Bayesian community-wide culture-independent microbial source tracking

By Dan Knights, J. Kuczynski, Emily S. Charlson, Jesse R. Zaneveld, Michael C. Mozer, Ronald G. Collman, Frederic D. Bushman, Rob Knight, Scott T. Kelley. Nature Methods, 2011

1,590 citations recorded by the source corpus.

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.

Subfields: Clinical Biochemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e2bf2773c08d9b60d5cc51bcc2d34e8c89a23f00

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In Clinical Biochemistry

In Molecular Biology

Citations in the corpus

Maturation of the Infant Microbiome Community Structure and Function Across Multiple Body Sites and in Relation to Mode of Delivery (2017, positive): “Having extensively sampled multiple maternal body sites in parallel with equivalent neonatal and infant samples, we thus sought to perform SourceTracker analysis 41 to predict the most probable maternal origin of the neonatal microbiota.”
Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data (2017, background): “5 does not identify specific contaminants [26].”
A practical guide to amplicon and metagenomic analysis of microbiome data (2020, positive): “FEAST (Shenhav et al., 2019) and SourceTracker (Knights et al., 2011) were designed to unravel the origins of microbial communities.”