A PHYLOGENETIC SCAN TEST ON A DIRICHLET-TREE MULTINOMIAL MODEL FOR MICROBIOME DATA

• 成果类型: Article
• 署名作者: Tang, Yunfan; Ma, Li; Nicolae, Dan L.
• 署名单位: University of Chicago; Duke University
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/17-AOAS1086
• 发表日期: 2018
• 页码: 1-26
• 关键词: INEQUALITIES; IDENTITIES; regression; FRAMEWORK

摘要

In this paper, we introduce the phylogenetic scan test (PhyloScan) for investigating cross-group differences in microbiome compositions using the Dirichlet-tree multinomial (DTM) model. DTM models the microbiome data through a cascade of independent local DMs on the internal nodes of the phylogenetic tree. Each of the local DMs captures the count distributions of a certain number of operational taxonomic units at a given resolution. Since distributional differences tend to occur in clusters along evolutionary lineages, we design a scan statistic over the phylogenetic tree to allow nodes to borrow signal strength from their parents and children. We also derive a formula to bound the tail probability of the scan statistic, and verify its accuracy through simulations. The PhyloScan procedure is applied to the American Gut dataset to identify taxa associated with diet habits. Empirical studies performed on this dataset show that PhyloScan achieves higher testing power in most cases.