A unified approach for quantifying, testing and correcting population stratification in case-control association studies

Prakash Gorroochurn, Susan E. Hodge, Gary A. Heiman, David A. Greenberg

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

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 (δ), 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 δ in association studies (e.g., at α = 0.05, a δ of size 0.416 is small, a δ of size 0.653 is medium, and a δ 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.

Original languageEnglish (US)
Pages (from-to)149-159
Number of pages11
JournalHuman Heredity
Volume64
Issue number3
DOIs
StatePublished - Jun 2007
Externally publishedYes

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Keywords

  • Association studies
  • Delta-centralization
  • False positive rate
  • Genomic control
  • Population stratification

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