bio-pathway-gsea
Gene Set Enrichment Analysis using clusterProfiler gseGO and gseKEGG. Use when analyzing ranked gene lists to find coordinated expression changes in gene sets without arbitrary significance cutoffs. Detects subtle but coordinated expression changes.
npx skills add majiayu000/claude-skill-registry --skill gsea-gptomics-bioskills-2 --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. Use when analyzing ranked gene lists to find coordinated expression changes in gene sets without arbitrary significance cutoffs. Detects subtle but coordinated expression changes.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill gsea-gptomics-bioskills-2 --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.