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 BioTender-max/awesome-bio-agent-skills --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.
## Version Compatibility Reference examples tested with: DESeq2 1.42+ 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. # 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. ## When to Use GSEA vs ORA | Scenario | Preferred | Why | |----------|-----------|-----| | Have ranked DE results for all genes | GSEA | Uses full information; no arbitrary cutoff | | Biological signal involves many modest but coordinated changes | GSEA | Core strength -- detects "distributed enrichment" ORA misses | | Gene list NOT from ranking (co-expression module, GWAS hits) | ORA | No meaningful ranking exists | | Few total measured genes, cannot construct meaningful ranking | ORA | GSEA needs large ranked lists to be powerful | In benchmarks, GSEA-f
- Version Compatibility
- Core Concept
- When to Use GSEA vs ORA
- Prepare Ranked Gene List
- Convert Gene IDs for GSEA
- Ranking Metric Selection
- GSEA with GO
- GSEA with KEGG
- GSEA with Custom Gene Sets
- MSigDB Gene Sets
- Understanding Results
- Interpreting NES (Normalized Enrichment Score)
- Leading Edge Interpretation
- Key Parameters
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 BioTender-max/awesome-bio-agent-skills --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 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.