Statistical and Computational Methods to Dissect Ancestry-Biased Germline Effects in Lung Cancer

Abstract

Lung cancer is a complex disease influenced by a variety of genetic and environmental factors. The germline mutations associated with the disease vary greatly between the East Asian and the European populations. We explore these differences by analyzing genome-wide association study summary statistics from European and Japanese biobanks. Using stratified linkage disequilibrium regression in conjunction wit gene expression-based and epigenetic annotations, we derive cell-types and biological processes associated with lung cancer and smoking in both populations.