  Genetic association study is an essential step to discover genetic factors
that are associated with a complex trait of interest. In this paper we present
a novel generalized quasi-likelihood score (GQLS) test that is suitable for a
study with either a quantitative trait or a binary trait. We use a logistic
regression model to link the phenotypic value of the trait to the distribution
of allelic frequencies. In our model, the allele frequencies are treated as a
response and the trait is treated as a covariate that allows us to leave the
distribution of the trait values unspecified. Simulation studies indicate that
our method is generally more powerful in comparison with the family-based
association test (FBAT) and controls the type I error at the desired levels. We
apply our method to analyze data on Holstein cattle for an estimated breeding
value phenotype, and to analyze data from the Collaborative Study of the
Genetics of Alcoholism for alcohol dependence. The results show a good portion
of significant SNPs and regions consistent with previous reports in the
literature, and also reveal new significant SNPs and regions that are
associated with the complex trait of interest.
