Merge pull request #711 from mamtagiri/patch-1

Update with sas token change notice

Author: Jill Grant

articles/open-datasets/dataset-1000-genomes.md

@@ -9,6 +9,8 @@ ms.date: 07/10/2024
 
 # 1000 Genomes
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 The 1000 Genomes Project ran between 2008 and 2015, to create the largest public catalog of human variation and genotype data. The final data set contains data for 2,504 individuals from 26 populations and 84 million identified variants. For more information, visit the 1000 Genome Project [website](https://www.internationalgenome.org/) and these publications:
 
 [Pilot Analysis: A map of human genome variation from population-scale sequencing Nature 467, 1061-1073 (28 October 2010)](https://www.nature.com/articles/nature09534)

articles/open-datasets/dataset-clinvar-annotations.md

@@ -9,6 +9,8 @@ ms.date: 06/13/2024
 
 # ClinVar Annotations
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 The [ClinVar](https://www.ncbi.nlm.nih.gov/clinvar/) resource is a freely accessible, public archive of reports - with supporting evidence - about the relationships among human variations and phenotypes. It facilitates access to and communication about the claimed relationships between human variation and observed health status, and about the history of that interpretation. It provides access to a broader set of clinical interpretations that researchers can incorporate into genomics workflows and applications.
 
 Visit the [Data Dictionary](https://www.ncbi.nlm.nih.gov/projects/clinvar/ClinVarDataDictionary.pdf) and the [FAQ resource](https://www.ncbi.nlm.nih.gov/clinvar/docs/faq/) for more information about the data.

articles/open-datasets/dataset-encode.md

@@ -8,6 +8,8 @@ ms.date: 04/16/2021
 
 # ENCODE: Encyclopedia of DNA Elements
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 The [Encyclopedia of DNA Elements (ENCODE) Consortium](https://www.encodeproject.org/help/project-overview/) is an ongoing international collaboration of research groups funded by the National Human Genome Research Institute (NHGRI). ENCODE's goal is to build a comprehensive parts list of functional elements in the human genome, including elements that act at the protein and RNA levels, and regulatory elements that control cells and circumstances in which a gene is active.
 
 ENCODE investigators employ various assays and methods to identify functional elements. The discovery and annotation of gene elements is accomplished primarily by sequencing a diverse range of RNA sources, comparative genomics, integrative bioinformatic methods, and human curation. Regulatory elements are typically investigated through DNA hypersensitivity assays, assays of DNA methylation, and immunoprecipitation (IP) of proteins that interact with DNA and RNA, that is, modified histones, transcription factors, chromatin regulators, and RNA-binding proteins, followed by sequencing.

articles/open-datasets/dataset-gatk-resource-bundle.md

@@ -8,6 +8,8 @@ ms.date: 04/16/2021
 
 # GATK Resource Bundle
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 The [GATK resource bundle](https://gatk.broadinstitute.org/hc/articles/360035890811-Resource-bundle) is a collection of standard files for working with human resequencing data with the GATK.
 
 [!INCLUDE [Open Dataset usage notice](./includes/open-datasets-usage-note.md)]

articles/open-datasets/dataset-genomics-data-lake.md

@@ -30,6 +30,8 @@ The Genomics Data Lake is hosted in the West US 2 and West Central US Azure regi
 | [GATK Resource Bundle](dataset-gatk-resource-bundle.md) | GATK Resource bundle |
 | [TCGA Open Data](dataset-the-cancer-genome-atlas.md) | TCGA Open Data |
 | [Pan UK-Biobank](dataset-panancestry-uk-bio-bank.md) | Pan UK-Biobank |
+| [ImmuneCODE database](dataset-immunecode.md) | ImmuneCODE database |
+| [Open Targets dataset](dataset-panancestry-uk-bio-bank.md) | Open Targets dataset |
 
 ## Next steps
 

articles/open-datasets/dataset-human-reference-genomes.md

@@ -8,6 +8,8 @@ ms.date: 04/16/2021
 
 # Human Reference Genomes
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 This dataset includes two human-genome references assembled by the [Genome Reference Consortium](https://www.ncbi.nlm.nih.gov/grc): Hg19 and Hg38.
 
