fine-mapping

What problem does it solve?

This Skill enables the statistical fine-mapping of GWAS loci, identifying credible sets and posterior inclusion probabilities for causal variant discovery.

Core Features & Use Cases

• Fine-Mapping: Statistical fine-mapping of GWAS loci using SuSiE, SuSiE-inf, and Approximate Bayes Factors (ABF).
• Credible Sets: Identifies credible sets of likely causal variants and computes posterior inclusion probabilities (PIPs).
• Visualisation: Generates locus PIP plots, regional association plots, and credible set summary tables.
• Use Case: Researchers can use this Skill to fine-map GWAS loci and identify potential causal variants for further investigation.

Quick Start

Run the fine-mapping skill on your GWAS summary stats and LD matrix. For example:

python skills/fine-mapping/fine_mapping.py --sumstats gwas_sumstats.tsv --ld ld_matrix.npy --output /tmp/finemapping