| Literature DB >> 31182859 |
Liat Shenhav1, Mike Thompson2, Tyler A Joseph3, Leah Briscoe2, Ori Furman4, David Bogumil4, Itzhak Mizrahi4, Itsik Pe'er3, Eran Halperin5,6,7,8.
Abstract
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.Mesh:
Year: 2019 PMID: 31182859 DOI: 10.1038/s41592-019-0431-x
Source DB: PubMed Journal: Nat Methods ISSN: 1548-7091 Impact factor: 28.547