FEAST: fast expectation-maximization for microbial source tracking.
Journal
Nature methods
ISSN: 1548-7105
Titre abrégé: Nat Methods
Pays: United States
ID NLM: 101215604
Informations de publication
Date de publication:
07 2019
07 2019
Historique:
received:
06
08
2018
accepted:
23
04
2019
pubmed:
12
6
2019
medline:
13
7
2019
entrez:
12
6
2019
Statut:
ppublish
Résumé
A major challenge of analyzing the compositional structure of microbiome data is identifying its potential origins. Here, we introduce fast expectation-maximization microbial source tracking (FEAST), a ready-to-use scalable framework that can simultaneously estimate the contribution of thousands of potential source environments in a timely manner, thereby helping unravel the origins of complex microbial communities ( https://github.com/cozygene/FEAST ). The information gained from FEAST may provide insight into quantifying contamination, tracking the formation of developing microbial communities, as well as distinguishing and characterizing bacteria-related health conditions.
Identifiants
pubmed: 31182859
doi: 10.1038/s41592-019-0431-x
pii: 10.1038/s41592-019-0431-x
pmc: PMC8535041
mid: NIHMS1637086
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
627-632Subventions
Organisme : NLM NIH HHS
ID : R01 LM013327
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH095458
Pays : United States
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