A randomization test for controlling population stratification in whole-genome association studies.
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.
Kimmel
Gad
G
Computer Science Division, University of California Berkeley, Berkeley, CA 94720, USA. kimmel@cs.berkeley.edu
Jordan
Michael I
MI
Halperin
Eran
E
Shamir
Ron
R
Karp
Richard M
RM
D000465:Algorithms; D030541:Databases, Genetic; D020022:Genetic Predisposition to Disease; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide / Q000235:genetics