042e2646ff4128483ac 10153084248 CTSP-DLBCL1 74ddb751-fe74-4229-bfb6-4a5b4fbd6487 3a464c6c-87b7-408f-9634-0ae6fbb36be0 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 2112ad72-9db4-45eb-96e1-d0e492a36f79 55a649d4a6c7e01de732d630ab1de0ad 10153943317 +f328aa80-e4fc-4a4a-917d-d66b331b32ab 681e2db5-032f-41e2-9142-dd1c398fedad.rna_seq.genomic.gdc_realn.bam ed80ae99102403506b22ec5ed5ca7248 11019664471 CTSP-DLBCL1 7d855b3b-2ebc-4ab6-ba70-00a951bb16b1 9b09c715-be8f-4766-bdc0-15cb84db0d7e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome e20327ba-fc43-409d-b8d1-796a42e2609f dc0a83c18d4fd01a3f9f6e6773d45000 11020727113 +58e2f675-ff73-43cc-a603-2687734a72bd 227f4026-6261-41cc-bd90-d8e7e2c6a6c5.rna_seq.star_splice_junctions.tsv.gz 0cda1afc9cb45bf93bdea6933be37a8d 1683100 CTSP-DLBCL1 1cfe090d-9a34-4984-a0d8-392ab83635b3 233eb561-f830-481a-9be6-b879d7a2804a Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 34751834-8606-4a2a-9b38-a270a216269f 5f34bd3933876a488701598b5068caec 1693000 +053e44dd-7a62-484f-a3dd-3d4b61434cd0 1cb29fb6-28f5-4a0d-b3aa-a31fa9bd8c81.rna_seq.transcriptome.gdc_realn.bam 43f6c9f9ed4c1049af454dcf45ec0e24 10088657038 CTSP-DLBCL1 19ec7505-20c7-4ba2-bf08-4a8875cb2639 4ffdce88-9cf9-4917-940f-85f1ba616bdb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome dd5c7731-78e7-423d-a308-74ccc42a5d28 a110bf36117f54a00fee9af01eb74c43 11480220416 +3701cb3f-5499-4725-b022-a0cb24e2112a af881ac0-7652-4993-9c9d-b90df41539a8.rna_seq.transcriptome.gdc_realn.bam 52467dce99a784c2131abf2a6a25d6b9 13563264957 CTSP-DLBCL1 1c106f72-b318-4dbf-8309-16460143321a 57e8a11b-3c35-40dd-8610-ba360c472291 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 71b2588e-a0fe-4093-96d4-fbf56ae769e7 5d6088141237764d2cb539f62e19b97c 14830850028 +91e558d7-3aa2-46e1-ac99-62582ee7691c 6d542eb2-847c-4056-ae7e-77f95d621471.rna_seq.star_splice_junctions.tsv.gz 788105248a6c13ecada33790877e5327 3228142 CTSP-DLBCL1 d6d16d58-db69-4bed-9ecd-d728d782cebb b1e4a92c-5813-4a55-97f1-c9f1ff299046 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts ad7140e4-11de-419d-a271-48050bd80ca3 a753029b866a3e6990be6337adac2087 3248339 +97c3a42a-32a2-44a4-8ebf-dd5d7af44c72 6d542eb2-847c-4056-ae7e-77f95d621471.rna_seq.transcriptome.gdc_realn.bam af056c12d2927fab539b0bf7074d982b 13214007498 CTSP-DLBCL1 d6d16d58-db69-4bed-9ecd-d728d782cebb b1e4a92c-5813-4a55-97f1-c9f1ff299046 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2e38bcba-cd88-44a0-8f4b-d1fe42c25958 49d3791f1e0db24cc22c15b4cdb8aa23 14888919094 +7b113f3d-5bbf-4d59-824c-fe8620329718 2ccd52d8-0e04-452d-a01c-6871df224846.rna_seq.chimeric.gdc_realn.bam a7d8ea7ef75ac56cbc1a04c1df4b6e7f 75153790 CTSP-DLBCL1 ef939e8e-8f38-43c8-8a7f-9908500632b3 a91390ae-9dd0-44fd-a063-63fae5d05f6d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 0d8e0994-697e-40d8-b94a-e4e553577f91 408dd563b2020433a3fac90421da43d9 75132800 +5f528219-ba34-409c-9f87-96cda41f0313 e943b2fa-2221-473d-bb40-2cea4b5368f3.rna_seq.genomic.gdc_realn.bam c514c4fd908e22fc6ca32fb2b21aacd9 15917919983 CTSP-DLBCL1 02643d04-0cf6-4920-b7b7-849ee7b2a151 9bbe952d-c658-4cde-b4f0-e33f1fcbd5d8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 978b2c18-9e21-472b-b39f-baa1437ec427 2f3aa432324393b0b3933ef00b91c9bd 15918562211 +c240652e-344c-4470-8c54-f6794d7c975e 27f73608-27df-40c8-8070-3cc95e5ccece.rna_seq.chimeric.gdc_realn.bam 4d440f68456aaca64af841c8488216b2 57380567 CTSP-DLBCL1 aa7c507e-0d0f-49aa-a497-507a43bdeed2 38ca66e1-66b9-4bf3-b345-5308bac4a94c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric e7d7a5fa-d210-465c-b473-fa04ef2ff773 641c7ea7bade265c11caa6007fb37f0b 57375080 +6867e48d-a837-455d-808b-ca48eac36753 c5e5ee89-3692-4a68-ac12-a957fff4b430.rna_seq.chimeric.gdc_realn.bam 7de011bef99512c097409c0bfe44930f 67198477 CTSP-DLBCL1 f4eae82f-bd27-4fc1-b244-890608724ed0 30c43dfb-efd9-498f-a0b1-4e4f04a96372 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 0c0766eb-bd97-4806-8c5e-c40ed4d226e0 56c0c6ffecbd23aad4a536576b8d8d8f 67189195 +62768353-d6c6-47a7-9f79-f772cdfcba56 b9b8f975-5470-46d2-8ac9-fae47a13775b.rna_seq.chimeric.gdc_realn.bam 4536059a097fc221eec2750287407c54 61068263 CTSP-DLBCL1 1a039fa8-0ea7-4ceb-8847-8949ff47b597 9da96617-6567-4b6f-88e2-01cef6b09505 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 7c44a360-0c1d-4fe8-9247-d7d3e5b5fa47 80a40d9ee54edfe4bf02d391a2bef268 61063090 +738b5f0b-8784-4ae3-bf70-c8444dd0bff7 fd392cb1-b4f7-4edd-9383-a6d570fef6e0.rna_seq.star_gene_counts.tsv.gz a3fd7d9ea2e7ad53c12f2ea3c24cfe85 392592 CTSP-DLBCL1 4a69b6e0-390c-46ca-a3df-c34c536cc109 f73419c8-9049-41a4-a329-8d8940127532 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 510533bd-590b-475a-b5e8-e7bb36e7bd32 ca4b280f75b5b867a1d192c3bae82194 4214876 +072c4ffe-3e3d-4c9d-a5bf-6da5ab0d677c e42faefa-02df-4769-ac74-cfb872add1dd.rna_seq.star_gene_counts.tsv.gz 1f8c5ce9540de78074567762e015f735 392362 CTSP-DLBCL1 bd18c252-e23c-40d9-a9b0-98ebe7146f89 8da91347-aed2-4cf9-8843-f784459105bd Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts b3a5d20f-4461-4d9c-8cb5-8bf8fe07d7b3 58a9faee0af19eb2b02f64484132f0ce 4213289 +2b9789e2-0a7f-4bf0-b07a-fc57618c7c61 3ba1bde4-a77d-4cf1-8c68-0de5de354895.rna_seq.chimeric.gdc_realn.bam b8a630c4d8fbbe0ac7d3c88a0fa6e439 108773920 CTSP-DLBCL1 e198a237-2675-4e8e-a903-d76b66da8a61 b9464d1c-1139-4acd-810a-f835c0173f50 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 6305e2b8-663e-491a-83e3-0538e7e9a93e eeec4b301948984614508747d5a6fc9b 108783103 +1c9c2570-8afc-4742-82f8-d0e0e9f78a9b f698c580-c854-4ece-afd1-e7caee2d1340.rna_seq.chimeric.gdc_realn.bam 604cf89495f0120faa1a8b9a759580fa 63756074 CTSP-DLBCL1 4234a18e-c1ae-4f16-a7c4-259d7db8bab4 0fb08ea8-01f1-4647-a627-f92c3ee663d5 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 9db1aa5d-0dfc-435b-b878-edc664f53bc7 058e656e7d27c4b5840574797a2afe86 63761287 +27840a1f-9200-44d2-a241-cf80a6b9eee8 f141b476-2997-4fc2-b534-63ed5d025ac5.rna_seq.star_splice_junctions.tsv.gz d8dd4e825f3a1aca43f1cf74fee2b485 3212989 CTSP-DLBCL1 fdc4789f-ab38-4bc8-9eae-4a699ebd5c07 6e993457-d278-4cd0-ae1a-7dd315abb20c Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts fb1b7ea7-090e-4bc7-acbc-63ab402ef87f e7a05836f62e39a5d7aa36d01b90b25f 3235892 +c7b8e778-eeac-47c7-b572-819c2df59cba 3ba1bde4-a77d-4cf1-8c68-0de5de354895.rna_seq.star_splice_junctions.tsv.gz be6211c6f49aab4788c8bfd1f5ecb8db 3325483 CTSP-DLBCL1 e198a237-2675-4e8e-a903-d76b66da8a61 b9464d1c-1139-4acd-810a-f835c0173f50 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 70cd9d59-abf8-4e25-ab81-9bb8ae74b1f6 07046a3055f2097ee1266fffa58a796a 3345198 +556f48f2-92f3-4713-a5a1-51f86b890d91 c8dcb848-9069-4c4b-85be-292eb0eea455.rna_seq.star_gene_counts.tsv.gz 11ab00c1b9b707faec10f95ce21796da 413519 CTSP-DLBCL1 9b42ae91-9921-48a0-8cac-e6b637804b3d e10a9e1f-c33f-4125-9260-5b937da2e01d Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 4eac6ed1-840e-49b4-9ad8-a6c92cf9ed17 cc1d55196cb1ee459964286b606a7d13 4238163 +961bb9e6-6476-4413-b058-c236890a130d b179a25c-bf07-4d15-bf8e-0fcb70148d8d.rna_seq.star_splice_junctions.tsv.gz f1db10a47c67254735ec970c54a0a968 2755615 CTSP-DLBCL1 dd6f8769-ee57-4171-a353-ceb762541845 c5821dcf-c024-405b-932b-5de5d7c4f008 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 409661fd-8e7b-488b-bf69-da722dece9ae 97971fd6e84e7aa35665466e2dcdff89 2771725 +8c0527a8-552a-4551-a9d5-559183ee5549 05940c26-6a3b-4d76-8daa-a9dd759ac72a.rna_seq.star_splice_junctions.tsv.gz d70ffe192441d2ac9393b66f31106b4b 2521177 CTSP-DLBCL1 3fafa489-0d0e-42f5-9c9f-5a83a5935930 516d9470-89ad-4138-9be8-fc9c093ea023 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts f3f6f2fb-e7ad-4fae-98ff-4e4c87c276a5 6db6d6f0ca118822bb4a4eea8331fabb 2536252 +09b260c3-4412-40a0-8031-772d591c4dcc 5a2a72ad-53f2-423b-a033-e2f71c134f81.rna_seq.star_splice_junctions.tsv.gz db917e9b765f4b832aa228d987c30bfc 3303490 CTSP-DLBCL1 78182973-d259-48da-8f55-a83bfdcf5132 c4d124bd-3f40-49f4-932a-92fb134adc20 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts ddd61e75-9505-4780-bb77-8c0167ff745c 152ce620c52086563f02e516189f28c8 3327002 +79d79ba4-7663-4b37-88b4-76d2d00bb8c2 71afda6c-30eb-41f9-bccd-ea6f12776062.rna_seq.genomic.gdc_realn.bam 03302b551153e16eac590653ae9b6e7e 8284739226 CTSP-DLBCL1 238f9b51-6ca4-4749-bfc8-db51421f6a68 587df096-a9f0-476c-8d6a-d0e34d1d382d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome cd3400bf-7dbe-481a-a2ae-a33644963a17 786d96861e4710531f165526a350860f 8285537756 +4b5bbe12-6109-47d3-9647-51e605d629a5 276569e1-e7c3-4e44-bbe8-d39a6697ca2e.rna_seq.genomic.gdc_realn.bam ac88c7c5683d423be817b58b7152a039 9529689525 CTSP-DLBCL1 f5446fd4-c684-4693-8e2a-3e32a58bff76 0a81b54a-8ca9-460c-bf5d-8589e14862ef Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome d95df18e-7f4f-4828-82bf-755fed4fd239 73c1aa19258d18bb544b0afc3a6f4ecc 9530809469 +3067682e-2e82-40f4-9211-8e1722036f1a 0cb1c975-1516-42f0-a235-90accb91610b.rna_seq.chimeric.gdc_realn.bam e93bf112243ef71eb92177de18cd812c 93231592 CTSP-DLBCL1 2f49bfda-f7e2-4d2e-8cc5-95aa7173ba88 cf1c8eeb-5aeb-4bb7-bd75-24eaf87f16f1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 6f6e701a-d2cb-4835-814f-5e717f22428c 3c1a75d939679ee2f08f0c58040bba9c 93218679 +1022cd51-5988-4b0f-bbf6-06cd2e4bb6f0 1cb29fb6-28f5-4a0d-b3aa-a31fa9bd8c81.rna_seq.chimeric.gdc_realn.bam 699887deab1616908fbc98956e5b494a 111612933 CTSP-DLBCL1 19ec7505-20c7-4ba2-bf08-4a8875cb2639 4ffdce88-9cf9-4917-940f-85f1ba616bdb Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 37a31523-8490-4aa9-ad4e-0b6dabf3aea0 af147ab3c117045ddc4608be217fa608 111569663 +c9d5737c-e0d2-455c-a256-a00108f3c2e2 7fbeb31f-699a-447b-b75f-6a6cd4bcd582.rna_seq.genomic.gdc_realn.bam f4e1eb3de48ae4df08d7f825bb6a6856 9265532698 CTSP-DLBCL1 ad38dc02-4775-49f9-bede-79e10cc2c5e7 70155e15-8a57-4bf9-9fbf-0310dd55a08e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 09f9cdce-6b0c-4d68-90bc-8a21432dc985 ccd5a253cbda2063267007c24b86f5c9 9269842869 +4eee9449-dbc0-42bc-8565-4d7a06b2ac7f 0cb1c975-1516-42f0-a235-90accb91610b.rna_seq.genomic.gdc_realn.bam 3cae787521d23c7f26320b11eb56e8e5 7723435116 CTSP-DLBCL1 2f49bfda-f7e2-4d2e-8cc5-95aa7173ba88 cf1c8eeb-5aeb-4bb7-bd75-24eaf87f16f1 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 437d4615-4539-48e4-91d7-0082bb4e5ef2 8280c4a07be1aa22f81d9fdf55558db2 7724531848 +37da28e6-09c0-4fd2-b1de-f20871f0b3aa e755b027-61a9-44ad-ac75-843bcc6a8d33.rna_seq.star_gene_counts.tsv.gz 2baa8db9802ed2285f22a690adb76c78 399235 CTSP-DLBCL1 1e2211f6-0804-483f-9c37-ca140f9e2869 b424deb7-5739-40e6-bd26-485f90cf3186 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts fb4e4a6a-0553-4fa6-bef4-2dade76c2042 d41c59b4fc5ba245f400a2e8ce2743ea 4221157 +b6ae6762-4681-4802-ac71-2b093ea7adf7 b179a25c-bf07-4d15-bf8e-0fcb70148d8d.rna_seq.star_gene_counts.tsv.gz 1345bbc75d0e36a95d7956aa7f64dffc 400274 CTSP-DLBCL1 dd6f8769-ee57-4171-a353-ceb762541845 c5821dcf-c024-405b-932b-5de5d7c4f008 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 162c5b36-4a5b-4aa4-bd55-ab259acfa92d 6d3a347f54a770e27dd96ccf55909960 4223438 +61dbea06-7055-4fbc-98a8-940fc23b6ee3 c71dfd10-2cb5-45a2-9014-552bce17dfed.rna_seq.genomic.gdc_realn.bam b1ff887356796b8cafbd34348d7ff049 9760396270 CTSP-DLBCL1 8fb4e965-dba7-44ce-8652-e3792a24923e ddbea483-f4b3-473b-86de-d8f5999eaf8f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome e494b6a0-46ec-4089-9826-0761e288982a 7c214a3fa7c1445ce79ea1b3cfbf2e24 9761508590 +99e2d8de-b0a7-470b-9b26-b327710e56c5 227f4026-6261-41cc-bd90-d8e7e2c6a6c5.rna_seq.genomic.gdc_realn.bam 88feeafbb7c3bdf14cfd53fdf4290e21 6489971829 CTSP-DLBCL1 1cfe090d-9a34-4984-a0d8-392ab83635b3 233eb561-f830-481a-9be6-b879d7a2804a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 18ac893d-9a0c-458c-9b71-8fc9de4cbfda 9014a5c0836277bdbfa8281d1d6f0974 6491058264 +7fd2b9b4-035f-47a9-b2aa-d368ffb5bb8d f0bf271d-adaf-417f-ae35-1a534ef0bed0.rna_seq.genomic.gdc_realn.bam 2fcccd56dd3a223ad2a52a2e59f60797 9920797488 CTSP-DLBCL1 1897c9a8-d44e-4777-8cf5-322df09f589b 80d59c3f-3d4f-4fef-a176-fe2a23f17def Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 984b653f-3750-49bb-8e9d-e1dc7a411cb6 6372bf00fcf1d56ddcc6197f999f636e 9921826609 +b2fb560d-3915-4532-b194-691686fbd546 e42faefa-02df-4769-ac74-cfb872add1dd.rna_seq.star_splice_junctions.tsv.gz e796d8402f1078b2611d4d3fc28af4a1 2555257 CTSP-DLBCL1 bd18c252-e23c-40d9-a9b0-98ebe7146f89 8da91347-aed2-4cf9-8843-f784459105bd Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts b510d854-4c25-45ad-a566-dd3e4a02ed9d 4a7242b2dea9c05e639b56df33232120 2571842 +46f5d4dc-6c6c-493a-bb18-0175facb8b99 fd392cb1-b4f7-4edd-9383-a6d570fef6e0.rna_seq.star_splice_junctions.tsv.gz d4f31695c79bd1ef95d2b3318cdc7a63 2546273 CTSP-DLBCL1 4a69b6e0-390c-46ca-a3df-c34c536cc109 f73419c8-9049-41a4-a329-8d8940127532 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 506d4411-166b-4d50-addd-29044f2f4819 41c3a3fe507834c899227dc08a37e067 2563509 +244b4547-2011-40e5-ac59-6c04091c62c2 612b8058-b904-4a7f-977b-43142754e805.rna_seq.star_splice_junctions.tsv.gz 128a40c5dead665dcb912ff935b47950 3147139 CTSP-DLBCL1 24d3d797-ef5d-48c3-aa4c-1631f3fbcb49 01e8e700-d9cf-44e7-9f53-6f621e6b5889 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e16c619a-05fd-469c-ab32-604598496dde a3069b5c3c1cee59d4485315a38e8bd8 3167492 +6f9ddab4-5fb3-4d12-b1b7-1f56986721d3 0decbc4c-b959-4428-b536-795c225c6693.rna_seq.star_gene_counts.tsv.gz 8fb291853d246e2dbdfb821fafd98566 397703 CTSP-DLBCL1 a19418d3-4a31-436b-8986-c9759a135b7f ca9db3d6-d43f-4297-94cd-bd18c7a5c205 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts f8321222-1c07-4fb9-a1da-84e487d1a001 7fb9ce091d30ffcd746489e2fc94bfcc 4219992 +58480c8f-e10d-4309-a78a-711d502859fb b179a25c-bf07-4d15-bf8e-0fcb70148d8d.rna_seq.chimeric.gdc_realn.bam 25b4a3cd5d87c62e2b4625fdcf9a4c63 88635033 CTSP-DLBCL1 dd6f8769-ee57-4171-a353-ceb762541845 c5821dcf-c024-405b-932b-5de5d7c4f008 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 4553f0d5-5621-4ee2-9de8-7d4b7662649c 7194ee6dcab78d3cde187ea6a9989e29 88621928 +d68caf1e-a760-47dc-8ae0-a2c1d5dd6d4b e10bcf20-7db4-46fb-a61d-0e26f3f2e412.rna_seq.star_splice_junctions.tsv.gz 9df3833b3365332c0e5c775cdf4afa70 2720056 CTSP-DLBCL1 940fcc76-8cec-4ba0-b464-f86b04e38706 a632f675-2aa1-402d-8e41-fb7d6d7c4b72 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts b1e96ece-4507-49b7-924d-044b095e12bc fe1c59f3ed451e3c76195ac16e841536 2739337 +6b6aca13-c69c-4fbf-80b8-35750b69f20a 2f85441b-0e65-4d79-8ffd-eabec0e548c4.rna_seq.chimeric.gdc_realn.bam aa71f2fcf24c09e267dade4c09c9901c 99542089 CTSP-DLBCL1 f9c586d5-cc4b-46f6-bdea-067ecbb870a4 b0e16770-1ca5-4fb5-970b-8b97912d35fa Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric c802eaa9-e57a-41e1-9382-c94a91f7c2cd 8846f318c62dc9e62e570d4603b39a82 99546009 +7dc79b7d-59b0-4d16-88d4-7a90cfb7e5f7 652a015a-f40d-4ffe-978a-34314745f7a6.rna_seq.star_gene_counts.tsv.gz 8ff1c37f1cfc1c2c75f58b0a7e21510f 392223 CTSP-DLBCL1 6ae555c0-6c58-4d03-9719-009cb96c339c 5d58c0f8-d4c6-4ee2-aca3-67d1103bda64 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts b93a06aa-47d6-45d7-90a8-ec262b17a408 f664cc6802313aab351efa3d4e2c91cb 4212060 +514d7b1a-0344-4f79-b4d1-09a0d54fb415 652a015a-f40d-4ffe-978a-34314745f7a6.rna_seq.chimeric.gdc_realn.bam 992598821a91bd2e26945d9c1b043311 110383843 CTSP-DLBCL1 6ae555c0-6c58-4d03-9719-009cb96c339c 5d58c0f8-d4c6-4ee2-aca3-67d1103bda64 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric b3a13a0d-266a-4ba0-97d9-b69363c54998 6701dac5ff395fb4efa09dc25410af34 110372747 +081caf72-76dc-4539-847d-b6b4a741dc51 8e2fbbae-96d3-4e99-8863-dbb43b8d9a3c.rna_seq.star_gene_counts.tsv.gz 37f45bb984b6debed9565edbc9773e9f 397302 CTSP-DLBCL1 59a39f8f-6a36-4d83-9f6d-a7460ceb8e1f f9ab981e-c7fa-44a8-a95c-0dd8ee19f47e Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 41cf49d6-ea94-48ec-be0f-f92cb0b91cfb c36f11a1d892da8cad584f8e96ab1874 4221103 +f036fa3c-1506-4a50-94e5-6729e55c8764 1cb29fb6-28f5-4a0d-b3aa-a31fa9bd8c81.rna_seq.star_splice_junctions.tsv.gz 9313e8219862ed11cae9f06b5644c7b6 2234860 CTSP-DLBCL1 19ec7505-20c7-4ba2-bf08-4a8875cb2639 4ffdce88-9cf9-4917-940f-85f1ba616bdb Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 65dee447-4c18-4f66-a92e-e888e95cc540 112ba0a2bf7d0877e91a9a270ab9b493 2247439 +1a0947e8-bab0-4a68-b7ba-a28a7e0505f3 