RT Journal Article
SR Electronic
T1 BugBase predicts organism-level microbiome phenotypes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 133462
DO 10.1101/133462
A1 Tonya Ward
A1 Jake Larson
A1 Jeremy Meulemans
A1 Ben Hillmann
A1 Joshua Lynch
A1 Dimitri Sidiropoulos
A1 John R. Spear
A1 Greg Caporaso
A1 Ran Blekhman
A1 Rob Knight
A1 Ryan Fink
A1 Dan Knights
YR 2017
UL http://biorxiv.org/content/early/2017/05/02/133462.abstract
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.