 For more information on Hg19 (GRCh37) data, see the [GRCh37 report at NCBI](https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.13/).

articles/open-datasets/dataset-illumina-platinum-genomes.md

@@ -8,6 +8,8 @@ ms.date: 04/16/2021
 
 # Illumina Platinum Genomes
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 Whole-genome sequencing is enabling researchers worldwide to characterize the human genome more fully and accurately. This requires a comprehensive, genome-wide catalog of high-confidence variants called in a set of genomes as a benchmark. Illumina has generated deep, whole-genome sequence data of 17 individuals in a three-generation pedigree. Illumina has called variants in each genome using a range of currently available algorithms.
 
 For more information on the data, see the official [Illumina site](https://www.illumina.com/platinumgenomes.html).
@@ -206,4 +208,4 @@ run gatk VariantsToTable -V NA12877.vcf.gz -F CHROM -F POS -F TYPE -F AC -F AD -
 
 ## Next steps
 
-View the rest of the datasets in the [Open Datasets catalog](dataset-catalog.md).
+View the rest of the datasets in the [Open Datasets catalog](dataset-catalog.md).

articles/open-datasets/dataset-open-cravat.md

@@ -8,6 +8,8 @@ ms.date: 04/16/2021
 
 # OpenCravat: Open Custom Ranked Analysis of Variants Toolkit
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 OpenCRAVAT is a Python package that performs genomic variant interpretation including variant impact, annotation, and scoring. OpenCRAVAT has a modular architecture with a wide variety of analysis modules and annotation resources that can be selected and installed/run based on the needs of a given study.
 
 For more information on the data, see the [OpenCravat](https://opencravat.org/).

articles/open-datasets/dataset-open-targets.md

@@ -8,6 +8,8 @@ ms.date: 04/16/2021
 
 # Open Targets
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 The Open Targets Platform is a data resource to facilitate the systematic identification and prioritization of potential therapeutic drug targets. This resource integrates publicly available datasets, including those datasets that are generated by the Open Targets consortium, to build and score target-disease associations, aiding in the identification and prioritization of drug targets. Additionally, it incorporates pertinent annotation information about targets, diseases, phenotypes, drugs, and their key relationships.
 
 The Open Targets Genetics highlights variant-centric statistical evidence to allow both prioritization of candidate causal variants at trait-associated loci and identification of potential drug targets. It collects and combines genetic associations gathered from published literature as well as newly derived data from sources like UK Biobank and FinnGen. Additionally, it includes functional genomics information such as chromatin conformation and interactions, along with quantitative trait loci (eQTLs, pQTLs, and sQTLs). Large-scale pipelines apply statistical fine-mapping across thousands of trait-associated loci to resolve association signals and link each variant to its proximal and distal target genes using a 'Locus2Gene' assessment. Integrated cross-trait colocalisation analyses and linking to detailed pharmaceutical compounds extend the capacity of Open Targets Genetics to explore drug repositioning opportunities and shared genetic architecture.

articles/open-datasets/dataset-the-cancer-genome-atlas.md

@@ -12,6 +12,8 @@ ms.date: 09/22/2022
 
 # TCGA Open Data
 
+[!INCLUDE [Open Dataset access change notice](./includes/open-datasets-change-note.md)]
+
 The Cancer Genome Atlas (TCGA), a landmark cancer genomics program, molecularly characterized over 20,000 primary cancer and matched normal samples spanning 33 cancer types[[1]](https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga). The TCGA cancer data made available publically are two tiers: open or controlled access. 
 
 - Open access [available on Azure]: This dataset contains deindentified clinical and biospecimen data or summarized data that doesn't contain any individually identifiable information. The data types included are Gene expression, methylation beta values and protein quantification. DNA level datatype includes gene level copy number and masked copy number segment.