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BugBase Predicts Organism Level Microbiome Phenotypes

Tonya Ward, Jake Larson, Jeremy Meulemans, Ben Hillmann, Joshua Lynch, Dimitri Sidiropoulos, John Spear, Greg Caporaso, Ran Blekhman, Rob Knight, Ryan Fink, Dan Knights
doi: https://doi.org/10.1101/133462
Tonya Ward
University of Minnesota;
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Jake Larson
University of Minnesota;
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Jeremy Meulemans
University of Minnesota;
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Ben Hillmann
University of Minnesota;
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Joshua Lynch
University of Minnesota;
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Dimitri Sidiropoulos
University of Minnesota;
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John Spear
Colorado School of Mines;
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Greg Caporaso
Northern Arizona University;
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Ran Blekhman
University of Minnesota;
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Rob Knight
University of California San Diego;
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Ryan Fink
St. Cloud State University
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Dan Knights
University of Minnesota;
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  • For correspondence: dknights@umn.edu
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Abstract

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 the organism-level pathway coverage of BugBase predictions to be statistically higher powered than current bag-of-genes approaches for discerning functional changes in both host-associated and environmental microbiomes.

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The copyright holder for this preprint is the author/funder. It is made available under a CC-BY 4.0 International license.
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  • Posted May 2, 2017.

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BugBase Predicts Organism Level Microbiome Phenotypes
Tonya Ward, Jake Larson, Jeremy Meulemans, Ben Hillmann, Joshua Lynch, Dimitri Sidiropoulos, John Spear, Greg Caporaso, Ran Blekhman, Rob Knight, Ryan Fink, Dan Knights
bioRxiv 133462; doi: https://doi.org/10.1101/133462
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BugBase Predicts Organism Level Microbiome Phenotypes
Tonya Ward, Jake Larson, Jeremy Meulemans, Ben Hillmann, Joshua Lynch, Dimitri Sidiropoulos, John Spear, Greg Caporaso, Ran Blekhman, Rob Knight, Ryan Fink, Dan Knights
bioRxiv 133462; doi: https://doi.org/10.1101/133462

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