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Morton, James T; Aksenov, Alexander A; Nothias, Louis Felix; Foulds, James R; Quinn, Robert A; Badri, Michelle H; Swenson, Tami L; Van Goethem, Marc W; Northen, Trent R; Vazquez-Baeza, Yoshiki; Wang, Mingxun; Bokulich, Nicholas A; Watters, Aaron; Song, Se Jin; Bonneau, Richard; Dorrestein, Pieter C; Knight, Rob
Nature methods, 12/2019, Volume: 16, Issue: 12Journal Article
Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We show with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.
