PT  - JOURNAL ARTICLE
AU  - Tonya Ward
AU  - Jake Larson
AU  - Jeremy Meulemans
AU  - Ben Hillmann
AU  - Joshua Lynch
AU  - Dimitri Sidiropoulos
AU  - John R. Spear
AU  - Greg Caporaso
AU  - Ran Blekhman
AU  - Rob Knight
AU  - Ryan Fink
AU  - Dan Knights
TI  - BugBase predicts organism-level microbiome phenotypes
AID  - 10.1101/133462
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 133462
4099  - http://biorxiv.org/content/early/2017/05/02/133462.short
4100  - http://biorxiv.org/content/early/2017/05/02/133462.full
AB  - Shotgun metagenomics and marker gene amplicon sequencing can be used to directly measure or predict the functional repertoire of the microbiota en masse, but current methods do not readily estimate the functional capability of individual microorganisms. Here we present BugBase, an algorithm that predicts organism-level coverage of functional pathways as well as biologically interpretable phenotypes such as oxygen tolerance, Gram staining and pathogenic potential, within complex microbiomes using either whole-genome shotgun or marker gene sequencing data. We find BugBase’s organism-level pathway coverage predictions to be statistically higher powered than current ‘bag-of-genes’ approaches for discerning functional changes in both host-associated and environmental microbiomes.