c71dfd10-2cb5-45a2-9014-552bce17dfed.rna_seq.chimeric.gdc_realn.bam f8c0bbb5b98cce7d106a20c28818ef9c 115188835 CTSP-DLBCL1 8fb4e965-dba7-44ce-8652-e3792a24923e ddbea483-f4b3-473b-86de-d8f5999eaf8f Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 53cdcb2a-985f-4db9-820c-318ba1f883d1 4eec465d05ae2564e9e3620d01dbe7da 115180221 +0b49608b-7bb8-450f-b339-971b0dcb2f26 c5e5ee89-3692-4a68-ac12-a957fff4b430.rna_seq.star_gene_counts.tsv.gz 6369093e787b50a4b96a8a29a8385bb2 390745 CTSP-DLBCL1 f4eae82f-bd27-4fc1-b244-890608724ed0 30c43dfb-efd9-498f-a0b1-4e4f04a96372 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 6a3aaaa9-bd2c-43db-89b1-4ea7b55b3fb6 f42a6c49741cc998bde21d15c86babed 4207040 +3525546a-d69e-43e3-afae-8340a3e21dc4 fd392cb1-b4f7-4edd-9383-a6d570fef6e0.rna_seq.genomic.gdc_realn.bam 5f6c2263d030b2ca1c612949594fcd18 10392402067 CTSP-DLBCL1 4a69b6e0-390c-46ca-a3df-c34c536cc109 f73419c8-9049-41a4-a329-8d8940127532 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome c25a448f-ceac-456c-9591-aef89167a579 ffe7fdb36be42a73fe78d0bda892408c 10392733751 +de061bd3-98c8-40fb-b50e-60a1665e938a c8dcb848-9069-4c4b-85be-292eb0eea455.rna_seq.transcriptome.gdc_realn.bam 1ffd91124f8fbf641861a4218a9e64ac 16971537943 CTSP-DLBCL1 9b42ae91-9921-48a0-8cac-e6b637804b3d e10a9e1f-c33f-4125-9260-5b937da2e01d Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 5735c06f-6d93-4d74-a0af-9d5267c1acd0 b4cc349fcb07757ed4428b1874fe9a5f 19151743046 +787f4fa5-1ebb-46bb-9293-f4b1304284b8 2f85441b-0e65-4d79-8ffd-eabec0e548c4.rna_seq.transcriptome.gdc_realn.bam f8e800ccae95805642008056459ddfc4 13247255542 CTSP-DLBCL1 f9c586d5-cc4b-46f6-bdea-067ecbb870a4 b0e16770-1ca5-4fb5-970b-8b97912d35fa Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 4a7e8fc6-3612-4706-881a-353a1e66dc23 0a8efebf0a3a00e1e6d4b5de22f0409e 14897964440 +2621bd36-099d-4fd9-aed9-7ca4a6a81083 c9031d4b-6e6c-4e3e-9474-445775b59db1.rna_seq.chimeric.gdc_realn.bam 31e0369e7dbfde68b8f643e19b6c8f31 110321562 CTSP-DLBCL1 99d6ff63-42a4-4c8f-93ab-54d4cd3e54b1 9ac5e8f0-1bf4-4f1a-9999-7df9ffc03616 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 51442a2b-d1d7-4134-9199-233afd08a465 0253b25f4971127b18bb06b8bf84c7f2 110479885 +240694b5-6c3d-42c3-854b-90c49586a785 a3102a04-33a2-4d3f-a62e-c7efc7a1b0e6.rna_seq.transcriptome.gdc_realn.bam cb246ea7a4b8e05bb817580267d29389 13051951767 CTSP-DLBCL1 c09103e8-7b31-47b1-8422-7a2af43ee186 b1f5e458-27d1-4534-98e7-dd6c2f9faa79 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome dd16c01b-87eb-4bde-b9f7-335f9adb8665 2b8eb86c27cd742917c4b22e88c3fa63 14763428138 +bed5e3fe-e012-4280-b74d-4707150380a0 27f73608-27df-40c8-8070-3cc95e5ccece.rna_seq.transcriptome.gdc_realn.bam bc040e07da82ee0ac0687dedc03dd820 12368067299 CTSP-DLBCL1 aa7c507e-0d0f-49aa-a497-507a43bdeed2 38ca66e1-66b9-4bf3-b345-5308bac4a94c Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 2ff36b0a-8f68-44a7-8b5d-0ac7d4a0ada1 0dbb0a073a74b965aa6b405b6a426605 13573222371 +766e9c06-55d5-459f-aa26-a466066793f8 a3102a04-33a2-4d3f-a62e-c7efc7a1b0e6.rna_seq.chimeric.gdc_realn.bam c8d25faef4e8e505915a04171157fe39 100373472 CTSP-DLBCL1 c09103e8-7b31-47b1-8422-7a2af43ee186 b1f5e458-27d1-4534-98e7-dd6c2f9faa79 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric d231ef5b-1097-48c2-a1e5-4db30c76e4c8 a6fc8d333c761a06822a0bc4a502c46d 100362517 +1772c86d-39cd-4f16-8cf4-0f16f2d492fd 2ccd52d8-0e04-452d-a01c-6871df224846.rna_seq.star_splice_junctions.tsv.gz 7995d31acff283d02419167c58833dac 2896396 CTSP-DLBCL1 ef939e8e-8f38-43c8-8a7f-9908500632b3 a91390ae-9dd0-44fd-a063-63fae5d05f6d Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 75df8cbc-4466-4355-8062-26896ddbea45 3f5edf3fc21dcae031a054f652f14cba 2915298 +59a36b22-5617-4d0c-838b-5507dd0a23da 7197211d-f88b-4e10-b672-8d15462191cb.rna_seq.transcriptome.gdc_realn.bam 2b37cb76caa9a8f48d14c6e8dabb4aed 14033787728 CTSP-DLBCL1 1ea52221-8c19-41a6-88b1-7c38d9ebde18 32ce1b3a-75d2-48f2-ae76-811abd1696db Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome c6e0b78f-2eb4-495e-ac87-e93461630b78 cb19d442928bbd556591fedfa43900f2 15734301706 +d799232b-f80c-478a-a547-f14b11730b44 f0bf271d-adaf-417f-ae35-1a534ef0bed0.rna_seq.transcriptome.gdc_realn.bam 3e7b39d6cddf22c60b7a3dff1da02b0d 13492611266 CTSP-DLBCL1 1897c9a8-d44e-4777-8cf5-322df09f589b 80d59c3f-3d4f-4fef-a176-fe2a23f17def Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 0df783ea-c1eb-4d63-909a-633dca976053 e62918d238dd8a8c5c1ad40ac14525d1 15180304808 +cac5a72f-7c5f-41ce-b0b0-47ed069c9fab af881ac0-7652-4993-9c9d-b90df41539a8.rna_seq.star_splice_junctions.tsv.gz 114e9a7686227ecf2e1c2cf1a5722dca 2911446 CTSP-DLBCL1 1c106f72-b318-4dbf-8309-16460143321a 57e8a11b-3c35-40dd-8610-ba360c472291 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 161e642a-d9f1-4dce-9802-d0e7f00763e5 411c710ce58d2ee61bccacd3ee60ef21 2932540 +fad1bf15-6545-4894-af54-5d2665f2e7ef 612b8058-b904-4a7f-977b-43142754e805.rna_seq.genomic.gdc_realn.bam 5444e837cbc9c8d9a067e996a24f715e 10721796514 CTSP-DLBCL1 24d3d797-ef5d-48c3-aa4c-1631f3fbcb49 01e8e700-d9cf-44e7-9f53-6f621e6b5889 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome aeaa858b-db41-4011-b008-0c5dcc807d7f f78e39b880229742791aa86fb4aec58e 10723751184 +bd7d65d2-7518-4a61-ae64-06afc1db43d8 8e2fbbae-96d3-4e99-8863-dbb43b8d9a3c.rna_seq.transcriptome.gdc_realn.bam 63e719f2dc83e3941cfcd657ca981eb1 11618147865 CTSP-DLBCL1 59a39f8f-6a36-4d83-9f6d-a7460ceb8e1f