Robust suptest for the genetic association study under genetic model uncertainty

In case–control studies the Cochran–Armitage trend test is powerful for detection of an association between a risk genetic marker and a disease of interest. To apply this test, a score should be assigned to the genotypes based on the genetic model. When the underlying genetic model is unknown, the trend test statistic is quite sensitive to the choice of the score. In this paper, we study the asymptotic property of the robust suptest statistic defined as a supremum of Cochran–Armitage trend test across all scores between 0 and 1. Through numerical studies we show that small to moderate sample size performances of the suptest appear reasonable in terms of type I error control and we compared empirical powers of the suptest to those of three individual Cochran–Armitage trend tests and the maximum of the three Cochran–Armitage trend tests. The use of the suptest is applied to rheumatoid arthritis data from a genome-wide association study.