Association Analysis Of Quantitative Traits Based On Genetic Model Selection

In genetic association studies with quantitative trait loci(QTL),the association between a candidate genetic marker and the trait of interest is commonly examined by the omnibus F test or by the t-test corresponding to a given genetic model or mode of inheritance.It is known that the t-test with a correct model specification is more powerful than the F test.However,since the underlying genetic model is rarely known in practice,use of a model-specific t-test may incur substantial power loss.Robust-efficient tests,such as the Maximin Efficiency Robust Test(MERT)and MAX3 have been proposed.In this paper,we propose a novel robust-efficient approach,i.e.,genetic model selection(GMS),for quantitative trait.GMS is a two-step procedure that selecting genetic model by testing Hardy-Weinberg disequilibrium(HWD)with extremal samples of population in the first step and then applying corresponding genetic model-specific t-test in the second step.Simulations show that GMS is not only more efficient than MERT and MAX3,but also has comparable power to the optimal t-test when the genetic model is known.Application to the data from Alzheimer’s Disease Neuroimaging Initiative(ADNI)cohort demonstrate the promising performance of the proposed approach for identifying biological meaningful SNPs on chromosome 19.