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clusterprofiler-pathways

Performs GO, KEGG, and GSEA enrichment analysis on single-cell DEG lists using clusterProfiler.

Updated May 28, 2026
Search Tags:#bioinformatics#single-cell#pathway enrichment#gsea#kegg#go analysis#clusterprofiler
One-click install
npx skills add https://github.com/cpanse/skills --skill clusterprofiler-pathways-cpanse
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clusterprofiler-pathways
Source: https://github.com/cpanse/skills/tree/main/single-cell-spatial-general/skills/clusterprofiler-pathways
Command: npx skills add https://github.com/cpanse/skills --skill clusterprofiler-pathways-cpanse

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires clusterProfiler, enrichplot, org.Hs.eg.db, org.Mm.eg.db, Seurat, ggplot2, dplyr, and includes references (resource) components.

What problem does it solve? Interpreting long lists of differentially expressed genes from single-cell RNA-seq is difficult without biological context. This Skill turns FindMarkers output into enriched GO terms, KEGG pathways, and GSEA results with publication-ready visualizations on FGCZ infrastructure. ## Core Features & Use Cases - GO and KEGG enrichment: Run enrichGO and enrichKEGG separately on up- and down-regulated genes with BH correction and organism-specific OrgDb packages (human, mouse, rat, zebrafish). - GSEA and multi-group comparison: Perform gseGO on ranked gene lists and compare enrichment across cell types with compareCluster. - Rich visualization set: Generate dotplots, barplots, cnetplots, emapplots, heatplots, and UpSet plots at 300 DPI, plus gene ID conversion with bitr. - Use Case: After running Seurat FindMarkers on cortical excitatory neurons, feed the DEG table into the included perform_enrichment helper to produce GO/KEGG tables and dotplots for both up- and down-regulated genes in one call. ## Quick Start Ask the agent to run clusterProfiler GO and KEGG enrichment on your Seurat FindMarkers DEG results and generate dotplots for up- and down-regulated genes.

Frequently Asked Questions about clusterprofiler-pathways

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run GO enrichment analysis on Seurat FindMarkers results?▼

Filter FindMarkers output by adjusted p-value and log2 fold change, then pass the gene symbols to enrichGO with the appropriate OrgDb package and keyType SYMBOL. Run it separately for up- and down-regulated genes to distinguish their biological processes.

How to convert gene symbols to Entrez IDs for KEGG enrichment in R?▼

Use the bitr function from clusterProfiler with fromType SYMBOL and toType ENTREZID against your organism's OrgDb package. KEGG enrichment requires Entrez IDs, and you should check the conversion rate since some symbols may not map.

Does clusterProfiler support organisms other than human and mouse?▼

Yes, clusterProfiler supports rat, zebrafish, fly, and worm through their respective OrgDb packages such as org.Rn.eg.db and org.Dr.eg.db. For KEGG, use the matching organism code like rno for rat or dre for zebrafish.

Why does enrichGO report that none of the genes can be mapped?▼

This usually means the keyType does not match your gene identifiers or the wrong organism database is loaded. Check your gene format with head(), list valid types with keytypes(), and try ENSEMBL or ENTREZID instead of SYMBOL.

What should I do when no enrichment is found for my gene list?▼

No enrichment often results from too few genes (under five) or overly strict cutoffs. Relax pvalueCutoff to 0.1 and qvalueCutoff to 0.3, or try other ontologies like Molecular Function or Cellular Component instead of Biological Process.

How do I compare pathway enrichment across multiple cell types?▼

Use compareCluster with a named list of gene sets, one per cell type, and fun set to enrichGO. Visualize the result with a faceted dotplot to show enriched terms side by side across clusters.

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