A Zero-Inflated Latent Dirichlet Allocation Model for Microbiome Studies.

ABSTRACT: The human microbiome consists of a community of microbes in varying abundances and is shown to be associated with many diseases. An important first step in many microbiome studies is to identify possible distinct microbial communities in a given data set and to identify the important bacterial taxa that characterize these communities. The data from typical microbiome studies are high dimensional count data with excessive zeros due to both absence of species (structural zeros) and low sequencing depth or dropout. Although methods have been developed for identifying the microbial communities based on mixture models of counts, these methods do not account for excessive zeros observed in the data and do not differentiate structural from sampling zeros. In this paper, we introduce a zero-inflat

SUBMITTER: Deek RA 

PROVIDER: S-EPMC7862749 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature