DOI: 10.1101/497826Dec 17, 2018Paper

High Dimensional Mediation Analysis with Applications to Causal Gene Identification

BioRxiv : the Preprint Server for Biology
Qi Zhang

Abstract

Mediation analysis has been a popular framework for elucidating the mediating mechanism of the exposure effect on the outcome. Previous literature in causal mediation primarily focused on the classical settings with univariate exposure and univariate mediator, with recent growing interests in high dimensional mediator. In this paper, we study the mediation model with high dimensional exposure and high dimensional mediator, and introduce two procedures for mediator selection, MedFix and MedMix. MedFix is our new application of adaptive lasso with one additional tuning parameter. MedMix is a novel mediation model based on high dimensional linear mixed model, for which we also develop a new variable selection algorithm. Our study is motivated by the causal gene identification problem, where causal genes are defined as the genes that mediate the genetic effect. For this problem, the genetic variants are the high dimensional exposure, the gene expressions the high dimensional mediator, and the phenotype of interest the outcome. We evaluate the proposed methods in extensive real data driven simulations, and apply them to causal gene identification from a mouse f2 dataset for diabetes study. We show that the mixed model based approach...Continue Reading

Related Concepts

Diabetes
Gene Expression
Genes
Literature
Laboratory mice
Size
Gene Mutant
Simulation
Analysis
2-Dimensional

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