bio-workflows-expression-to-pathways
Workflow from differential expression results to functional enrichment analysis. Covers GO, KEGG, Reactome enrichment with clusterProfiler and visualization. Use when taking DE results to pathway enrichment.
npx skills add BioTender-max/awesome-bio-agent-skills --skill expression-to-pathways --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.
## Version Compatibility Reference examples tested with: DESeq2 1.42+, R stats (base), ReactomePA 1.46+, clusterProfiler 4.10+, ggplot2 3.5+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Expression to Pathways Workflow **"Find enriched pathways from my differential expression results"** → Orchestrate GO enrichment (clusterProfiler), GSEA, KEGG/Reactome pathway mapping, and enrichment visualization from DE gene lists or ranked gene lists. Convert differential expression results into biological insights through functional enrichment analysis. ## Method Selection | Scenario | Method | Why | |----------|--------|-----| | Have DE results with Wald stat / t-stat for all genes | GSEA (Step 4) | Uses full ranking; no arbitrary cutoff; ~35% higher F1 than ORA | | Clear gene list from non-DE source (co-expression, GWAS) | ORA (Steps 1-3) | No ranking available | | RNA-seq with known gene length bias | GOseq (goseq package) | S
- Version Compatibility
- Method Selection
- Workflow Overview
- Input Preparation
- From DESeq2 Results
- Gene ID Conversion
- Step 1: GO Over-representation Analysis
- Step 2: KEGG Pathway Enrichment
- Step 3: Reactome Pathway Enrichment
- Step 4: Gene Set Enrichment Analysis (GSEA)
- Step 5: Visualization
- Step 6: Export Results
- Parameter Recommendations
- Troubleshooting
What does the bio-workflows-expression-to-pathways skill do?
Workflow from differential expression results to functional enrichment analysis. Covers GO, KEGG, Reactome enrichment with clusterProfiler and visualization. Use when taking DE results to pathway enrichment.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill expression-to-pathways --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 BioTender-max/awesome-bio-agent-skills, a repository with 135 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.