B1268
Title: Understanding microbiome meta-community structure through a hierarchical Dirichlet process
Authors: Jack OBrien - Bowdoin College (United States) [presenting]
Abstract: The explosion of metagenomic sequencing data has led to intense interest in the modeling of microbial community structure that plays an important role in medicine, agriculture, and ecology. We expand on standard mixture model approaches to these data to include a hierarchical Dirichlet process with an underlying latent allocation that allows for more flexible structure within and across samples. We demonstrate an explicit connection between the components of the model (niches) and the unified neutral theory of biodiversity, a key piece of ecological theory. Our formulation allows for a Gibbs sampling strategy and we provide two examples from the recent literature. We also present a thermodynamic integration approach to determining the optimal number of niches in a data set.
