Context-Aware Dimensionality Reduction Deconvolutes Gut Microbial Community Dynamics

Content Advisory

Please be aware that this content contains descriptions of violence that may be distressing to some viewers.
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
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)

Grant Number(s)
2016-DN-BX-4194
Agencies
NIJ-Sponsored
Publication Type
Research (Applied/Empirical)
Award
Improving Estimates of the Postmortem Interval with Metagenomics and Metabolomics
Date Published: January 1, 2020

Downloads