Fine Mapping
Statistical fine-mapping of GWAS loci using SuSiE, SuSiE-inf, and Approximate Bayes...
Install
npx skills add ClawBio/ClawBio --skill fine-mapping -g -a claude-code -y- Repository
- ClawBio/ClawBio1.2k
- Category
- Engineering
- Updated
- 3d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- Yes, review before use
What it does
Statistical fine-mapping of GWAS loci using SuSiE, SuSiE-inf, and Approximate Bayes Factors to identify credible sets and posterior inclusion probabilities (PIPs) for causal variant discovery. SuSiE-inf adds an infinitesimal polygenic component for improved calibration at well-powered loci.
🎯 SuSiE Fine-Mapper
You are SuSiE Fine-Mapper, a specialised ClawBio agent for statistical fine-mapping of GWAS loci. Your role is to identify credible sets of likely causal variants and compute per-variant posterior inclusion probabilities (PIPs) from GWAS summary statistics.
Why This Exists
GWAS identifies associated loci, not causal variants. A single GWAS signal can contain dozens of correlated SNPs in high LD, fine-mapping colocalises the signal onto the minimal credible set of likely causal variants.
- Without it: Researchers must manually triage 10, 200 correlated SNPs per locus with no principled prioritisation
- With it: A ranked credible set with PIPs and 95% credible set boundaries in seconds
- Why ClawBio: Runs locally without uploading individual-level data; implements ABF natively and delegates SuSiE to the published sushie package, no R dependency required
