bio-pathway-gsea
Gene Set Enrichment Analysis using clusterProfiler gseGO and gseKEGG. Uses a ranked gene list to find coordinated changes in gene sets without requiring arbitrary significance cutoffs. Detects subtle but coordinated expression changes.
npx skills add majiayu000/claude-skill-registry --skill gsea --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.
# Gene Set Enrichment Analysis (GSEA) ## Core Concept GSEA uses **all genes ranked by a statistic** (log2FC, signed p-value) rather than a subset of significant genes. It finds gene sets where members are enriched at the top or bottom of the ranked list. ## Prepare Ranked Gene List ```r library(clusterProfiler) library(org.Hs.eg.db) de_results <- read.csv('de_results.csv') # Create named vector: values = statistic, names = gene IDs gene_list <- de_results$log2FoldChange names(gene_list) <- de_results$gene_id # Sort in decreasing order (REQUIRED) gene_list <- sort(gene_list, decreasing = TRUE) ``` ## Convert Gene IDs for GSEA ```r # Convert symbols to Entrez IDs gene_ids <- bitr(names(gene_list), fromType = 'SYMBOL', toType = 'ENTREZID', OrgDb = org.Hs.eg.db) # Create ranked list with Entrez IDs gene_list_entrez <- gene_list[names(gene_list) %in% gene_ids$SYMBOL] names(gene_list_entrez) <- gene_ids$ENTREZID[match(names(gene_list_entrez), gene_ids$SYMBOL)] gene_list_entrez <- sort(gene_list_entrez, decreasing = TRUE) ``` ## Alternative Ranking Statistics ```r # Signed p-value (recommended for detecting both up and down) gene_list <- -log10(de_results$pvalue) * sign(de_results$log2Fol
- Core Concept
- Prepare Ranked Gene List
- Convert Gene IDs for GSEA
- Alternative Ranking Statistics
- GSEA with GO
- GSEA with KEGG
- GSEA with Custom Gene Sets
- MSigDB Gene Sets
- Understanding Results
- Interpreting NES (Normalized Enrichment Score)
- Key Parameters
- Export Results
- Notes
- Related Skills
What does the bio-pathway-gsea skill do?
Gene Set Enrichment Analysis using clusterProfiler gseGO and gseKEGG. Uses a ranked gene list to find coordinated changes in gene sets without requiring arbitrary significance cutoffs. Detects subtle but coordinated expression changes.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill gsea --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 majiayu000/claude-skill-registry, a repository with 534 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.