期刊
NATURE METHODS
卷 16, 期 7, 页码 627-+出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/s41592-019-0431-x
关键词
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资金
- European Research Council under the European Union [640384]
- National Science Foundation [1705197, DGE-1644869]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1705197] Funding Source: National Science Foundation
- European Research Council (ERC) [640384] Funding Source: European Research Council (ERC)
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.
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