gsea-pathway-analyzer
Gene Set Enrichment Analysis skill for functional annotation and pathway interpretation
npx skills add a5c-ai/babysitter --skill gsea-pathway-analyzer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# GSEA Pathway Analyzer Skill ## Purpose Enable Gene Set Enrichment Analysis for functional annotation and pathway interpretation. ## Capabilities - Preranked GSEA execution - Gene ontology enrichment - KEGG/Reactome pathway analysis - Custom gene set support - Leading edge analysis - Publication-ready visualizations ## Usage Guidelines - Rank genes appropriately for analysis type - Select relevant gene set collections - Apply multiple testing correction - Identify leading edge genes for interpretation - Generate clear visualizations - Document gene set versions ## Dependencies - GSEA - clusterProfiler - g:Profiler - Enrichr ## Process Integration - RNA-seq Differential Expression Analysis (rnaseq-differential-expression) - Single-Cell RNA-seq Analysis (scrnaseq-analysis) - Multi-Omics Data Integration (multi-omics-integration)
- Purpose
- Capabilities
- Usage Guidelines
- Dependencies
- Process Integration
What does the gsea-pathway-analyzer skill do?
Gene Set Enrichment Analysis skill for functional annotation and pathway interpretation
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill gsea-pathway-analyzer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.