bioRxivBioinformatics
GenoWAP: Post-GWAS Prioritization Through Integrated Analysis of Genomic Functional Annotation
Abstract
MotivationGenome-wide association study (GWAS) has been a great success in the past decade. However, significant challenges still remain in both identifying new risk loci and interpreting results. Bonferroni-corrected significance level is known to be conservative, leading to insufficient statistical power when the effect size is moderate at risk locus. Complex structure of linkage disequilibrium also makes it challenging to separate causal variants from nonfunctional ones in large haplotype blocks.\n\nResultsWe describe GenoWAP, a post-GWAS prioritization method that integrates genomic functional annotation and GWAS test statistics. The effectiveness of GenoWAP is demonstrated through its applications to Crohns disease and schizophrenia using the largest studies available, where highly ranked loci show substantially stronger signals in the whole dataset after prioritization based on a subset of samples. At the single nucleotide polymorphism (SNP) level, top ranked SNPs after prioritization have both higher replication rates and consistently stronger enrichment of eQTLs. Within each risk locus, GenoWAP is also able to distinguish functional sites from groups of correlated SNPs.\n\nAvailability and ImplementationGenoWAP is freely available on the web at http://genocanyon.med.yale.edu/GenoWAP
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- research focus: variant effect prediction
- approach: statistical model
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