A Zero-inflated Beta-binomial Model for Microbiome Data Analysis.

ABSTRACT: The microbiome is increasingly recognized as an important aspect of the health of host species, involved in many biological pathways and processes and potentially useful as health biomarkers. Taking advantage of high-throughput sequencing technologies, modern bacterial microbiome studies are metagenomic, interrogating thousands of taxa simultaneously. Several data analysis frameworks have been proposed for microbiome sequence read count data and determining the most significant features. However, there is still room for improvement. We introduce a zero-inflated beta-binomial (ZIBB) to model the distribution of microbiome count data and to determine association with a continuous or categorical phenotype of interest. The approach can exploit mean-variance relationships to improve power and a

SUBMITTER: Hu T 

PROVIDER: S-EPMC6124506 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature