Nov 1, 2016

Improved methods for multi-trait fine mapping of pleiotropic risk loci

Bioinformatics
Gleb KichaevBogdan Pasaniuc

Abstract

Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation. In this work we introduce a new approach, fastPAINTOR, that leverages evidence across correlated traits, as well as functional annotation data, to improve fine-mapping accuracy at pleiotropic risk loci. To improve computational efficiency, we describe an new importance sampling scheme to perform model inference. First, we demonstrate in simulations that by leveraging functional annotation data, fastPAINTOR increases fine-mapping resolution relative to existing methods. Next, we show that jointly modeling pleiotropic risk regions improves fine-mapping resolution compared to standard single trait and pleiotropic fine mapping strategies. We report a reduction in the number of SNPs required for follow-up in order to capture 90% of the causal variant...Continue Reading

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  • Citations36

References

Mentioned in this Paper

Computer Software
Genome-Wide Association Study
Research
Follow-up
Genome
Dysequilibrium Syndrome
Bio-Informatics
Genome Mapping
Computer Programs and Programming
Genomics

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