A Multiple-Testing Procedure for High-Dimensional Mediation Hypotheses

• 成果类型: Article
• 署名作者: Dai, James Y.; Stanford, Janet L.; LeBlanc, Michael
• 署名单位: Fred Hutchinson Cancer Center; University of Washington; University of Washington Seattle
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2020.1765785
• 发表日期: 2022
• 页码: 198-213
• 关键词: true null hypotheses; prostate-cancer; dna methylation; complex traits; PROPORTION; inference; irx4

摘要

Mediation analysis is of rising interest in epidemiologic studies and clinical trials. Among existing methods, the joint significance test yields an overly conservative Type I error rate and low power, particularly for high-dimensional mediation hypotheses. In this article, we develop a multiple-testing procedure that accurately controls the family-wise error rate (FWER) and the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. The core of our procedure is based on estimating the proportions of component null hypotheses and the underlying mixture null distribution ofp-values. Theoretical developments and simulation experiments prove that the proposed procedure effectively controls FWER and FDR. Two mediation analyses on DNA methylation and cancer research are presented: assessing the mediation role of DNA methylation in genetic regulation of gene expression in primary prostate cancer samples; exploring the possibility of DNA methylation mediating the effect of exercise on prostate cancer progression. Results of data examples include well-behaved quantile-quantile plots and improved power to detect novel mediation relationships. An R package HDMT implementing the proposed procedure is freely accessible in CRAN.for this article are available online.