Massive metagenomic data analysis using abundance-based machine learning.

Journal: Biology direct
Published Date:

Abstract

BACKGROUND: Metagenomics is the application of modern genomic techniques to investigate the members of a microbial community directly in their natural environments and is widely used in many studies to survey the communities of microbial organisms that live in diverse ecosystems. In order to understand the metagenomic profile of one of the densest interaction spaces for millions of people, the public transit system, the MetaSUB international Consortium has collected and sequenced metagenomes from subways of different cities across the world. In collaboration with CAMDA, MetaSUB has made the metagenomic samples from these cities available for an open challenge of data analysis including, but not limited in scope to, the identification of unknown samples.

Authors

  • Zachary N Harris
    Department of Biology, Saint Louis University, Saint Louis, MO, 63103, USA.
  • Eliza Dhungel
    Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, MO, 63103, USA.
  • Matthew Mosior
    Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, MO, 63103, USA.
  • Tae-Hyuk Ahn
    Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, MO, 63103, USA. ted.ahn@slu.edu.