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Avoiding stratification in association studies

Part 2. Genomics

2.6. SNPs/Haplotypes

Short Specialist Review

  1. Bernie Devlin1,
  2. Kathryn Roeder2

Published Online: 15 JAN 2005

DOI: 10.1002/047001153X.g206304

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Devlin, B. and Roeder, K. 2005. Avoiding stratification in association studies. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 2:2.6:75.

Author Information

  1. 1

    University of Pittsburgh, Pittsburgh, PA, USA

  2. 2

    Carnegie Mellon University, Pittsburgh, PA, USA

Publication History

  1. Published Online: 15 JAN 2005

Abstract

In the study of complex disease, separating causal from confounded factors is a challenge for genetic epidemiologists. Population structure can be an important source of confounding. In the context of population samples, the tools useful for overcoming the effects of population structure are described in terms of experimental design and statistical analysis.

Keywords:

  • genomic control;
  • structured association;
  • population substructure;
  • confounding