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Activity Number:
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527
- Contributed Poster Presentations: Section on Statistics in Genomics and Genetics
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Type:
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Contributed
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Date/Time:
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Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Genomics and Genetics
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Abstract #306599
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Title:
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Integrating GWAS and Omics QTL Summary Statistics in Elucidating Molecular Mechanisms of Trait-Associated SNPs and Detecting Pleiotropy in Human Complex Traits
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Author(s):
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Kevin J Gleason* and Fan Yang and Lin Chen
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Companies:
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University of Chicago and University of Colorado Denver and University of Chicago
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Keywords:
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omics;
GWAS;
summary statistics
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Abstract:
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We propose a method to integrate summary statistics from GWAS and omics QTL studies to map complex trait associations and elucidate the molecular mechanisms through which SNPs affect complex traits. Our computational tool – Primo (Package in R for Integrative Multi-Omics association analysis) – simultaneously analyzes a moderately large number of sets of summary statistics, allowing the comprehensive integration of QTL statistics for multi-omics traits in multiple tissue types. In contrast to meta-analysis approaches that test for overall effects, Primo exhibits great flexibility in allowing study heterogeneity and sample correlations, and in identifying SNPs in interpretable combinations of association patterns. We evaluated the performance of Primo through extensive simulations and applied Primo to two applications: to examine the omics trait associations for known GWAS SNPs and to identify pleiotropic effects in pairs of complex traits by integrating GWAS summary statistics and omics QTL statistics in trait-relevant tissue types from the Gene-Tissue Exchange Project and other studies. The package is freely available for download at https://github.com/kjgleason/primo.
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Authors who are presenting talks have a * after their name.