f9ab981e-c7fa-44a8-a95c-0dd8ee19f47e Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome e602628b-c8f2-46b6-949a-b65186d6dc5c 635e094c0ef9ba76db3a47b6caa96996 13090672965 +a0b2c4d0-f922-4ddb-9866-615cfaac65bf 7fbeb31f-699a-447b-b75f-6a6cd4bcd582.rna_seq.star_gene_counts.tsv.gz a35ae57988e373d3de9e3d9850d927a4 386863 CTSP-DLBCL1 ad38dc02-4775-49f9-bede-79e10cc2c5e7 70155e15-8a57-4bf9-9fbf-0310dd55a08e Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts b70f4f9c-47c2-44a4-960a-11a41f1648b8 abaec3e9679bf51c54f5982403fd01ef 4211683 +d7759cee-ccc3-4bd7-8808-ece4b52dc62e 71afda6c-30eb-41f9-bccd-ea6f12776062.rna_seq.star_gene_counts.tsv.gz 09d0a74d92206381936fbf6f2d499e08 389154 CTSP-DLBCL1 238f9b51-6ca4-4749-bfc8-db51421f6a68 587df096-a9f0-476c-8d6a-d0e34d1d382d Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts a8e4faaa-58ba-4fde-b670-4e332bc384f0 c64539dd20725c4cf3daf5dc54bfcc69 4213135 +c5a08afd-0bcb-41f7-8a86-8d17d61dcd72 32a7a7e8-374f-4f68-87a9-8f1a8f4dced7.rna_seq.star_gene_counts.tsv.gz 1a0d7d2b4ca29cc232e49f6f70cb19ef 395292 CTSP-DLBCL1 7f9bcb4d-b75f-4aca-b77c-fa163e28547d 01c65105-6305-4aef-8471-cd549882a902 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 9c9a1f15-e327-4d84-9dd7-150a4f24b16d 4de2d7cdf35b7900bfc13416c5961d9e 4212245 +56c8bd68-aa9d-4fec-8a93-46bac848dd6f 681e2db5-032f-41e2-9142-dd1c398fedad.rna_seq.star_splice_junctions.tsv.gz d326b65ed6cc906467c8156f4bf989ba 2895567 CTSP-DLBCL1 7d855b3b-2ebc-4ab6-ba70-00a951bb16b1 9b09c715-be8f-4766-bdc0-15cb84db0d7e Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts b5c6d94e-d9b5-41b4-8513-87ca45e4514a 75372a353bd6c10a8f28ccea1aec11c0 2913024 +f0ba197f-c4af-440b-bb63-4176ebd48536 c71dfd10-2cb5-45a2-9014-552bce17dfed.rna_seq.star_splice_junctions.tsv.gz 1d491ccabb2d01a94a2290394611dbf7 2909797 CTSP-DLBCL1 8fb4e965-dba7-44ce-8652-e3792a24923e ddbea483-f4b3-473b-86de-d8f5999eaf8f Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 6c593eeb-05a2-445d-b714-c41c1c820177 602e1881d593355f8128b5e9e27120fb 2928681 +2519e205-0e3d-4e6c-a0fb-ed4335d06210 276569e1-e7c3-4e44-bbe8-d39a6697ca2e.rna_seq.star_splice_junctions.tsv.gz 1a2ab3161891801c7798d5344103cf72 2659694 CTSP-DLBCL1 f5446fd4-c684-4693-8e2a-3e32a58bff76 0a81b54a-8ca9-460c-bf5d-8589e14862ef Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts d9716b09-26b3-43d6-a315-9a3baae45de3 87b303361e1360b30b63dd0161322789 2680164 +efa4b4bb-fee5-4497-ba89-f3f74c281eef a3102a04-33a2-4d3f-a62e-c7efc7a1b0e6.rna_seq.star_splice_junctions.tsv.gz 4c1aa5b229eae31e5f782546fc5b38f9 2894158 CTSP-DLBCL1 c09103e8-7b31-47b1-8422-7a2af43ee186 b1f5e458-27d1-4534-98e7-dd6c2f9faa79 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 219105d2-9975-40a6-99db-7b5cb797fb81 1642d8b562ab6bddc48793bd460dca79 2913676 +43605f8d-bd54-43bb-87d7-f1678e9e45a5 652a015a-f40d-4ffe-978a-34314745f7a6.rna_seq.star_splice_junctions.tsv.gz 057c08701cb6656d6f60b07c995f8cb3 2031036 CTSP-DLBCL1 6ae555c0-6c58-4d03-9719-009cb96c339c 5d58c0f8-d4c6-4ee2-aca3-67d1103bda64 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 712ea824-daae-4c52-9e4e-91e9ec4ac250 9d06e59bcc50dc5ad74e8655a6931aeb 2041710 +b3ad6ba7-9dd5-460d-bc2c-8ccd5a63894a 89b59b00-040c-42c7-98b5-08655a429ac5.rna_seq.genomic.gdc_realn.bam fbf8394f33b60b508b34875164899405 11303364799 CTSP-DLBCL1 8ed9dd0d-da89-437a-a2f0-b03e9e29b89b 8019c334-a159-4c5b-a043-924395acc137 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome a6740968-5f85-4e6c-a0ff-035b93316562 6345116e219f61c6a0647607eb1e4ea9 11303469564 +fe504647-2f84-4203-957a-e35ebf37c27d b9b8f975-5470-46d2-8ac9-fae47a13775b.rna_seq.genomic.gdc_realn.bam 824f1b859feb82b56621e1105b80cfe1 8841616300 CTSP-DLBCL1 1a039fa8-0ea7-4ceb-8847-8949ff47b597 9da96617-6567-4b6f-88e2-01cef6b09505 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 16a2eff1-9fa0-4bbb-80f3-adbf7528d0d9 373897d4305fb1d302d8ece30392090c 8842987196 +a41e6d4c-05f1-4d06-9ba4-19ff71906a5c 05940c26-6a3b-4d76-8daa-a9dd759ac72a.rna_seq.star_gene_counts.tsv.gz a17c3722bc470c70e3e9971778e061b2 401368 CTSP-DLBCL1 3fafa489-0d0e-42f5-9c9f-5a83a5935930 516d9470-89ad-4138-9be8-fc9c093ea023 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 3d858dfe-d2e5-418f-bd89-60b8c0a9193a ebd4e08fcd4dc9a4e7742e22d2334d07 4226537 +35aaa23f-a7bd-4199-b5d3-bb68ba2d2da8 612b8058-b904-4a7f-977b-43142754e805.rna_seq.chimeric.gdc_realn.bam 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e1bcbeea-3ec0-46fe-b3f9-79e762d0c16d 05e845007ba6011ffac5d89fbf114145 2213226 +c47869b2-0ea4-4a95-9748-ce8ada0e46a3 f0bf271d-adaf-417f-ae35-1a534ef0bed0.rna_seq.chimeric.gdc_realn.bam 750654ec51d246a8c09f271725a1fa53 114379572 CTSP-DLBCL1 1897c9a8-d44e-4777-8cf5-322df09f589b 80d59c3f-3d4f-4fef-a176-fe2a23f17def Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric bcc3c623-677b-401d-ac83-612bd5cda9ae ab7e456627fec8a81cf02528580f8537 114355661 +9f874d14-1bea-43e6-bad0-85489d71a48e 71afda6c-30eb-41f9-bccd-ea6f12776062.rna_seq.star_splice_junctions.tsv.gz 3fc759368387c23efe9dec1f272271d1 2511960 CTSP-DLBCL1 238f9b51-6ca4-4749-bfc8-db51421f6a68 587df096-a9f0-476c-8d6a-d0e34d1d382d Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts 746c53be-6a58-406a-a00c-0712bfd5b6be df92ea18d0fb49abf4b4a7e265ba5544 2528308 +07ad2445-e707-48eb-86d8-5787643b8ff9 f141b476-2997-4fc2-b534-63ed5d025ac5.rna_seq.genomic.gdc_realn.bam 096e4d138341c06e74292d4e785041c0 11346912853 