Association tests for complex disease genes while controlling population stratification

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© 2007 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. Although genetic association studies using unrelated individuals may be subject to bias caused by population stratification, alternative familybased association methods that are robust to population stratification may be less powerful. This chapter discusses methods that use unrelated individuals to identify associations between candidate markers and traits of interest (both qualitative and quantitative), while controlling population stratification through a set of genomic markers of the same individual. These methods can control population stratification and are more powerful than family-based methods. We first introduce association tests based on population samples in a homogeneous population, and discuss why population stratification can cause false-positive results in association studies. Then, we review established methods, which include the genomic control, structure association, and semiparametric approaches, for controlling false-positive results by using a set of unlinked markers of the same individual instead of using family members in family-based association studies. Finally, we discuss some possible extensions of the existing methods and some topics that need further investigation.

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Current Topics in Human Genetics: Studies in Complex Diseases