Biostatistics Commons^™

Identification Of Gene-Environment Interactions In Cancer Prognosis Studies Using Penalization, Shuangge Ma

Shuangge Ma

High-throughput cancer studies have been extensively conducted, searching for genetic risk factors independently associated with prognosis beyond clinical and environmental risk factors. Many studies have shown that the gene-environment interactions may have important implications. Some of the existing methods, such as the commonly adopted single-marker analysis, may be limited in that they cannot accommodate the joint effects of a large number of genetic markers or use ineffective marker identification techniques. In this study, we analyze cancer prognosis studies, and adopt the AFT (accelerated failure time) model to describe survival. A weighted least squares approach, which has the lowest computational cost, …