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+4eab6bee-4897-4dc2-8479-e6d393d4320b b179a25c-bf07-4d15-bf8e-0fcb70148d8d.rna_seq.genomic.gdc_realn.bam 0a7699ff4b2228cbef219c4ffaf8845f 8576177032 CTSP-DLBCL1 dd6f8769-ee57-4171-a353-ceb762541845 c5821dcf-c024-405b-932b-5de5d7c4f008 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome c232eb54-4b73-41ea-b636-0e6303986290 35fb8d9f1d0a744d8fd5761ae2a85333 8579418870 +a51f66be-8376-47fd-9ad6-95002292baf7 6d542eb2-847c-4056-ae7e-77f95d621471.rna_seq.star_gene_counts.tsv.gz 2ed5edb5ce86f362106a64b9b2569820 414807 CTSP-DLBCL1 d6d16d58-db69-4bed-9ecd-d728d782cebb b1e4a92c-5813-4a55-97f1-c9f1ff299046 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts 65dba826-f06e-428e-9085-cc1096975072 4358fa8eb16733eab718575fb21145f9 4239196 +f6187e27-0d31-448b-b2a4-6c4f391846aa 05940c26-6a3b-4d76-8daa-a9dd759ac72a.rna_seq.genomic.gdc_realn.bam e08bbe33ee0bc6a6119d8a33b43029a4 9770516286 CTSP-DLBCL1 3fafa489-0d0e-42f5-9c9f-5a83a5935930 516d9470-89ad-4138-9be8-fc9c093ea023 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 3e4cb302-3eb8-4f32-8958-a885cdae84f3 8412bb8906c7894a55f899727aa179b9 9772395981 +4ff7b981-6313-4680-b57e-5b6b122e8489 227f4026-6261-41cc-bd90-d8e7e2c6a6c5.rna_seq.transcriptome.gdc_realn.bam 0520c120d656b7d6cdc5dca50e3a2aed 10126420430 CTSP-DLBCL1 1cfe090d-9a34-4984-a0d8-392ab83635b3 233eb561-f830-481a-9be6-b879d7a2804a Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome f37224b9-f054-4aab-a0e4-d82ce5f013f4 925aa258c27b52412a5cbe559fd16d97 11356630285 +8ce196f8-e49b-470a-819c-3ff45d0bceee 32a7a7e8-374f-4f68-87a9-8f1a8f4dced7.rna_seq.chimeric.gdc_realn.bam 4c0fe581014977fa98f3ffcb2ee3838b 114040850 CTSP-DLBCL1 7f9bcb4d-b75f-4aca-b77c-fa163e28547d 01c65105-6305-4aef-8471-cd549882a902 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Chimeric 8aeb2033-99a8-4159-9e8e-84d1950afdac 381a51852e44521c51be7b3cb9acda9d 114034396 +ca7c3f8a-9c88-41bc-8e8c-f4650e451f6c 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Genome dcea8db7-85d1-469c-9980-357867a0f366 61471287f1327546721540528b5f028d 11518322986 +b1c841e8-e993-492c-a0e7-75e38ab8dcf9 05940c26-6a3b-4d76-8daa-a9dd759ac72a.rna_seq.transcriptome.gdc_realn.bam ead111a092497f0c8eae7a068f347196 12538478176 CTSP-DLBCL1 3fafa489-0d0e-42f5-9c9f-5a83a5935930 516d9470-89ad-4138-9be8-fc9c093ea023 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 953534bf-2333-46f8-809b-b450de95cd69 6859c98c750ea7c5a1a53e5341897dd2 14227220566 +48ab49e4-777d-4e3c-960f-aec2273137cd c9031d4b-6e6c-4e3e-9474-445775b59db1.rna_seq.star_gene_counts.tsv.gz 069b613ff06a32953daa16d454ae82f1 385390 CTSP-DLBCL1 99d6ff63-42a4-4c8f-93ab-54d4cd3e54b1 9ac5e8f0-1bf4-4f1a-9999-7df9ffc03616 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts dc465880-dff0-4e14-b31c-b437d168f0da d5a241e73294e6928804a605c7ef8615 4206839 +8a114d32-f0d7-4d21-9d21-333eaac9363b 89b59b00-040c-42c7-98b5-08655a429ac5.rna_seq.chimeric.gdc_realn.bam 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dfdbb1ce1fd1cf49775050a744baa82e 10020555842 +f015c10f-2586-4103-9709-f5b131df1a95 c467a051-c8c1-400c-a304-1c8cef015684.rna_seq.star_splice_junctions.tsv.gz e459afd48c1761b5444d7d550e38eea5 3202724 CTSP-DLBCL1 d3571dfb-71e1-49ee-a0c5-5cfebc791674 5a6f75c2-64f9-4f14-b70e-f11e9b78e18a Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts e18814be-c5bd-4e7e-9865-9ebf180b913f 995c138aba59edd85a3c348cc2303ae8 3224501 +5bc29f2b-cda2-4386-9d48-62c41e4d0939 89b59b00-040c-42c7-98b5-08655a429ac5.rna_seq.star_splice_junctions.tsv.gz f9bc74d64a941510dd825ebd3195b693 3145139 CTSP-DLBCL1 8ed9dd0d-da89-437a-a2f0-b03e9e29b89b 8019c334-a159-4c5b-a043-924395acc137 Transcriptome Profiling Splice Junction Quantification RNA-Seq STAR - Counts dcd65bc8-82bc-4bd5-90d9-6697eb599c11 c70c8dbf49ea627bdbb5d7cb7db84157 3165383 +938a0111-ba6a-448d-aa64-6999eb986cab 3ba1bde4-a77d-4cf1-8c68-0de5de354895.rna_seq.transcriptome.gdc_realn.bam d1a3b2dcfc674aae15033b0181e78579 15315194855 CTSP-DLBCL1 e198a237-2675-4e8e-a903-d76b66da8a61 b9464d1c-1139-4acd-810a-f835c0173f50 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 00f078ef-68de-4d48-9709-3b7dfc175078 070d4d8b901be7a7339c3fdafafb4ea5 17125284292 +1c9a0691-54be-445e-b5e8-1d39a6476519 5a2a72ad-53f2-423b-a033-e2f71c134f81.rna_seq.star_gene_counts.tsv.gz 56a527142903f038d6106dc7131bd25f 402600 CTSP-DLBCL1 78182973-d259-48da-8f55-a83bfdcf5132 c4d124bd-3f40-49f4-932a-92fb134adc20 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts af165644-2342-43c1-9b2d-a347773e67e3 6e56e9a332357a700d015d789f2b5700 4221103 +b9251b1d-dda6-49d6-9dfb-388ef74a4771 e10bcf20-7db4-46fb-a61d-0e26f3f2e412.rna_seq.star_gene_counts.tsv.gz 5974ecfba1b3426ec0ed8956d3bbaca7 394821 CTSP-DLBCL1 940fcc76-8cec-4ba0-b464-f86b04e38706 a632f675-2aa1-402d-8e41-fb7d6d7c4b72 Transcriptome Profiling Gene Expression Quantification RNA-Seq STAR - Counts ef23b7af-6c91-4cb4-961c-07acec32e4fd b714180de7af29bf3458911434d1458b 4220420 +7e7bea43-4377-4fed-9611-d06f103e0962 e943b2fa-2221-473d-bb40-2cea4b5368f3.rna_seq.transcriptome.gdc_realn.bam 555f4db6c95e43e8b077a83ab7ddc5fa 8021856972 CTSP-DLBCL1 02643d04-0cf6-4920-b7b7-849ee7b2a151 9bbe952d-c658-4cde-b4f0-e33f1fcbd5d8 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Transcriptome 188c7e2f-ff1b-4820-9c53-65e870d5edc8 0aeeee88e3f64b515386e8d569c74898 8597280396 +02ef32f9-2b1e-44a7-86a1-aec6ed2937bd 652a015a-f40d-4ffe-978a-34314745f7a6.rna_seq.genomic.gdc_realn.bam