Mixture Models of Metagenomic Read Counts for Ecological Analysis

• Activity Number: 314
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): John O'Brien*+
• Companies: Bowdoin College
• Keywords: Metagenomics ; ecology ; mixture model ; sequence analysis

Abstract

Metagenomics - techniques for ascertaining sequence data from uncultured environmental samples - has become a powerful means to explore ecological dynamics in the environment. The most common technique involves sampling a single gene, such as 16S rRNA, largely conserved across the tree of life to infer the distribution of species present within a set of samples. I show how a Bayesian mixture model applied to the read count data from a set of metagenomic samples can be used to infer a small number of ecological states that underlie the microbial dynamics of the collection. I provide an example from the English Channel showing that these states capture temporal fluctuations in the dominant photosynthetically productive microbial populations.