This is a Snakemake workflow for generating gene expression counts from RNA-sequencing data using STAR and featureCounts (from the subread package). The workflow is designed to handle both single-end and paired-end sequencing data, as well as sequencing data from multiple lanes. Processing of patient-derived xenograft (PDX) samples is also supported, by using disambiguate to separate graft/host sequence reads.
If you use this workflow in a paper, don't forget to give credits to the authors by citing the URL of this repository and, if available, its DOI (see above).
The standard (non-PDX) workflow essentially performs the following steps:
- Cutadapt is used to trim the input reads for adapters and/or poor-quality base calls.
- The trimmed reads are aligned to the reference genome using STAR.
- The resulting alignments are sorted and indexed using sambamba.
- featureCounts is used to generate gene expression counts.
- The (per sample) counts are merged into a single count file.
- The merged counts are normalized for differences in sequencing depth (using DESeq's median-of-ratios approach) and log-transformed.
This results in the following dependency graph:
The PDX workflow is a slightly modified version of the standard workflow, which aligns the reads to two reference genome (the host and graft reference genomes) and uses disambiguate to remove sequences originating from the host organism. See the documentation for more details.
Documentation is available at: http://jrderuiter.github.io/snakemake-rnaseq.
This software is released under the MIT license.