tooluniverse-gwas-finemapping
Identify and prioritize causal variants at GWAS loci using statistical fine-mapping and locus-to-gene predictions. Computes posterior probabilities for causal variants, links variants to genes via L2G predictions, annotates functional consequences, and suggests validation strategies. Use when asked to fine-map GWAS loci, prioritize causal variants, identify credible sets, or link GWAS signals to causal genes.
npx skills add BioTender-max/awesome-bio-agent-skills --skill tooluniverse-gwas-finemapping --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.
# GWAS Fine-Mapping & Causal Variant Prioritization Identify and prioritize causal variants at GWAS loci using statistical fine-mapping and locus-to-gene predictions. ## Overview Genome-wide association studies (GWAS) identify genomic regions associated with traits, but linkage disequilibrium (LD) makes it difficult to pinpoint the causal variant. **Fine-mapping** uses Bayesian statistical methods to compute the posterior probability that each variant is causal, given the GWAS summary statistics. This skill provides tools to: - **Prioritize causal variants** using fine-mapping posterior probabilities - **Link variants to genes** using locus-to-gene (L2G) predictions - **Annotate variants** with functional consequences - **Suggest validation strategies** based on fine-mapping results ## Key Concepts ### Credible Sets A **credible set** is a minimal set of variants that contains the causal variant with high confidence (typically 95% or 99%). Each variant in the set has a **posterior probability** of being causal, computed using methods like: - **SuSiE** (Sum of Single Effects) - **FINEMAP** (Bayesian fine-mapping) - **PAINTOR** (Probabilistic Annotation INtegraTOR) ### Posterior Prob
- Overview
- Key Concepts
- Credible Sets
- Posterior Probability
- Locus-to-Gene (L2G) Predictions
- Use Cases
- 1. Prioritize Variants at a Known Locus
- 2. Fine-Map a Specific Variant
- 3. Explore All Loci from a GWAS Study
- 4. Find GWAS Studies for a Disease
- 5. Get Validation Suggestions
- Workflow Example: Complete Fine-Mapping Analysis
- Data Classes
- FineMappingResult
What does the tooluniverse-gwas-finemapping skill do?
Identify and prioritize causal variants at GWAS loci using statistical fine-mapping and locus-to-gene predictions. Computes posterior probabilities for causal variants, links variants to genes via L2G predictions, annotates functional consequences, and suggests validation strategies. Use when asked to fine-map GWAS loci, prioritize causal variants, identify credible sets, or link GWAS signals to causal genes.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill tooluniverse-gwas-finemapping --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.