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Activity Number: 679 - Variable Selection and Prediction Models for Genomic Data
Type: Contributed
Date/Time: Thursday, August 2, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #327174
Title: SMUT: Multi-SNP Mediation Intersection-Union Test
Author(s): Wujuan Zhong* and Cassandra Spracklen and Karen Mohlke and Xiaojing Zheng and Jason P Fine and Yun Li
Companies: University of North Carolina, Chapel Hill and University of North Carolina, Chapel Hill and University of North Carolina, Chapel Hill and University of North Carolina, Chapel Hill and University of North Carolina at Chapel Hill and University of North Carolina at Chapel Hill
Keywords: mediation analysis; multiple SNPs; intersection-union test
Abstract:

Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in regions resulting in no protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing mediation effects of multiple correlated SNPs via a mediator (for example, the expression of a gene in the neighborhood) on phenotypic outcome. We propose SMUT, multi-SNP Mediation intersection-Union Test to fill in the methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 77%, power gains over alternative methods. In addition, SMUT was able to confirm known mediators in a real dataset of Finns for plasma adiponectin level, while many alternative methods failed to generate significant results. We believe SMUT will become a useful tool to shed light on mechanisms underlying GWAS variants, facilitating functional follow-up.


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