tooluniverse-rnaseq-deseq2

tooluniverse-rnaseq-deseq2 is a Bioinformatics & life sciences skill for AI agents, published by mims-harvard in the ToolUniverse repository on GitHub. Skillspace rates tooluniverse-rnaseq-deseq2 C (72/100) and it passed the safety scan; the rating is based on static analysis only.

RNA-seq differential expression analysis with DESeq2, edgeR, and limma-voom — DEG lists, fold changes, dispersion estimation, design formulas including covariates, multi-condition contrasts, and Venn-set operations across groups. Routes across DESeq2 (default), edgeR (QL-F / exact test for small replicate counts), and limma-voom (large n / complex designs). Use when you have a count matrix + metadata, want to find DEGs, or need dispersion/PCA/clustering analysis. Includes RULE ZERO precedence (read executed.ipynb if present).

Grade

C

Quality

72 / 100

Safety

Passed

GitHub stars

1,566

Unproven: rated by static analysis only, not yet compared head-to-head.

Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: it is a near-duplicate variant of another skill. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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