Hypotheses on a tree: new error rates and testing strategies

• 成果类型: Article
• 署名作者: Bogomolov, Marina; Peterson, Christine B.; Benjamini, Yoav; Sabatti, Chiara
• 署名单位: Technion Israel Institute of Technology; University of Texas System; UTMD Anderson Cancer Center; Tel Aviv University; Stanford University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asaa086
• 发表日期: 2021
• 页码: 575590
• 关键词: false discovery rate; inference

摘要

We introduce a multiple testing procedure that controls global error rates at multiple levels of resolution. Conceptually, we frame this problem as the selection of hypotheses that are organized hierarchically in a tree structure. We describe a fast algorithm and prove that it controls relevant error rates given certain assumptions on the dependence between the p-values. Through simulations, we demonstrate that the proposed procedure provides the desired guarantees under a range of dependency structures and that it has the potential to gain power over alternative methods. Finally, we apply the method to studies on the genetic regulation of gene expression across multiple tissues and on the relation between the gut microbiome and colorectal cancer.