pathway-enrichment
Skill for pathway and gene-set enrichment analysis on gene lists.
About
Performs pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results. Used when the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".
At a glance
- Made for
- Business teams
- Pricing
- Free
- Access
- No sign-in
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Capabilities
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Provenance
- Discovered
- Relayed by github
- Identifier
- urn:air:github.com:k-dense-ai:scientific-agent-skills:pathway-enrichment
- Catalog host
- github.com · via github registry
- Anchor check
- Not anchored
- Last crawled
- seen 8d ago
Discovered through github.com's registry, not anchored by StealthStack. We relay the listing as-is; we have not checked that the URN authority matches the publishing host. How trust works →