Simultaneous genetic association test on multiple traits

Dr. Zeny Feng, Department of Mathematics & Statistics, University of Guelph, April 1st, 2011.

A novel generalized quasi-likelihood scoring (GQLS) method is proposed to test the association between a genetic marker and a trait. The GQLS method accommodates the situation with samples of related subjects, and is flexible to test on both binary trait and quantitative trait. It can be also extended to solve the problem when sample is collected from multiple sub-populations. To date, methods in the area of genetic association studies have focused on the test of a single trait at a time. When a large number of markers are tested for association with multiple traits, controlling the overall type I error when testing traits independently becomes an issue. On the other hand, it is of great interest to identify common genetic factors that are associated with one or more than one traits. Based on our GQLS method, we develop a new method named quasi-likelihood scoring approach for multiple traits (QLSM). Simulation studies are used to validate the type I error and assess the power. Our methods will be applied to analyze real data on Canadian Holstein Cattle.