Accommodating population stratification in case-control association analysis: a new test and its application to genome-wide study on rheumatoid arthritis

Yufang Zhang; Xiangjun Xiao; Kai Wang

doi:10.1186/1753-6561-3-s7-s111

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Accommodating population stratification in case-control association analysis: a new test and its application to genome-wide study on rheumatoid arthritis

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Accommodating population stratification in case-control association analysis: a new test and its application to genome-wide study on rheumatoid arthritis

Yufang Zhang, Xiangjun Xiao and Kai Wang

BMC proceedings, Vol.3(Suppl 7), pp.S111-S111

12/15/2009

DOI: 10.1186/1753-6561-3-s7-s111

PMCID: PMC2795883

PMID: 20017976

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Abstract

It is well known that conventional association tests can lead to excessive false positives when there is population stratification. We propose a new test for detecting genetic association with a case-control study design. Unlike some other methods for handling population stratification, we treat the cases as a population and the controls as another one even though each of them may be a mixture of several sub-populations. A likelihood-ratio test is used to test whether the allele frequency of a testing single-nucleotide polymorphism in the case population is the same as that in the control population. This new test is applied to the Genetic Analysis Workshop 16 Problem 1 data on rheumatoid arthritis. Compared with the Pearson chi-square genotype test, the association strength of many single-nucleotide polymorphisms is decreased while the signal at the HLA region on 6p21 is maintained.

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Title: Subtitle: Accommodating population stratification in case-control association analysis: a new test and its application to genome-wide study on rheumatoid arthritis
Creators: Yufang Zhang - Department of Biostatistics, University of Iowa, 200 Hawkins Drive C227 GH, Iowa City, Iowa 52242 USA
Xiangjun Xiao - Department of Biostatistics, University of Iowa, 200 Hawkins Drive C227 GH, Iowa City, Iowa 52242 USA
Kai Wang - Department of Biostatistics, University of Iowa, 200 Hawkins Drive C227 GH, Iowa City, Iowa 52242 USA
Resource Type: Journal article
Publication Details: BMC proceedings, Vol.3(Suppl 7), pp.S111-S111
DOI: 10.1186/1753-6561-3-s7-s111
PMID: 20017976
PMCID: PMC2795883
NLM abbreviation: BMC Proc
ISSN: 1753-6561
eISSN: 1753-6561
Publisher: BioMed Central
Language: English
Date published: 12/15/2009
Academic Unit: Biostatistics
Record Identifier: 9983997347402771

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