bio-pathway-gsea - Run ranked gene set enrichment analysis
Analyzes ranked gene vectors with GO, KEGG, Reactome, and MSigDB GSEA, and scores per-sample pathway activity with ssGSEA or GSVA.
Tags
Updated: 2026-10-06Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Build ranked gene vectors
- Run GO enrichment analysis
- Run KEGG enrichment analysis
- Run Reactome enrichment analysis
- Run MSigDB GSEA
- Score sample pathway activity
- Interpret leading-edge genes
- Compare permutation strategies
Inputs
- Differential expression results
- Named ranked gene vector
- Gene identifiers
- Expression matrix
- Phenotype labels
- Design matrix
- Gene set collection
- Gene set version or date
- Organism annotation
Outputs
- Enrichment result tables
- Normalized enrichment scores
- Adjusted p-values
- Leading-edge gene lists
- Per-sample pathway scores
- Enrichment plots
Requirements
- R environment
- clusterProfiler 4.18.4 or later
- org.Hs.eg.db 3.22 or later
- msigdbr 26 or later
- fgsea 1.36 or later
- Installed organism annotations
- KEGG REST API access for KEGG analysis