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Support for GEO ids has been dropped in this release due to breaking changes introduced in the NCBI API. For more detailed information please see [this PR](https://github.com/nf-core/fetchngs/pull/102).
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As a workaround, if you have a GEO accession you can directly download a text file containing the appropriate SRA ids to pass to the pipeline:
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- Search for your GEO accession on [GEO](https://www.ncbi.nlm.nih.gov/geo)
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- Click `SRA Run Selector` at the bottom of the GEO accession page
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- Select the desired samples in the `SRA Run Selector` and then download the `Accession List`
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This downloads a text file called `SRR_Acc_List.txt` that can be directly provided to the pipeline e.g. `--input SRR_Acc_List.txt`.
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### Enhancements & fixes
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-[#97](https://github.com/nf-core/fetchngs/pull/97) - Add support for generating nf-core/taxprofiler compatible samplesheets.
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-[#99](https://github.com/nf-core/fetchngs/issues/99) - SRA_IDS_TO_RUNINFO fails due to bad request
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- Add `enum` field for `--nf_core_pipeline` to parameter schema so only accept supported pipelines are accepted
Copy file name to clipboardExpand all lines: README.md
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## Introduction
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**nf-core/fetchngs** is a bioinformatics pipeline to fetch metadata and raw FastQ files from both public and private databases. At present, the pipeline supports SRA / ENA / DDBJ / GEO / Synapse ids (see [usage docs](https://nf-co.re/fetchngs/usage#introduction)).
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**nf-core/fetchngs** is a bioinformatics pipeline to fetch metadata and raw FastQ files from both public and private databases. At present, the pipeline supports SRA / ENA / DDBJ / Synapse ids (see [usage docs](https://nf-co.re/fetchngs/usage#introduction)).
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The pipeline is built using [Nextflow](https://www.nextflow.io), a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html) implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.
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Via a single file of ids, provided one-per-line (see [example input file](https://raw.githubusercontent.com/nf-core/test-datasets/fetchngs/sra_ids_test.txt)) the pipeline performs the following steps:
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### SRA / ENA / DDBJ / GEO ids
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### SRA / ENA / DDBJ ids
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1. Resolve database ids back to appropriate experiment-level ids and to be compatible with the [ENA API](https://ena-docs.readthedocs.io/en/latest/retrieval/programmatic-access.html)
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2. Fetch extensive id metadata via ENA API
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- Otherwise use [`sra-tools`](https://github.com/ncbi/sra-tools) to download `.sra` files and convert them to FastQ
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4. Collate id metadata and paths to FastQ files in a single samplesheet
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### GEO ids
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Support for GEO ids was dropped in [[v1.7](https://github.com/nf-core/fetchngs/releases/tag/1.7)] due to breaking changes introduced in the NCBI API. For more detailed information please see [this PR](https://github.com/nf-core/fetchngs/pull/102).
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As a workaround, if you have a GEO accession you can directly download a text file containing the appropriate SRA ids to pass to the pipeline instead:
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- Search for your GEO accession on [GEO](https://www.ncbi.nlm.nih.gov/geo)
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- Click `SRA Run Selector` at the bottom of the GEO accession page
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- Select the desired samples in the `SRA Run Selector` and then download the `Accession List`
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This downloads a text file called `SRR_Acc_List.txt` that can be directly provided to the pipeline e.g. `--input SRR_Acc_List.txt`.
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### Synapse ids
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1. Resolve Synapse directory ids to their corresponding FastQ files ids via the `synapse list` command.
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### Samplesheet format
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The columns in the auto-created samplesheet can be tailored to be accepted out-of-the-box by selected nf-core pipelines, these currently include [nf-core/rnaseq](https://nf-co.re/rnaseq/usage#samplesheet-input) and the Illumina processing mode of [nf-core/viralrecon](https://nf-co.re/viralrecon/usage#illumina-samplesheet-format). You can use the `--nf_core_pipeline` parameter to customise this behaviour e.g. `--nf_core_pipeline rnaseq`. More pipelines will be supported in due course as we adopt and standardise samplesheet input across nf-core.
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The columns in the auto-created samplesheet can be tailored to be accepted out-of-the-box by selected nf-core pipelines, these currently include:
You can use the `--nf_core_pipeline` parameter to customise this behaviour e.g. `--nf_core_pipeline rnaseq`. More pipelines will be supported in due course as we adopt and standardise samplesheet input across nf-core.
Copy file name to clipboardExpand all lines: docs/output.md
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The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data depending on the type of ids provided:
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- Download FastQ files and create samplesheet from:
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1.[SRA / ENA / DDBJ / GEO ids](#sra--ena--ddbj--geo-ids)
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1.[SRA / ENA / DDBJ ids](#sra--ena--ddbj-ids)
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2.[Synapse ids](#synapse-ids)
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-[Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution
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Please see the [usage documentation](https://nf-co.re/fetchngs/usage#introduction) for a list of supported public repository identifiers and how to provide them to the pipeline.
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### SRA / ENA / DDBJ / GEO ids
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### SRA / ENA / DDBJ ids
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<detailsmarkdown="1">
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<summary>Output files</summary>
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-`fastq/`
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-`*.fastq.gz`: Paired-end/single-end reads downloaded from the SRA / ENA / DDBJ / GEO.
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-`*.fastq.gz`: Paired-end/single-end reads downloaded from the SRA / ENA / DDBJ.
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-`fastq/md5/`
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-`*.md5`: Files containing `md5` sum for FastQ files downloaded from the ENA.
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The pipeline has been set-up to automatically download and process the raw FastQ files from both public and private repositories. Identifiers can be provided in a file, one-per-line via the `--input` parameter. Currently, the following types of example identifiers are supported:
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### Samplesheet format
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As a bonus, the columns in the auto-created samplesheet can be tailored to be accepted out-of-the-box by selected nf-core pipelines, these currently include [nf-core/rnaseq](https://nf-co.re/rnaseq/usage#samplesheet-input) and the Illumina processing mode of [nf-core/viralrecon](https://nf-co.re/viralrecon/usage#illumina-samplesheet-format). You can use the `--nf_core_pipeline` parameter to customise this behaviour e.g. `--nf_core_pipeline rnaseq`. More pipelines will be supported in due course as we adopt and standardise samplesheet input across nf-core. It is highly recommended that you double-check that all of the identifiers you defined using `--input` are represented in the samplesheet. Also, public databases don't reliably hold information such as strandedness information so you may need to amend these entries too if for example your samplesheet was created by providing `--nf_core_pipeline rnaseq`.
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As a bonus, the columns in the auto-created samplesheet can be tailored to be accepted out-of-the-box by selected nf-core pipelines, these currently include:
You can use the `--nf_core_pipeline` parameter to customise this behaviour e.g. `--nf_core_pipeline rnaseq`. More pipelines will be supported in due course as we adopt and standardise samplesheet input across nf-core. It is highly recommended that you double-check that all of the identifiers you defined using `--input` are represented in the samplesheet. Also, public databases don't reliably hold information such as strandedness information so you may need to amend these entries too if for example your samplesheet was created by providing `--nf_core_pipeline rnaseq`.
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