A Bayesian Multi-Task Approach for Detecting Global Microbiome Associations



Hatami, Farhad, Beamish, Emma ORCID: 0000-0002-7000-7641, Rigby, Rachael and Dondelinger, Frank ORCID: 0000-0003-1816-6300
(2020) A Bayesian Multi-Task Approach for Detecting Global Microbiome Associations. A Bayesian Multi-Task Approach for Detecting Global Microbiome Associations. 2020.01.08.897538-.

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Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Motivation</jats:title><jats:p>The human gut microbiome has been shown to be associated with a variety of human diseases, including cancer, metabolic conditions and inflammatory bowel disease. Current statistical techniques for microbiome association studies are limited by relying on measures of ecological distance, or only allowing for the detection of associations with individual bacterial species, rather than the whole microbiome.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In this work, we develop a novel Bayesian multi-task approach for detecting global microbiome associations. Our method is not dependent on a choice of distance measure, and is able to incorporate phylogenetic information about microbial species. We apply our method to simulated data and show that it allows for consistent estimation of global microbiome effects. Additionally, we investigate the performance of the model on two real-world microbiome studies: a study of microbiome-metabolome associations in inflammatory bowel disease (Beamish, 2017), and a study of associations between diet and the gut microbiome in mice (Turnbaugh <jats:italic>et al</jats:italic>., 2009). We show that we can use the method to reliably detect associations in real-world datasets with varying numbers of samples and covariates.</jats:p></jats:sec><jats:sec><jats:title>Availability</jats:title><jats:p>Our method is implemented using the R interface to the Stan Hamiltonian Monte Carlo sampler. Software for running our methods is available at <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/FrankD/MicrobiomeGlobalAssociations">https://github.com/FrankD/MicrobiomeGlobalAssociations</jats:ext-link>.</jats:p></jats:sec><jats:sec><jats:title>Contact</jats:title><jats:p><jats:email>f.dondelinger@lancaster.ac.uk</jats:email></jats:p></jats:sec>

Item Type: Article
Uncontrolled Keywords: Nutrition, Digestive Diseases, Oral and gastrointestinal
Depositing User: Symplectic Admin
Date Deposited: 17 Nov 2020 08:48
Last Modified: 15 Mar 2024 14:58
DOI: 10.1101/2020.01.08.897538
Open Access URL: https://www.biorxiv.org/content/10.1101/2020.01.08...
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3107149