Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 73,413 bioRxiv papers from 319,549 authors.

BugBase Predicts Organism Level Microbiome Phenotypes

By Tonya Ward, Jake Larson, Jeremy Meulemans, Ben Hillmann, Joshua Lynch, Dimitri Sidiropoulos, John R. Spear, Greg Caporaso, Ran Blekhman, R. Knight, Ryan Fink, Dan Knights

Posted 02 May 2017
bioRxiv DOI: 10.1101/133462

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.

Download data

  • Downloaded 2,744 times
  • Download rankings, all-time:
    • Site-wide: 1,536 out of 73,424
    • In bioinformatics: 301 out of 7,156
  • Year to date:
    • Site-wide: 3,361 out of 73,424
  • Since beginning of last month:
    • Site-wide: 3,361 out of 73,424

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)