FRG Biweekly Meeting: Siqi Xiang, UNC

Title: Binary Expansion Testing and Dependence Analysis Of Genomic Data

Abstract: In The Cancer Genome Atlas (TCGA) data set, there are many interesting nonlinear dependencies between pairs of genes that reveal important relationships and subtypes of cancer. We study the nonlinear relationships among the expression of genes using a powerful tool called Binary Expansion Testing (BET). We find many nonlinear patterns, some of which are driven by known cancer subtypes, some of which are novel. However, the Bonferroni adjusted p-values in this exploratory data analysis of TCGA could be overly conservative when used to determine the significant gene pairs. Thus, to improve the power of BET, we study the distribution of the maximal BET z-statistics when doing pairwise testing in a large-scale data set. The extreme value theorem is applied. We also propose a selection method of significant dependence pairs based on BET z-scores using this distribution.