Context-Aware Dimensionality Reduction Deconvolutes Gut Microbial Community Dynamics

• NCJ Number: 255160
• Journal: Nature Biotechnology Dated: 2020
• Author(s): Cameron Martino; Liat Shenhav; Clarisse A. Marotz; George Armstrong; Daniel McDonald; Yoshiki Vázquez-Baeza; James T. Morton; Lingjing Jiang; Maria G. Dominguez-Bello; Austin D. Swafford; Eran Halperin; Rob Knight
• Date Published: 2020
• Length: 12 pages
• Grant Number(s): 2016-DN-BX-4194
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description
• Award: Improving Estimates of the Postmortem Interval with Metagenomics and Metabolomics

Annotation

Since the translational power of human microbiome studies is limited by high interindividual variation, this article describes 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.

Abstract

CTF identifies robust patterns in sparse compositional datasets, allowing for the detection of microbial changes associated with specific phenotypes that are reproducible across datasets. (publisher abstract modified)