Copyright © 2007 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 81, Issue 5, 895-905, 1 November 2007
doi:10.1086/521372
Article
A Randomization Test for Controlling Population Stratification in Whole-Genome Association Studies
Gad Kimmela, c, 
, 
, Michael I. Jordana, b, Eran Halperinc, Ron Shamird and Richard M. Karpa, c
a Computer Science Division University of California Berkeley, and International Computer Science Institute
b Department of Statistics University of California Berkeley, and International Computer Science Institute
c University of California Berkeley, and International Computer Science Institute, Berkeley
d School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv
Address for correspondence and reprints: Dr. Gad Kimmel, Computer Science Division, University of California Berkeley, Berkeley, CA 94720Abstract
Population stratification can be a serious obstacle in the analysis of genomewide association studies. We propose a method for evaluating the significance of association scores in whole-genome cohorts with stratification. Our approach is a randomization test akin to a standard permutation test. It conditions on the genotype matrix and thus takes into account not only the population structure but also the complex linkage disequilibrium structure of the genome. As we show in simulation experiments, our method achieves higher power and significantly better control over false-positive rates than do existing methods. In addition, it can be easily applied to whole-genome association studies.
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