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 FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-pathway-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. ## Prepare Ranked Gene List **Goal:** Create a sorted named vector of gene-level statistics suitable for GSEA input. **Approach:** Extract fold changes (or other statistics) from DE results, name by gene ID, and sort in decreasing order. **"Run GSEA on my differential expression results"** → Rank all genes by expression statistic and test whether predefined gene sets cluster toward the extremes of the ranked list. ```r library(clusterProfiler) library(org.Hs.eg.db) de_results <- read.csv('de_results.csv') # Create named vector: values = statistic, names =
- Version Compatibility
- 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
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 FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-pathway-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 FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 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.