metabolicfeatures
Performs enrichment analysis (GSEA-based) for metabolic pathways across different cell groups to identify significantly enriched pathways. Uses fast gene set enrichment analysis (fgsea package) to rank pathways by their association with specific clusters, conditions, or cell states. Generates summary plots and enrichment visualizations for biological interpretation.
npx skills add majiayu000/claude-skill-registry --skill metabolicfeatures --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.
# MetabolicFeatures Process Configuration ## Purpose Performs enrichment analysis (GSEA-based) for metabolic pathways across different cell groups to identify significantly enriched pathways. Uses fast gene set enrichment analysis (fgsea package) to rank pathways by their association with specific clusters, conditions, or cell states. Generates summary plots and enrichment visualizations for biological interpretation. ## When to Use - **Identify differentially active pathways**: When you need to find which metabolic pathways are enriched in specific cell groups - **Compare pathway enrichment**: To identify metabolic differences between clusters, treatments, or conditions - **After pathway activity scoring**: Complements MetabolicPathwayActivity by providing statistical enrichment (p-values, FDR) - **Part of ScrnaMetabolicLandscape**: Runs in parallel with MetabolicPathwayActivity and MetabolicPathwayHeterogeneity - **GSEA-based analysis**: When you want enrichment scores based on ranked gene lists (signal-to-noise, t-test, fold change) ## Configuration Structure ### Process Enablement MetabolicFeatures is part of the ScrnaMetabolicLandscape group. Enable it by enabling the group: `
- Purpose
- When to Use
- Configuration Structure
- Process Enablement
- Input Specification
- Environment Variables
- Gene Ranking Methods (prerankmethod)
- Available Methods
- Method Selection Guide
- FGSEA Parameters
- Core Parameters
- FGSEA Algorithm
- Reference
- Comparison Groups
What does the metabolicfeatures skill do?
Performs enrichment analysis (GSEA-based) for metabolic pathways across different cell groups to identify significantly enriched pathways. Uses fast gene set enrichment analysis (fgsea package) to rank pathways by their association with specific clusters, conditions, or cell states. Generates summary plots and enrichment visualizations for biological interpretation.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill metabolicfeatures --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.