Copyright © 2007 The American Society of Human Genetics. All rights reserved.
The American Journal of Human Genetics, Volume 81, Issue 6, 1158-1168, 1 December 2007
doi:10.1086/522036
Article
So Many Correlated Tests, So Little Time! Rapid Adjustment of P Values for Multiple Correlated Tests
Karen N. Conneely*, a, 
, 
and Michael Boehnkea
a Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor
Address for correspondence and reprints: Karen Conneely, Department of Human Genetics, Emory University School of Medicine, 615 Michael Street, Suite 301, Atlanta, GA 30322* Present affiliation: Department of Human Genetics, Emory University School of Medicine, Atlanta.
Abstract
Contemporary genetic association studies may test hundreds of thousands of genetic variants for association, often with multiple binary and continuous traits or under more than one model of inheritance. Many of these association tests may be correlated with one another because of linkage disequilibrium between nearby markers and correlation between traits and models. Permutation tests and simulation-based methods are often employed to adjust groups of correlated tests for multiple testing, since conventional methods such as Bonferroni correction are overly conservative when tests are correlated. We present here a method of computing P values adjusted for correlated tests (PACT) that attains the accuracy of permutation or simulation-based tests in much less computation time, and we show that our method applies to many common association tests that are based on multiple traits, markers, and genetic models. Simulation demonstrates that PACT attains the power of permutation testing and provides a valid adjustment for hundreds of correlated association tests. In data analyzed as part of the Finland–United States Investigation of NIDDM Genetics (FUSION) study, we observe a near one-to-one relationship (r2>.999) between PACT and the corresponding permutation-based P values, achieving the same precision as permutation testing but thousands of times faster.
Article Information
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