bulk-rnaseq
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g. "analyze my RNA-seq", "FASTQ to DESeq2", "run nf-core/rnaseq", "STAR/Salmon quantification", "build a counts matrix for DESeq2", or "go from reads to differentially expressed genes and enriched pathways". Routes between an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and covers experimental design, strandedness, and QC gates. For single-cell RNA-seq use the scanpy skill instead.
- Version
- 1.0
- License
- MIT
Pinned to revision de66e10cd0c8, so it is the text this page describes rather than whatever the author pushed since.
Files
- skills/bulk-rnaseq/SKILL.md
- skills/bulk-rnaseq/references/counts-and-handoff.md
- skills/bulk-rnaseq/references/design-and-qc.md
- skills/bulk-rnaseq/references/upstream-manual.md
- skills/bulk-rnaseq/references/upstream-nfcore.md
- skills/bulk-rnaseq/scripts/build_counts_matrix.py
- skills/bulk-rnaseq/scripts/validate_samplesheet.py
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