Article

A novel Bayesian fine-mapping model using a continuous global-local shrinkage prior with applications in prostate cancer analysis

2023-08-08

Abstract excerpt

The aim of fine-mapping is to identify genetic variants causally contributing to complex traits or diseases. Existing fine-mapping methods employ discrete Bayesian mixture priors and depend on a pre-specified maximum number of causal variants which may lead to sub-optimal solutions. In this work, we propose a novel fine-mapping method called h2-D2, utilizing a continuous global-local shrinkage prior. We also prese...

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Literature Corpus work: d349927d-d678-538a-b396-d8025c956450
DOI: 10.1101/2023.08.04.23293456

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