The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
FEAST: fast expectation-maximization for microbial source tracking
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
An obesity-associated gut microbiome with increased capacity for energy harvest
Turnbaugh, P. J., Ley, R. E., Mahowald, M. A., Magrini, V., Mardis, E. R., & Gordon, J. I. (2006) · Nature · doi:10.1038/nature05414 · Cited by 12,444
Fast model-based estimation of ancestry in unrelated individuals
Alexander, D. H., Novembre, J., & Lange, K. (2009) · Genome Research · doi:10.1101/gr.094052.109 · Cited by 9,898
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Lozupone, C., & Knight, R. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8228-8235.2005 · Cited by 8,227
A metagenome-wide association study of gut microbiota in type 2 diabetes
Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762
Obesity alters gut microbial ecology
Ley, R. E., Bäckhed, F., Turnbaugh, P., Lozupone, C. A., Knight, R. D., & Gordon, J. I. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504978102 · Cited by 6,176
Richness of human gut microbiome correlates with metabolic markers
Le Chatelier, E., Nielsen, T., Qin, J., Prifti, E., Hildebrand, F., Falony, G., Almeida, M., Arumugam, M., Batto, J.-M., Kennedy, S., et al. (2013) · Nature · doi:10.1038/nature12506 · Cited by 4,662
Lauber, C. L., Hamady, M., Knight, R., & Fierer, N. (2009) · Applied and Environmental Microbiology · doi:10.1128/aem.00335-09 · Cited by 4,063
Gut Microbiota from Twins Discordant for Obesity Modulate Metabolism in Mice
Ridaura, V. K., Faith, J. J., Rey, F. E., Cheng, J., Duncan, A. E., Kau, A. L., Griffin, N. W., Lombard, V., Henrissat, B., Bain, J. R., et al. (2013) · Science · doi:10.1126/science.1241214 · Cited by 3,788
The impact of the gut microbiota on human health: an integrative view
Clemente, J. C., Ursell, L. K., Parfrey, L. W., & Knight, R. (2012) · Cell · doi:10.1016/j.cell.2012.01.035 · Cited by 3,710
Bacterial Community Variation in Human Body Habitats Across Space and Time
Costello, E. K., Lauber, C. L., Hamady, M., Fierer, N., Gordon, J. I., & Knight, R. (2009) · Science · doi:10.1126/science.1177486 · Cited by 3,231
Cited by
Estaki, M., Jiang, L., Bokulich, N. A., McDonald, D., González, A., Kosciolek, T., Martino, C., Zhu, Q., Birmingham, A., Vázquez‐Baeza, Y., et al. (2020) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.100 · Cited by 565
Zheng, D., Yin, G., Liu, M., Chen, C., Jiang, Y., Hou, L., & Zheng, Y. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2021.146009 · Cited by 348
Zhang, L., Zhang, M., Huang, S., Li, L., Gao, Q., Wang, Y., Zhang, S., Huang, S., Yuan, L., Wen, Y., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31113-w · Cited by 258
Faecal microbiota transplantation for Clostridioides difficile: mechanisms and pharmacology
Khoruts, A., Staley, C., & Sadowsky, M. J. (2021) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-020-0350-4 · Cited by 155
The best practice for microbiome analysis using R
Wen, T., Niu, G., Chen, T., Shen, Q., Yuan, J., & Liu, Y.-X. (2023) · Protein & Cell · doi:10.1093/procel/pwad024 · Cited by 139
Metadata
- Authors
- Shenhav, L., Thompson, M., Joseph, T. A., Briscoe, L., Furman, O., Bogumil, D., Mizrahi, I., Pe’er, I., & Halperin, E.
- Venue
- Nature Methods
- Published
- 2019-06-10
- Volume
- 16
- Issue
- 7
- Pages
- 627-632
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2951702646
- Cited by
- 644
- References
- 14
- FWCI
- 34.32
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: FEAST: fast expectation-maximization for microbial source tracking. https://app.cochat.ai/papers/10.1038/s41592-019-0431-x
- The paper
- Shenhav, L., Thompson, M., Joseph, T. A., Briscoe, L., Furman, O., Bogumil, D., Mizrahi, I., Pe’er, I., & Halperin, E. (2019). FEAST: fast expectation-maximization for microbial source tracking. Nature Methods. https://doi.org/10.1038/s41592-019-0431-x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
