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STAR + edgeR/DESeq2/limma-voom + GSEA RNA-seq gene expression analysis workflow

Uses fastp for FASTQ QC and trimming and GENCODE reference genome and annotations. It currently supports two-group experimental conditions, but could be extended to support more complex experimental designs and contrast matrices. Automatically uses wrappers from my personal Snakemake wrappers repository.

Requires Mamba/Conda. Create and activate the workflow conda environment (which provides snakemake):

mamba env create -f envs/rna-seq-star-gex.yaml
mamba activate rna-seq-star-gex

Edit config.yaml, samples.tsv, and units.tsv with the study config and sample and data info.

Run the workflow:

snakemake --use-conda --cores all --resources gencode_download_jobs=2

Snakemake workflow rule graph shown below. For some reason with the latest version of Snakemake the fastp_trim_fastq workflow rule isn't showing up in the rule graph because I use a function with unpack to get raw and trimmed FASTQ inputs.

Snakemake rule graph