Context-aware dimensionality reduction deconvolutes gut microbial community dynamics

Cameron Martino, Liat Shenhav, Clarisse A. Marotz, George Armstrong, Daniel McDonald, Yoshiki Vázquez-Baeza, James T. Morton, Lingjing Jiang, Maria Gloria Dominguez-Bello, Austin D. Swafford, Eran Halperin, Rob Knight*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

The translational power of human microbiome studies is limited by high interindividual variation. We describe a dimensionality reduction tool, compositional tensor factorization (CTF), that incorporates information from the same host across multiple samples to reveal patterns driving differences in microbial composition across phenotypes. CTF identifies robust patterns in sparse compositional datasets, allowing for the detection of microbial changes associated with specific phenotypes that are reproducible across datasets.

Original languageEnglish
Pages (from-to)165-168
Number of pages4
JournalNature Biotechnology
Volume39
Issue number2
DOIs
StatePublished - Feb 2021
Externally publishedYes

Funding

FundersFunder number
Emerald Foundation 3022
Norwegian Institute of Public Health2019-0350
San Diego Digestive Diseases Research Center NIDDK1P30DK120515
National Science Foundation1R56MD013312, 1705197
National Institutes of Health1DP1AT010885
National Institute of Diabetes and Digestive and Kidney DiseasesP30DK120515
National Institute of Dental and Craniofacial Research1F31DE028478-01
National Institute of Justice2016-DN-BX-4194
Janssen Pharmaceuticals20175015

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