Biostatistics Seminar: Qing Lu, PhD, Michigan State University, Epidemiology & Biostatistics

Qing Lu, PhD

Associate Professor

Department of Epidemiology and Biostatistics

Michigan State University

“A Generalized Similarity U Test for Multivariate Analysis of Sequencing Data”

ABSTRACT:  Sequencing-based studies have become increasingly popular for genetic association studies of complex diseases. These studies pose great challenges to the traditional methods because of the high-dimensionality of data and the low frequency of genetic variants. Moreover, there is a great interest in biology and epidemiology to identify genetic risk factors contributed to multiple disease phenotypes. The multiple phenotypes can often follow different distributions, which bring an additional challenge. In this talk, we introduce a generalized similarity U test, referred to as GSU. GSU is a similarity-based test that can handle high-dimensional genotypes and phenotypes. We studied the properties of GSU, and provided the efficient p-value calculation for association test. Through simulation, we found that GSU had advantages over existing methods in terms of power and robustness to phenotype distributions. Finally, we used GSU to perform a multivariate analysis of sequencing data from the Dallas Heart Study and identified a joint association of 4 genes with 5 metabolic related phenotypes.