This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 599
Type: Invited
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #306299
Title: Genomewide Association Studies in Mixed Populations
Author(s): Hua Tang*+
Companies: Stanford University
Address: , , ,
Keywords: genetic admixture ; genome-wide association study

Admixture mapping is a method that exploits ancestral allele frequency differences to map disease susceptibility genes in recently admixed populations such as African Americans and Latinos. With the advent of high density genotyping platforms with as many as 500K SNPs or more for genome-wide association studies, a question arises as to the relative power of direct association analysis versus admixture mapping in such populations. Previously we have shown that with high-density SNP arrays, it is possible to accurately reconstruct the ancestry block structure of an admixed individual. Here we evaluate the relative efficiency of genotype- and ancestry-based association analyses. We also consider a strategy that combines the two sources of information.

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