TY - JOUR T1 - BugBase predicts organism-level microbiome phenotypes JF - bioRxiv DO - 10.1101/133462 SP - 133462 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 Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/05/02/133462.abstract N2 - 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. ER -