Genotype-Based Matching to Correct for Population Stratification in
Large-Scale Case-Control Genetic Association Studies
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Case-control association tests are generally more powerful than family-based association tests but population stratification can lead to spurious disease-marker association or mask a true association. We propose a similarity score matching approach that matches cases with controls and perform association test condition on the matched set so as to adjust for underlying population structures and potentially increase power. The genetic similarity score matching analysis consists of three steps:
1) Similarity score calculation for each pair of case and control
2) Optimal full matching to match cases with controls
3) Conditional logistic regression (additive or 2 d.f. test) |
Comments and suggestions are appreciated! Please email me: lianglim@umich.edu and Weihua Guan wguan@umich.edu |
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Input data format, meaning of parameters and output interpretation |
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Citation: |
Weihua Guan*, Liming Liang*, Michael Boehnke, Gonçalo R. Abecasis. Genotype-based matching to correct for population stratification in large-scale case-control genetic association studies. (2008)
* These authors contributed equally to this work. |
