nfcore/rnaseq Docker Image

Nextflow RNA-Seq analysis pipeline, part of the nf-core community..

Introduction

nf-core/rnaseq is a bioinformatics analysis pipeline used for RNA sequencing data.

The workflow processes raw data from FastQ inputs (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/, https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/), aligns the reads (https://github.com/alexdobin/STAR or https://ccb.jhu.edu/software/hisat2/index.shtml), generates counts relative to genes (http://bioinf.wehi.edu.au/featureCounts/, https://ccb.jhu.edu/software/stringtie/) or transcripts (https://combine-lab.github.io/salmon/, https://bioconductor.org/packages/release/bioc/html/tximport.html or https://github.com/deweylab/RSEM) and performs extensive quality-control on the results (http://rseqc.sourceforge.net/, Qualimap, https://bioconductor.org/packages/release/bioc/html/dupRadar.html, Preseq, https://bioconductor.org/packages/release/bioc/html/edgeR.html, MultiQC). See the output documentation for more details of the results.

The pipeline is built using [***] a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

Quick Start

i. Install https://nf-co.re/usage/installation

ii. Install either https://docs.docker.com/engine/installation/ or https://www.sylabs.io/guides/3.0/user-guide/ for full pipeline reproducibility (please only use https://conda.io/miniconda.html as a last resort; see https://nf-co.re/usage/configuration#basic-configuration-profiles)

iii. Download the pipeline and test it on a minimal dataset with a single command

bash
nextflow run nf-core/rnaseq -profile test,<docker/singularity/conda>

iv. Start running your own analysis!

bash
nextflow run nf-core/rnaseq -profile <docker/singularity/conda> --reads '*_R{1,2}.fastq.gz' --genome GRCh37

See usage docs for all of the available options when running the pipeline.

Documentation

The nf-core/rnaseq pipeline comes with documentation about the pipeline, found in the docs/ directory:

1. https://nf-co.re/usage/installation
2. Pipeline configuration
   • https://nf-co.re/usage/local_installation
   • https://nf-co.re/usage/adding_own_config
   • https://nf-co.re/usage/reference_genomes
3. Running the pipeline
4. Output and how to interpret the results
5. https://nf-co.re/usage/troubleshooting

Credits

These scripts were originally written for use at the National Genomics Infrastructure, part of SciLifeLab in Stockholm, Sweden, by Phil Ewels (https://github.com/ewels) and Rickard Hammarén (https://github.com/Hammarn).

Many thanks to other who have helped out along the way too, including (but not limited to): https://github.com/Galithil, https://github.com/pditommaso, https://github.com/orzechoj, https://github.com/apeltzer, https://github.com/colindaven, https://github.com/lpantano, https://github.com/olgabot, https://github.com/jburos, https://github.com/drpatelh.

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 Slack (you can join with https://nf-co.re/join/slack).

Citation

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: https://dx.doi.org/10.1038/s41587-020-0439-x.
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