A Bayesian fine-mapping model using a continuous global-local shrinkage prior with applications in prostate cancer analysis
We develop a fine-mapping method, called h2-D2, utilizing a continuous global-local shrinkage prior, and propose an approach to define credible set of causal variants in this framework. Our proposed method outperforms the state-of-art fine-mapping methods based on discrete mixture priors.
Source: The American Journal of Human Genetics - Category: Genetics & Stem Cells Authors: Xiang Li, Pak Chung Sham, Yan Dora Zhang Tags: Article Source Type: research