Title of the talk: Uncovering hidden functional patterns across diverse study populations from whole metagenome sequencing reads with Carnelian
Microbial populations exhibit functional changes in response to different ambient environments. Comparative metagenomic studies needed to understand these changes are yet to take full advantage of the increasingly available whole metagenome sequencing data. In this talk, I will introduce an end-to-end pipeline for metabolic functional profiling of metagenomic reads which is uniquely suited to finding common functional trends across data sets from diverse populations. Our software, Carnelian, combines probabilistic open reading frame finding with a new way of performing alignment-free functional profiling and is better able to detect the enzyme commission terms (ECs), especially from non-annotated species. I will show how this ability enables Carnelian to find concordant functional dysbiosis in geographically separated disease cohorts as well as uncover hidden functional relatedness of healthy microbiomes in populations with different subsistence strategies.