You've got count matrices and metadata, you need differential expression with DESeq2, and you want the answer to match what's actually in the published notebook. This skill provides audited wrapper scripts that emit every common interpretation at once: multiple filter combinations (strict padj+LFC+baseMean, padj+LFC-only, padj-only), shrunk and unshrunk fold changes, multi-contrast Venn regions with different denominators, and correlation/PCA variants across transforms. The core insight is that questions phrased as "using DESeq2, how many genes..." are usually asking you to read the executed notebook's output, not rerun the analysis. When you do need to rerun, the wrappers handle sample exclusions, covariate designs, and LFC shrinkage methods in one deterministic call so you're not debugging subtle filter mismatches between your reimplementation and the original.
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-rnaseq-deseq2