Statistical Genetics

Subtypes specific GWAS and risk prediction modeling on breast cancer subtypes

Composite kernel machine regression based on likelihood ratio test for joint testing of genetic and gene–environment interaction effect

In this article, we develop a kernel machine regression framework to model the overall genetic effect of a SNP-set, considering the possible Gene-Environment (GE) interaction. We propose a likelihood ratio test (LRT) and a restricted likelihood ratio …

A mixed-model approach for powerful testing of genetic associations with cancer risk incorporating tumor characteristics

Standard approach and methods accounting for subtype heterogeneity identified 33 novel breast cancer loci

Methods for analyzing genome-wide association studies

Genome-wide association study (GWAS) identifies 19 novel breast cancer loci from analyses accounting for subtype heterogeneity

Power Analysis for Genetic Association Test (PAGEANT) provides insights to challenges for rare variant association studies

We propose a new method for power calculation of aggregate level association rare variants tests. Compared to traditional power cacualtion, the new methods require a small number of key paprameters. We develop an analytic framework to obtain bounds …