nf-core/fetchngs
Pipeline to fetch metadata and raw FastQ files from public databases
1.8
). The latest
stable release is
1.12.0
.
Introduction
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).
The pipeline is built using Nextflow, 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 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.
On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.The results obtained from the full-sized test can be viewed on the nf-core website.
Pipeline summary
Via a single file of ids, provided one-per-line (see example input file) the pipeline performs the following steps:
SRA / ENA / DDBJ ids
- Resolve database ids back to appropriate experiment-level ids and to be compatible with the ENA API
- Fetch extensive id metadata via ENA API
- Download FastQ files:
- If direct download links are available from the ENA API, fetch in parallel via
curl
and performmd5sum
check - Otherwise use
sra-tools
to download.sra
files and convert them to FastQ
- If direct download links are available from the ENA API, fetch in parallel via
- Collate id metadata and paths to FastQ files in a single samplesheet
GEO ids
Support for GEO ids was dropped in [v1.7] due to breaking changes introduced in the NCBI API. For more detailed information please see this PR.
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:
- Search for your GEO accession on GEO
- Click
SRA Run Selector
at the bottom of the GEO accession page - Select the desired samples in the
SRA Run Selector
and then download theAccession List
This downloads a text file called SRR_Acc_List.txt
that can be directly provided to the pipeline once renamed with a .csv extension e.g. --input SRR_Acc_List.csv
.
Synapse ids
- Resolve Synapse directory ids to their corresponding FastQ files ids via the
synapse list
command. - Retrieve FastQ file metadata including FastQ file names, md5sums, etags, annotations and other data provenance via the
synapse show
command. - Download FastQ files in parallel via
synapse get
- Collate paths to FastQ files in a single samplesheet
Samplesheet format
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
- Ilumina processing mode of nf-core/viralrecon
- nf-core/taxprofiler
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.
Quick Start
-
Install
Nextflow
(>=21.10.3
) -
Install any of
Docker
,Singularity
(you can follow this tutorial),Podman
,Shifter
orCharliecloud
for full pipeline reproducibility (you can useConda
both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see docs). -
Download the pipeline and test it on a minimal dataset with a single command:
Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (
YOURPROFILE
in the example command above). You can chain multiple config profiles in a comma-separated string.- The pipeline comes with config profiles called
docker
,singularity
,podman
,shifter
,charliecloud
andconda
which instruct the pipeline to use the named tool for software management. For example,-profile test,docker
. - Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use
-profile <institute>
in your command. This will enable eitherdocker
orsingularity
and set the appropriate execution settings for your local compute environment. - If you are using
singularity
, please use thenf-core download
command to download images first, before running the pipeline. Setting theNXF_SINGULARITY_CACHEDIR
orsingularity.cacheDir
Nextflow options enables you to store and re-use the images from a central location for future pipeline runs. - If you are using
conda
, it is highly recommended to use theNXF_CONDA_CACHEDIR
orconda.cacheDir
settings to store the environments in a central location for future pipeline runs.
- The pipeline comes with config profiles called
-
Start running your own analysis!
Documentation
The nf-core/fetchngs pipeline comes with documentation about the pipeline usage, parameters and output.
Credits
nf-core/fetchngs was originally written by Harshil Patel (@drpatelh) from Seqera Labs, Spain and Jose Espinosa-Carrasco (@JoseEspinosa) from The Comparative Bioinformatics Group at The Centre for Genomic Regulation, Spain. Support for download of sequencing reads without FTP links via sra-tools was added by Moritz E. Beber (@Midnighter) from Unseen Bio ApS, Denmark. The Synapse workflow was added by Daisy Han @daisyhan97 and Bruno Grande @BrunoGrandePhD from Sage Bionetworks, Seattle.
Contributions and Support
If you would like to contribute to this pipeline, please see the contributing guidelines.
For further information or help, don’t hesitate to get in touch on the Slack #fetchngs
channel (you can join with this invite).
Citations
If you use nf-core/fetchngs for your analysis, please cite it using the following doi: 10.5281/zenodo.5070524
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md
file.
You can cite the nf-core
publication as follows:
The nf-core framework for community-curated bioinformatics pipelines.
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.