Bayesian shrinkage estimation of high dimensional causal mediation effects in omics studies.

ABSTRACT: Causal mediation analysis aims to examine the role of a mediator or a group of mediators that lie in the pathway between an exposure and an outcome. Recent biomedical studies often involve a large number of potential mediators based on high-throughput technologies. Most of the current analytic methods focus on settings with one or a moderate number of potential mediators. With the expanding growth of -omics data, joint analysis of molecular-level genomics data with epidemiological data through mediation analysis is becoming more common. However, such joint analysis requires methods that can simultaneously accommodate high-dimensional mediators and that are currently lacking. To address this problem, we develop a Bayesian inference method using continuous shrinkage priors to extend previous

SUBMITTER: Song Y 

PROVIDER: S-EPMC7228845 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature