FEAST: fast expectation-maximization for microbial source tracking
By L. Shenhav, Mike Thompson, Tyler A. Joseph, Leah Briscoe, Ori Furman, David Bogumil, Itzhak Mizrahi, Itsik Pe'er, Eran Halperin. Nature Methods, 2019
511 citations recorded by the source corpus.
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. FEAST provides a computationally efficient tool to estimate the contribution of microbial sources to a target microbial community, as demonstrated for a variety of complex environmental samples.
Subfields: Biomedical Engineering, Ecology, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/13f5a5974500ce3d8f2d5d8da71efd526e501a0a
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In Ecology
- Nicholas A. Bokulich
- J. Gregory Caporaso
- Rob Knight
- Antonio Gonzalez
- Daniel McDonald
- Yoshiki Vazquez-Baeza
- Amanda Birmingham
- Cameron Martino
In Molecular Biology
- Rob Knight
- J. Gregory Caporaso
- Antonio Gonzalez
- Nicholas A. Bokulich
- Yoshiki Vazquez-Baeza
- Daniel McDonald
- Amanda Birmingham
- Cameron Martino
Citations in the corpus
- QIIME 2 Enables Comprehensive End‐to‐End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data (2020, methodology): “Numerous normalization methods have been proposed to restore absolute abundances such as rarefaction (Weiss et al., 2017), as well as median (Love, Huber, & Anders, 2014), quantile (Paulson, Stine, Bravo, & Pop, 2013), and constant sum normalization.”
- A practical guide to amplicon and metagenomic analysis of microbiome data (2020, unknown): “FEAST (Shenhav et al., 2019) and SourceTracker (Knights et al., 2011) were designed to unravel the origins of microbial communities.”