title: Bayesian community-wide culture-independent microbial source tracking.
abstract: Contamination is a critical issue in high-throughput metagenomic studies, yet progress toward a comprehensive solution has been limited. We present SourceTracker, a Bayesian approach to estimate the proportion of contaminants in a given community that come from possible source environments. We applied SourceTracker to microbial surveys from neonatal intensive care units (NICUs), offices and molecular biology laboratories, and provide a database of known contaminants for future testing.
authors.affiliation: Department of Computer Science, University of Colorado, Boulder, Colorado, USA.
authors.forename: Dan
authors.initials: D
authors.lastname: Knights
authors.forename: Justin
authors.initials: J
authors.lastname: Kuczynski
authors.forename: Emily S
authors.initials: ES
authors.lastname: Charlson
authors.forename: Jesse
authors.initials: J
authors.lastname: Zaneveld
authors.forename: Michael C
authors.initials: MC
authors.lastname: Mozer
authors.forename: Ronald G
authors.initials: RG
authors.lastname: Collman
authors.forename: Frederic D
authors.initials: FD
authors.lastname: Bushman
authors.forename: Rob
authors.initials: R
authors.lastname: Knight
authors.forename: Scott T
authors.initials: ST
authors.lastname: Kelley
mesh_terms: D001499:Bayes Theorem; D017714:Community-Acquired Infections / Q000382:microbiology; D019295:Computational Biology; D003428:Cross Infection / Q000209:etiology; D004197:Disease Reservoirs / Q000382:microbiology*; D004784:Environmental Monitoring / Q000379:methods*; D050456:Fomites / Q000382:microbiology; D006801:Humans; D007363:Intensive Care Units, Neonatal; D007374:Interior Design and Furnishings; D007753:Laboratories; D013689:Telephone