Article

Latent Interacting Variable-Effects Modeling of Gut Microbiome Multi-Omics in Inflammatory Bowel Disease

2022-07-09

Abstract excerpt

<h4>ABSTRACT</h4> Latent Interacting Variable Effects (LIVE) modeling is a framework to integrate different types of microbiome multi-omics data by combining latent variables from single-omic models into a structured meta-model to determine discriminative, interacting multi-omics features driving disease status. We implemented and tested LIVE modeling in publicly available metagenomics and metabolomics datasets f...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: f70af425-8a1e-5725-bd77-9e595f5bcee8
DOI: 10.1101/2022.07.08.499280

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Latent Interacting Variable-Effects Modeling of Gut Microbiome Multi-Omics in Inflammatory Bowel DiseaseDOI 10.1101/2022.07.08.499280Read

Poly-omic risk scores predict inflammatory bowel disease diagnosisSemantic proximity Read

Poly-omic risk scores predict inflammatory bowel disease diagnosis.Semantic proximity Read

SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domainsSemantic proximity Read

MaAsLin 3: Refining and extending generalized multivariable linear models for meta-omic association discoverySemantic proximity Read

A latent unknown clustering integrating multi-omics data (LUCID) with phenotypic traits.Semantic proximity Read

Analyzing associations and higher-order effects in multi-omics data with double machine learningSemantic proximity Read

Multivariable Association Discovery in Population-scale Meta-omics StudiesSemantic proximity Read

Phenotype-driven parallel embedding for microbiome multi-omic data integrationSemantic proximity Read

Identifying High-Dimensional Genomic Factors Modulating Biological Networks Across Multi-Omics DataSemantic proximity Read

Extended Graphical Lasso for Multiple Interaction Networks for High Dimensional Omics DataSemantic proximity Read

Unfolding and De-confounding: Biologically meaningful causal inference from longitudinal multi-omic networks using <tt>METALICA</tt>Semantic proximity Read

Multi-omic modelling of inflammatory bowel disease with regularized canonical correlation analysisSemantic proximity Read