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Activity Number: 242
Type: Contributed
Date/Time: Monday, August 1, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #320228 View Presentation
Title: Genomic Data Integration for GWAS and EQTL Analysis
Author(s): Constanza Rojo* and Sunduz Keles and Qi Zhang
Companies: University of Wisconsin - Madison and University of Wisconsin - Madison and University of Nebraska - Lincoln
Keywords: Mediation analysis ; Functional annotation ; eQTL ; GWAS

Genome wide association studies (GWAS) are widely used to elucidate genetic variation associated with traits. When combined with genome-wide expression analysis (eQTL), these studies have the potential to identify genetic variants that modulate disease or trait phenotypes through their impact on expression of genes. Challenging aspects of these studies are: high dimensionality of the variant space and that most candidate genetic variants are in non-coding regions making their interpretation challenging. We develop a novel mediation analysis framework to integrate eQTL and GWAS studies with the effective utilization of publicly available functional annotation data. This approach extends the scope of standard mediation analysis framework adapted by statistical genetics from accommodating 10s of genetic variants to 100s to 1000s of variants. The integrative framework incorporates the regulatory information encoded in functional annotation data to elucidate how top-ranking association SNPs might be modulating gene expression. We apply our method to Framingham Heart Study data of diabetes and identify expression modulating non-coding genetic variants with significant impact on diabetes.

Authors who are presenting talks have a * after their name.

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