d763085cc7876fe50245da269e18f68c 17368168039 CTSP-DLBCL1 6ae555c0-6c58-4d03-9719-009cb96c339c 5d58c0f8-d4c6-4ee2-aca3-67d1103bda64 Sequencing Reads Aligned Reads RNA-Seq STAR 2-Pass Genome 29365b74-cfbe-4b5b-bde2-a2dbee092c8b eed1ba3c0ed9ee73199929717c3db668 17368717544 +ccde134e-0580-44c8-aa24-5701bf918131 276569e1-e7c3-4e44-bbe8-d39a6697ca2e.rna_seq.transcriptome.gdc_realn.bam 9311f788fa38db9b13ac457d21c38d4a 12330743965 CTSP-DLBCL1 f5446fd4-c684-4693-8e2a-3e32a58bff76 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Mutation Targeted Sequencing GENIE Simple Somatic Mutation 2e70b989-ec07-4438-9a42-23f310b38858 0c21dedb4fc1ed0cbc11509b118dece7 3716 +4ed5030c-b846-438c-88d8-28554514f2dd 45ac1088-4cd9-4743-adf8-e923201a737d.genie.aliquot.copy_number_score.tsv d4fd016346f03c0d7e73fae38213d5b3 23098 GENIE-DFCI f0102b99-5eeb-47c1-a739-3785f2f275d6 45ac1088-4cd9-4743-adf8-e923201a737d Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation 725e4662-4a37-4591-9dc9-c06130b74acf d1fc4c01ee9472b1679e48e54f9f0327 22998 +d3250c1d-1c03-4372-9cfd-4e884ab77529 957e7309-1ff6-4601-b0d6-4d2f4a2b0273.genie.aliquot.maf.gz ff329d0c486f743c9a2f58154777ad12 4390 GENIE-DFCI 777db5e2-b165-43a0-abfb-6c12a4b8d7e8 baaf6059-1242-425f-a8f9-5c3acf52a512 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 7b2749ae-a977-4e95-b594-06dc7d4a7ce7 3959b70138953921c1b79b05597b4e24 6245 +3f019323-fa47-4654-b618-f6cd840fbdc7 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Targeted Sequencing GENIE Copy Number Variation 2b671bf7-90dd-4be2-a097-f5ce89ca392e 50dd6c05ca048cdfb1c8cf371ea8ef88 22909 +4bd65a1e-e2d6-499a-bccd-0b20e883cf0d 3b814c33-e453-4fbe-9d72-224b6fac86f5.genie.aliquot.copy_number_score.tsv 8f0e0afc114b3864ca7a2015a3266736 23046 GENIE-DFCI 515e75aa-fea4-4c7f-b988-64d41676c7c2 3b814c33-e453-4fbe-9d72-224b6fac86f5 Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation d44b3fb9-075b-4872-872c-5748215f1b95 b0e7e34510adc39b4d3fbd6d59e537fa 22946 +1e08ebd8-a571-491c-bb2f-c9a56bf8920a c1b2865c-ac82-450d-bb75-3ddfb9d6724a.genie.aliquot.maf.gz db4fa9d64d59e93bdd67b39a97716ef6 3114 GENIE-DFCI d993e09f-0be7-4ae1-9f42-f2d7706725e4 5448890f-0d49-41a0-84a0-421e23a53550 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 842579f9-5d79-424f-9329-4e9a6d9e4b6c 54a2dd0b8ea1531d5af35500a2163f68 4168 +8917cfea-9567-4b38-8987-841399e876fe 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Scores Targeted Sequencing GENIE Copy Number Variation 4940f16a-8965-4af9-a2f3-ce7eb87cc0e5 75982a558ab1de5a216df94b5613621e 22914 +c34b972e-e2a0-40c8-be99-70126414257b 552982a8-a3c0-4a78-9795-ba642f974903.genie.aliquot.maf.gz 5e4401139d8fa7b840e972a5dc33ed59 1972 GENIE-DFCI c4e360de-2633-405f-bd97-db6d50abc638 1ef3f9d3-54b1-4317-aac9-19f5ae7203df Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 1bce55d7-a3f7-40c1-8bb5-a19a443f5974 a5b8aabab8ccd785fb33be31fcbd7d39 2284 +5c61894d-efdf-437d-a816-2d71c59df4f1 4f67648b-2874-4d9c-b310-513e43eb0fea.genie.aliquot.maf.gz 638c443db69a5c2009eb3fef2dd43a6b 3911 GENIE-DFCI 4b032793-b60f-4817-9d73-d4250caaf22d 8d1f9e54-7795-4f1f-9d75-8549a1eea5e2 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation d521108e-b154-430a-9d1b-a9beba30eec3 edfaee2eb2a8beeb0c8cf07d2f27b5de 5103 +1a19bc8e-5731-45a8-8069-10888aae0225 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Mutation Targeted Sequencing GENIE Simple Somatic Mutation 16ff1bb9-bfcc-4c7b-be04-c81934818d7d ba87c2c7d43bc72ea2489f439f4e694d 3660 +bd0e05cc-47e0-4214-a6b9-96f43deb85ee 363a6974-7c01-4fc3-8924-c3a26b9fe9cf.genie.aliquot.copy_number_score.tsv a5d002098b3b3a85132381caec4897ea 23010 GENIE-DFCI d5a7cd7e-717a-404e-a63e-4ddde3ad2a13 363a6974-7c01-4fc3-8924-c3a26b9fe9cf Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation c4595a38-102e-4ffd-8f38-94e70703bbc4 b3a091f14d30dac0b406de3b32c0252e 22910 +4f261ad5-9caa-414e-bb71-86bf9f56622c cbec0a3d-9796-48e4-a14b-f7e613ad9fef.genie.aliquot.maf.gz b1221d417c2a2bb5ac596057a1ae2087 4450 GENIE-DFCI d5a6c7b4-da55-4a25-86b8-51041e6434ac 1bf4ae7d-e857-4c9b-8b37-bd36f75a8e6f Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 59bd9f0f-f4f5-4e3f-85e1-5aa3bc3ba717 7ac8b8ecf0359fdb7f1185a08f5907b0 6590 +27ccd04d-55d9-4353-8e46-b1045c9d7d6e 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100c2f94-ab94-4899-baa8-a88d6f4c7b78 Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation 7fbaa3b9-5538-4fa7-a4ca-458062eb8f8d b1e1dd883334713bc445dc969922f70f 22909 +8af42442-330f-4fe8-b09f-fecd64752427 8a745e53-3c34-48b3-9d1c-e0a3e6277bb3.genie.aliquot.maf.gz 812321ab9e8073ffff8fc643f5a81c49 2160 GENIE-DFCI 9786e934-8867-4a01-992c-efc22c65a401 99e69935-e496-4fc6-80f9-4cce834d8dfe Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 5ba5c51b-dd1f-4c65-9d1c-3f2443ca930c eef2055091245646afbd6f2da25f86ab 2504 +5bd3abc8-4b53-49fb-9396-07c6e1ccfdd6 bbc514e8-d5ff-4724-a07c-5fe3a61ffdc7.genie.aliquot.copy_number_score.tsv 4bb3396c91a260fe065694129e8dd778 23012 GENIE-DFCI 4bde1396-986e-42bb-88dc-7ce14157fc86 bbc514e8-d5ff-4724-a07c-5fe3a61ffdc7 Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation 8b761531-ed2d-4f6d-a3c1-f10139a0ae82 1a31855351a84c2bce435d12a6b37912 22912 +ceb15405-dd4b-49aa-b98f-b45e7f0b341e 54ab98de-2dbb-44e3-9c5e-07281080eb81.genie.aliquot.copy_number_score.tsv 36713504ca40a2da80cdcdbfbe9f122d 23045 GENIE-DFCI 7ebf1647-022c-411c-aa00-38010a2bf7b7 54ab98de-2dbb-44e3-9c5e-07281080eb81 Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation 02c8267c-0192-4e5f-ba25-dfd99df576a5 e06d392e33f60ceada375fd169131894 22945 +e1b7a094-8dc4-4f79-b9f9-7b9a28058423 1ffcc0cc-23da-4275-aa97-e3b8a18ae334.genie.aliquot.maf.gz b8c9f79638243c1743704597671ce6d5 3823 GENIE-DFCI 001e9cbc-ccbc-4d29-a397-6cddd5591b1a eb6c79d5-4a8b-4a4d-81fe-6b9e3e49a069 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 541d5c17-f15a-4d92-9c83-f6bee9ce28f7 e4954b6db3f62d91bf33ef7b4717c96c 4439 +5a8b7119-1729-4fe6-95ac-a653687a3740 9f027156-2b19-4467-95a1-f5207069225f.genie.aliquot.maf.gz 41c14a684a2958a99826b8b9af3f14cc 4007 GENIE-DFCI 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Mutation c020a121-dcfb-4607-a8e6-f2fe44584080 be8ec1680abfdc12e561b6d1be175505 3915 +6939493c-75ef-4823-ae95-5f9250f6a9f1 9b82348f-0dcd-4cc3-99e5-8b4576a2ce5b.genie.aliquot.copy_number_score.tsv b4da9d8389609be5d56c6f8423790a2c 23009 GENIE-DFCI 1c0c5f61-4e08-44ab-9cae-babc08ef76e1 9b82348f-0dcd-4cc3-99e5-8b4576a2ce5b Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation 36344f22-28c6-4466-b823-aa541f6c41ec b1e1dd883334713bc445dc969922f70f 22909 +2e535344-f335-47db-9ff8-ec0a22837a4f 5485d396-0ecc-4a9b-b055-edd1b05e4225.genie.aliquot.maf.gz e05f8b7c5013b79d20fa653136a9b49f 4568 GENIE-DFCI 9f10b8b5-f1be-4bb8-b5ee-1c8c465e5673 8fb36be9-3387-4b78-96b0-de95c584809d Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation cd437987-aa7f-482a-93e8-d846e47a24b8 9beb3d7f083cceafd430c04b4aaafffe 6230 +53ce47bc-8136-4603-9bb5-63ac0be2ef87 95e40b87-d76b-48f5-8c93-21e071a24d0a.genie.aliquot.maf.gz 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Mutation Targeted Sequencing GENIE Simple Somatic Mutation 69252eef-8191-489f-97d5-fd8bf2803058 25829c1c7bac73eb2d528bf46b69699c 1827 +0b8baeaf-92ee-431a-8c52-a33fd2a6517e 35018b42-d4f4-4cc1-acbe-3ad32e95e160.genie.aliquot.maf.gz 450222b12b4550e1632106c2f9ba7fc1 3769 GENIE-DFCI fa420dc0-f233-43a5-923c-5fd79d93109a 68c681d1-285a-4daf-bb1b-d0668f5b780c Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation bf60c133-bf8f-44e2-b12b-2c75d998786d b8c83c896319da5366f8dd7e616b36fa 4887 +66c1e551-8000-453a-99bc-450b7ff0c10e 1b88dd4c-cc13-4ae3-9bc7-9ededf4792f0.genie.aliquot.maf.gz e2ed8aafd55e8f2e1b4a8b925414b57b 4415 GENIE-DFCI 2f8baf8e-4e89-4eea-a872-1c891ebf17c5 26e96e01-7a9b-4760-8784-03c365aa21c6 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 63e7e9a9-5ccc-40fd-9f0d-dfad5d544196 013b6467f5784c83ddfd4358eff95db7 6743 +3c8f59b7-d5ce-4313-82b3-6062431fd3ec 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cbc1552a-64cf-4b55-901c-51ee81e13f6d Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation 2c89a35f-8515-4908-a20f-d48c198bae23 b1e1dd883334713bc445dc969922f70f 22909 +eed32e81-6869-4bee-ba6d-7914704582a0 f580cabc-f0c4-47c4-8d5a-44689a649ba5.genie.aliquot.maf.gz b9418b98ae173f9bdc0f8f6f296fba46 2619 GENIE-DFCI 83f1d68c-0564-42ca-b11d-be060f12621b 83948441-a852-4d6f-ae83-b6c576d55c7d Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 7c13304a-c9a6-4c90-b79d-781426b66838 534f5a91a4442e16c62768b82beb8c7f 4754 +5add512d-45d1-4e78-815a-51669e472600 ed123478-dc1b-4ee3-a7ac-0984f3dd2512.genie.aliquot.maf.gz c09c7b46bdbbc17e3ec49e271c66d1fe 3868 GENIE-DFCI b0127bec-96a9-4f74-b8a9-7fdc6cbff59f 0595d75d-e058-43b9-a659-b48ea1961b67 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation a49f29cb-6551-40f9-b310-f1bcc8008a2a 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Sequencing GENIE Simple Somatic Mutation 3a4a041b-7cb8-4afd-b2d6-0d9946885fcb b90827389e0411094111df947b86cd08 7523 +9369a1c5-a812-49ab-911c-5ec23705076f 504ad34e-3629-49ae-813a-310125815225.genie.aliquot.maf.gz d00a687de846a0d92b9cc79047710390 22613 GENIE-DFCI e3887b85-36f0-4ecd-9d69-d79783458d00 8ec1ad21-9f53-4a27-8935-c50bb95b0780 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 202ebbb7-c8e7-4869-9580-d0548c45abba 08de67f044b12facb2be723e70a853ef 32662 +bb8a2660-cdc9-4a2a-a0fe-980cbb8743f2 be87c979-a412-490b-9e78-95cd1b03bced.genie.aliquot.copy_number_score.tsv b4da9d8389609be5d56c6f8423790a2c 23009 GENIE-DFCI b1171f07-bf0f-4836-8782-18798593d76e be87c979-a412-490b-9e78-95cd1b03bced Copy Number Variation Gene Level Copy Number Scores Targeted Sequencing GENIE Copy Number Variation 35112131-afc7-4d8c-b9c5-8a2cf4b3a6e7 b1e1dd883334713bc445dc969922f70f 22909 +c2371fcf-2c17-4539-9379-605aee9d8398 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818c44354c5c8391f4a7dbf8400da716 23014 +79a96267-3d33-4594-88b6-52f6d82bfd5b fc8a5673-db63-4a6a-9a46-c78cacb155c0.genie.aliquot.maf.gz 19f081338677d67268c59aa397eb7688 2544 GENIE-DFCI 1b466934-d980-4c47-abb5-0dd68c87d5a8 7d464845-0192-44df-8e5f-04b8039acef1 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation 52c66d41-0ae5-4bad-8b3b-bcd4db87dd9d d3adaacd744bea637b48963521adc85f 2804 +5c4a5726-2fff-494d-bba2-fe99975249a3 f281fd2c-3ee5-48a5-bf85-28fe2b5892b8.genie.aliquot.maf.gz a8b288c08f236c7751cbba6845e25006 5636 GENIE-DFCI 29a51e87-12ba-4dd0-ab93-b9d2e3a397d8 f95d81be-63d0-4f07-8829-fc2128f610c1 Simple Nucleotide Variation Masked Annotated Somatic Mutation Targeted Sequencing GENIE Simple Somatic Mutation dfe850ad-649c-49c5-a580-6864fc92db02 0375a6313e5a936dbf099ddf96c1fdcf 7304 +acb719d6-73d0-49ed-8bdb-17c7f922cfb8 d54da423-7e04-4b9a-9f5e-ba4342b376df.genie.aliquot.copy_number_score.tsv ac92a95e40002043785136a8043bf54b 23009 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