Learning representations of microbe-metabolite interactions.

ABSTRACT: 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.

SUBMITTER: Morton JT 

PROVIDER: S-EPMC6884698 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature