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Ann Hum Genet. 2011 May;75(3):418-27. doi: 10.1111/j.1469-1809.2010.00639.x. Epub 2011 Jan 31.

A comparison of association methods correcting for population stratification in case-control studies.

Author information

1
Department of Epidemiology and Public Health, Yale University, New Haven, CT 06510, USA.

Abstract

Population stratification is an important issue in case-control studies of disease-marker association. Failure to properly account for population structure can lead to spurious association or reduced power. In this article, we compare the performance of six methods correcting for population stratification in case-control association studies. These methods include genomic control (GC), EIGENSTRAT, principal component-based logistic regression (PCA-L), LAPSTRUCT, ROADTRIPS, and EMMAX. We also include the uncorrected Armitage test for comparison. In the simulation studies, we consider a wide range of population structure models for unrelated samples, including admixture. Our simulation results suggest that PCA-L and LAPSTRUCT perform well over all the scenarios studied, whereas GC, ROADTRIPS, and EMMAX fail to correct for population structure at single nucleotide polymorphisms (SNPs) that show strong differentiation across ancestral populations. The Armitage test does not adjust for confounding due to stratification thus has inflated type I error. Among all correction methods, EMMAX has the greatest power, based on the population structure settings considered for samples with unrelated individuals. The three methods, EIGENSTRAT, PCA-L, and LAPSTRUCT, are comparable, and outperform both GC and ROADTRIPS in almost all situations.

PMID:
21281271
PMCID:
PMC3215268
DOI:
10.1111/j.1469-1809.2010.00639.x
[Indexed for MEDLINE]
Free PMC Article

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