Bulk RNA-seq Differential Expression

Use this skill when the user has raw counts or a count-generation output and wants differential expression, contrasts, QC plots, or ranked gene tables.

Essential Inputs

Confirm:

• raw count matrix path and sample metadata path
• gene ID type and annotation mapping requirement
• biological conditions, replicates, batch variables, donor pairing, covariates, and exclusions
• exact contrasts and baseline levels
• preferred statistical framework: DESeq2, edgeR, limma-voom, or existing lab standard
• output needs: normalized counts, PCA, sample distance, volcano plots, heatmaps, ranked tables, GSEA-ready lists

Preconditions

Do not start differential expression until: