bio-pathway-reactome
Reactome pathway enrichment using ReactomePA package. Use when analyzing gene lists against Reactome's curated peer-reviewed pathway database. Performs over-representation analysis and GSEA with visualization and pathway hierarchy exploration.
npx skills add majiayu000/claude-skill-registry --skill reactome-pathways-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.
# Reactome Pathway Enrichment ## Core Pattern - Over-Representation Analysis ```r library(ReactomePA) library(org.Hs.eg.db) pathway_result <- enrichPathway( gene = entrez_ids, # Character vector of Entrez IDs organism = 'human', # human, rat, mouse, celegans, yeast, zebrafish, fly pvalueCutoff = 0.05, pAdjustMethod = 'BH', readable = TRUE # Convert to gene symbols ) head(as.data.frame(pathway_result)) ``` ## Prepare Gene List from DE Results ```r library(clusterProfiler) de_results <- read.csv('de_results.csv') sig_genes <- de_results[de_results$padj < 0.05 & abs(de_results$log2FoldChange) > 1, 'gene_symbol'] gene_ids <- bitr(sig_genes, fromType = 'SYMBOL', toType = 'ENTREZID', OrgDb = org.Hs.eg.db) entrez_ids <- gene_ids$ENTREZID ``` ## GSEA on Reactome Pathways ```r # Create ranked gene list (named vector sorted by statistic) gene_list <- de_results$log2FoldChange names(gene_list) <- de_results$entrez_id gene_list <- sort(gene_list, decreasing = TRUE) gsea_result <- gsePathway( geneList = gene_list, organism = 'human', pvalueCutoff = 0.05, pAdjustMethod = 'BH', verbose = FALSE ) head(as.data.frame(gsea_result)) ``` ## With Background Universe ```r all_genes <- de_results$entrez_i
- Core Pattern - Over-Representation Analysis
- Prepare Gene List from DE Results
- GSEA on Reactome Pathways
- With Background Universe
- Visualization
- View Pathway in Browser
- Export Results
- Different Organisms
- Compare Clusters
- Key Parameters
- Supported Organisms
- Related Skills
What does the bio-pathway-reactome skill do?
Reactome pathway enrichment using ReactomePA package. Use when analyzing gene lists against Reactome's curated peer-reviewed pathway database. Performs over-representation analysis and GSEA with visualization and pathway hierarchy exploration.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill reactome-pathways-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.