A Method For Rare Variant Association Analysis Based On Ordinal Variables

In recent years,there has been an increasing interest in detecting disease-related rare variants in sequencing studies.Numerous studies have shown that common variants can only explain a small proportion of the phenotypic variance for complex diseases.More and more evidences suggest that some of the missing heritability can be explained by rare variants.Considering the importance of rare variants,researchers have proposed a considerable amount of methods to identify the rare variants associated with complex diseases.Although extensive researches have been carried out on testing the association between rare variants and dichotomous,continuous or ordinal traits.So far,however,there has been little discussion about the case that both genotypes and phenotypes are ordinal variables.This paper introduces a method of γ-statistics based on contingency tables,called OV-RV,for examining disease related rare variants when both genotypes and phenotypes are ordinal.To date,little is known about the asymptotic distribution of the γ-statistic when conducting association analysis for rare variants.One advantage of OV-RV is that it provides a robust estimation of the distribution of the γ-statistic by employing the permutation approach proposed by Fisher.We also perform extensive simulations to investigate the numerical performance of OV-RV under various model settings.The simulation results reveal that OV-RV is valid and efficient,namely,it controls the type I error at the pre-specified significance level approximately and achieves higher power at the same significance level.