Association of ordinal traits and genetic variants in pedigree-structured samples by kernel method

Music City Center 

In genome-wide association studies (GWAS), logistic regression is one of the most popular analytics methods for binary traits. However, many GWAS methods have been limited application to binary traits. These methods have improperly often been used to account for ordinal traits, which may cause inappropriate analysis results. In this investigation, we develop a framework for the association analysis of the ordinal traits and genetic variants in pedigree-structured samples by collapsing and kernel methods. We use the local odds ratios GEE technology to describe the complicated correlation structures between family members and ordered categorical traits. We use the retrospective idea to treat the genetic markers as random variables for calculating genetic correlations among markers. The proposed genetic association method can accommodate ordinal traits and allow for the covariate adjustment. We conduct simulation studies to compare the proposed tests with the existing models for analyzing the ordered categorical data. We illustrate application of the proposed tests by analyzing the publicly available dataset.

ordinal traits

pedigree-based study

genetic variants

kernel statistic 

Section on Statistics in Epidemiology