GSM (genetic similarity score matching)is a software for efficient matched analysis of cases and controls in a genome-wide or large-scale candidate gene association study. GSM comprises three steps: (1) calculating similarity scores for pairs of individuals using the genotype data; (2) matching sets of cases and controls based on the similarity scores so that matched cases and controls have similar genetic background; and (3) using conditional logistic regression to perform association tests. Through computer simulation we show that GSM correctly controls false-positive rates and improves power to detect true disease predisposing variants
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Weihua Guan*, Liming Liang*, Michael Boehnke, Gonçalo R. Abecasis (2009).
Genotype-based matching to correct for population stratification in large-scale case-control genetic association studies.
Genet Epidemiol DOI:10.1002/gepi.20403