Association mapping, using a mixture model for complex traits

Genet Epidemiol. 2002 Aug;23(2):181-96. doi: 10.1002/gepi.210.


Association mapping for complex diseases using unrelated individuals can be more powerful than family-based analysis in many settings. In addition, this approach has major practical advantages, including greater efficiency in sample recruitment. Association mapping may lead to false-positive findings, however, if population stratification is not properly considered. In this paper, we propose a method that makes it possible to infer the number of subpopulations by a mixture model, using a set of independent genetic markers and then testing the association between a genetic marker and a trait. The proposed method can be effectively applied in the analysis of both qualitative and quantitative traits. Extensive simulations demonstrate that the method is valid in the presence of a population structure.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Alleles
  • Case-Control Studies
  • Chromosome Mapping / statistics & numerical data*
  • Computer Simulation
  • Gene Frequency
  • Genetics, Population*
  • Genotype
  • Humans
  • Models, Genetic*