GSEApy (Claude Skill)

GSEA and over-representation analysis (ORA) for RNA-seq and proteomics.


Type	Claude Skill
Supplier	jaechang-hits (community OSS, CC BY 4.0)
Availability	GA — part of the BixBench-evaluated SciAgent-Skills collection
Pricing	Free / OSS (MIT)
Capabilities	Read/Write — Claude runs the skill’s Python locally (Bash), not as an MCP tool

How to install

SciAgent-Skills is not an npm package — skills are plain markdown read directly by the agent (no npx/npm).

Claude Code — clone and load as a plugin:
```
git clone https://github.com/jaechang-hits/SciAgent-Skills
```
Then inside Claude Code run /plugin install sciagent-skills (verify it appears under /plugin → Installed). Clone into your project directory so Claude Code picks the skills up via CLAUDE.md.
Manual / other agents — point the agent at the skill file directly:
```
cp -r SciAgent-Skills/skills/genomics-bioinformatics/rnaseq/gseapy-gene-enrichment ~/.claude/skills/
```
The skill declares its own Python dependencies in its SKILL.md; install them when prompted on first use.

What it does

GSEA and over-representation analysis (ORA) for RNA-seq and proteomics. Wraps Enrichr for ORA against MSigDB, KEGG, GO, and 200+ databases; runs preranked GSEA on ranked DE gene lists. Outputs enrichment tables and running-score plots. Use after DESeq2 or edgeR for pathway-level interpretation.

Primary use cases: GSEA and over-representation analysis (ORA) for RNA-seq and proteomics.

Notes

Distributed as a SKILL.md (plus code examples) in the SciAgent-Skills collection — Claude executes it locally via Bash/Python rather than as an MCP server. Upstream license: MIT. The skill directory upstream is skills/genomics-bioinformatics/rnaseq/gseapy-gene-enrichment.

Sources

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