nf-core/rnaseq

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Introduction

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

The workflow processes raw data from FastQ inputs (FastQC, Trim Galore!), aligns the reads (STAR or HiSAT2), generates counts relative to genes (featureCounts, StringTie) or transcripts (Salmon, tximport) and performs extensive quality-control on the results (RSeQC, Qualimap, dupRadar, Preseq, edgeR, MultiQC). See the output documentation for more details of the results.

The pipeline is built using Nextflow, 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 nextflow

ii. Install one of docker, singularity or conda

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

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

iv. Start running your own analysis!

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. Installation
2. Pipeline configuration
   • Local installation
   • Adding your own system config
   • Reference genomes
3. Running the pipeline
4. Output and how to interpret the results
5. Troubleshooting

Credits

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

Many thanks to other who have helped out along the way too, including (but not limited to): @Galithil, @pditommaso, @orzechoj, @apeltzer, @colindaven, @lpantano, @olgabot, @jburos, @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 this invite).

Citation

If you use nf-core/rnaseq for your analysis, please cite it using the following doi: 10.5281/zenodo.1400710

You can cite the nf-core pre-print as follows:

Ewels PA, Peltzer A, Fillinger S, Alneberg JA, Patel H, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. nf-core: Community curated bioinformatics pipelines. bioRxiv. 2019. p. 610741. doi: 10.1101/610741.