Genome-wide fine-mapping improves identification of causal variants - PubMed
7 hours ago
- #genome-wide analysis
- #causal variants
- #fine-mapping
- Genome-wide fine-mapping (GWFM) enhances the identification of causal variants by integrating functional annotations and global genetic architecture, outperforming traditional locus-specific methods.
- In simulations and real data, GWFM shows superior performance in error control, power, resolution, precision, replication, and trans-ancestry prediction.
- Analysis of 48 complex traits reveals credible sets explaining 18% of SNP-based heritability, with 30% located beyond genome-wide significant loci.
- Modeling suggests that achieving fine-mapping for over 50% of heritability may require around 2 million samples.
- GWFM successfully identifies a known BMI-related variant at FTO and discovers new missense causal variants for schizophrenia and Crohn's disease.