期刊
HUMAN HEREDITY
卷 64, 期 3, 页码 149-159出版社
KARGER
DOI: 10.1159/000102988
关键词
association studies; population stratification; genomic control; delta centralization; false positive rate
资金
- NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [R55DK031813, R01DK031775, R01DK031813] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R01NS027941] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE ON ALCOHOL ABUSE AND ALCOHOLISM [R01AA013654] Funding Source: NIH RePORTER
- NIAAA NIH HHS [R01 AA013654] Funding Source: Medline
- NIDDK NIH HHS [R01 DK031775, R01 DK031813, DK31775, DK-31813] Funding Source: Medline
- NINDS NIH HHS [NS27941, R01 NS027941] Funding Source: Medline
The HapMap project has given case-control association studies a unique opportunity to uncover the genetic basis of complex diseases. However, persistent issues in such studies remain the proper quantification of, testing for, and correction for population stratification ( PS). In this paper, we present the first unified paradigm that addresses all three fundamental issues within one statistical framework. Our unified approach makes use of an omnibus quantity (delta), which can be estimated in a case-control study from suitable null loci. We show how this estimated value can be used to quantify PS, to statistically test for PS, and to correct for PS, all in the context of case-control studies. Moreover, we provide guidelines for interpreting values of delta in association studies ( e. g., at alpha = 0.05, a delta of size 0.416 is small, a delta of size 0.653 is medium, and a delta of size 1.115 is large). A novel feature of our testing procedure is its ability to test for either strictly any PS or only 'practically important' PS. We also performed simulations to compare our correction procedure with Genomic Control (GC). Our results show that, unlike GC, it maintains good Type I error rates and power across all levels of PS. Copyright (c) 2007 S. Karger AG, Basel.
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