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Abstract Details

Activity Number: 526
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #306606
Title: A Simulation Adjustment for Ancestry Using GWAS in Recently Admixed Populations
Author(s): Jianqi Zhang*+ and Daniel O. Stram
Companies: University of Southern California and University of Southern California
Address: 2001 N Soto St., Los Angeles, CA, 90032, United States
Keywords: genome wide association studies ; admixture population ; population stratification ; global ancestry ; local ancestry ; linkage disequilibrium ; type I error ; power ; simulation

Association analysis in recently admixed populations tends to produce spurious associations. In this study, we simulated recent population admixture: two established populations first formed a mixed population, and random mating took place for two generations. In the admixed population, we simulated genetic diseases using several polygenic models. Keeping track of the global ancestry of each individual and the local ancestry for each SNP we compared the effectiveness of adjusting for global and local ancestry in removing spurious associations and retaining power. We found that type I error rates were often controlled by only adjusting for global ancestry. However when causal SNPs were clustered, type I inflation was observed for non-causal SNPs that were near to the clusters of causal SNPs, even after adjustment for global ancestry. These false positive associations were reduced to their expected levels by controlling for local ancestry. The power of studies using admixed populations and the power of studies based on the ancestral populations were compared.

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