Arnold School of Public Health

Division of Biostatistics

 Lecture Presented By

 Yen-Yi Ho, PhD
Assistant Professor
Department of Statistics
University of South Carolina 

Abstract: Genetic molecules and gene products participate in complex inter-connected pathways in biological systems. With a wealth of new data generated through high-throughput technologies, researchers are able to study genetic interactions and cellular pathways at the system level. In this talk, I will discuss two important topics in analyzing large-scale genomic data: (1) combining genomic data from various sources, (2) identifying intricate genetic interactions between biological molecules.

In the first part of the talk, I will present novel approaches to combine SNP and gene expression information. These procedures utilize weights constructed by gene expression measurements to adjust p values from a genome-wide association (GWA) analysis. We apply the weight adjustment procedure to a GWA study on serum interferon-regulated chemokine levels in systemic lupus erythematosus patients.

In the second part of the talk, I will introduce a measurable three-way interaction— “liquid association”—observed among genes. It could be applied to study mechanisms that prompt cellular pathways to turn on or off.  I will present statistical inference procedures to examine the magnitude of liquid association in a given data set and demonstrate the implementation of these methods through simulation and experimental data analysis.

“Statistical Methods for Integrating Large-Scale Genomic Data and Identifying Higher-Order Interactions”

Monday, April 23, 2018
1:00 – 2:00
Discovery I
Room 331