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Candidate gene association analysis for a quantitative trait, using parent‐offspring trios
Author(s) -
Gauderman W. James
Publication year - 2003
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.10262
Subject(s) - population stratification , biology , trait , confounding , sample size determination , type i and type ii errors , genetics , population , candidate gene , statistics , genetic association , transmission disequilibrium test , evolutionary biology , mathematics , gene , computer science , allele , genotype , haplotype , demography , single nucleotide polymorphism , sociology , programming language
With the increasing availability of genetic data, many studies of quantitative traits focus on hypotheses related to candidate genes, and also gene‐environment (G×E) and gene‐gene (G×G) interactions. In a population‐based sample, estimates and tests of candidate gene effects can be biased by ethnic confounding, also known as population stratification bias. This paper demonstrates that even a modest degree of ethnic confounding can lead to unacceptably high type I error rates for tests of genetic effects. The parent‐offspring trio design is reviewed, and several forms of the quantitative transmission disequilibrium test (QTDT) are summarized. A variation of the QTDT (QTDT M ) is described that is based on a linear regression model with multiple intercepts, one per parental mating type. This and other models are expanded to allow testing of G×E and G×G interactions. A method for computing required sample sizes using direct computations is described. Sample size requirements for tests of genetic main effects and G×E and G×G interactions are compared across various QTDT approaches to infer their efficiencies relative to one another. The QTDT M is found to meet or exceed the efficiency of other QTDT approaches. For example, the QTDT M is approximately 3% more efficient than the QTDT of Rabinowitz ([1997] Hum. Hered. 47:342–350) for testing a genetic main effect, but can be as much as twice as efficient for testing G×E interaction, and three times more efficient for testing G×G interaction. Genet Epidemiol 25:327–338, 2003. © 2003 Wiley‐Liss, Inc.

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