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PMID: 16441260 Published · ppublish English Comparative Study Journal Article Research Support, Non-U.S. Gov't

Case-control association tests correcting for population stratification.

Annals of human genetics ·Vol. 70 ·No. Pt 1 ·2006-01-00 ·Pages 98-115

Köhler K, Bickeböller H

Abstract

In case-control association studies unobserved population stratification may act as a confounder, leading to an increased number of false positive results. Methods accounting for population structure by using additional genetic markers broadly follow one of two concepts: Genomic Control (GC) and Structured Association (SA). While extending existing methods of Structured Association we show that it is necessary to incorporate phenotypic information when inferring population structure, otherwise a systematic bias is introduced. Moreover, for moderate population stratification a Wald test statistic should be preferred as a Structured Association test statistic in comparison to a likelihood ratio test. The introduced extensions are compared to existing methods of Structured Association, as well as to Genomic Control, in a simulation study which is based on realistic situations of large case-control studies with moderate population stratification. A disadvantage of Genomic Control turns out to be the large variation in estimating the variance inflation factor, as well as the power loss if population structure increases. We come to the overall conclusion that Structured Association, if applied correctly, is superior to Genomic Control, at least in the case of simple population structure as simulated here.

MeSH Terms
Case-Control Studies Computer Simulation Genetics, Population Models, Genetic Phenotype Research Design
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Köhler K
Department of Genetic Epidemiology, University of Göttingen, Göttingen, Germany. karola.koehler@medizin.uni-goettingen.de
Bickeböller H
Article Info
Journal
Annals of human genetics
Abbr.
Ann Hum Genet
ISSN
0003-4800
Published
2006-01-00
Pages
98-115
Language
English
Region
England
NLM ID
0416661
Subset
IM
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