Evidence map›Paper›PMID 39563467›Full record

ArticleBioinformatics (Oxford, England)2024

Micro-DeMix: a mixture beta-multinomial model for investigating the heterogeneity of the stool microbiome compositions.

Ruoqian Liu, Yue Wang, Dan Cheng

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Ruoqian LiuSchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85251, United States.
Yue WangDepartment of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO 80045, United States.ORCID 0000-0002-4847-8826
Dan ChengSchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85251, United States.

Funding

National Institute of Health DMS-2220523Simons Foundation Collaboration 854127
6 · The paper itself

Abstract

motivationExtensive research has uncovered the critical role of the human gut microbiome in various aspects of health, including metabolism, nutrition, physiology, and immune function. Fecal microbiota is often used as a proxy for understanding the gut microbiome, but it represents an aggregate view, overlooking spatial variations across different gastrointestinal (GI) locations. Emerging studies with spatial microbiome data collected from specific GI regions offer a unique opportunity to better understand the spatial composition of the stool microbiome.

resultsWe introduce Micro-DeMix, a mixture beta-multinomial model that deconvolutes the fecal microbiome at the compositional level by integrating stool samples with spatial microbiome data. Micro-DeMix facilitates the comparison of microbial compositions across different GI regions within the stool microbiome through a hypothesis-testing framework. We demonstrate the effectiveness and efficiency of Micro-DeMix using multiple simulated datasets and the inflammatory bowel disease data from the NIH Integrative Human Microbiome Project. AVAILABILITY AND IMPLEMENTATION: The R package is available at https://github.com/liuruoqian/MicroDemix.

Indexed as

FecesGastrointestinal MicrobiomeSoftwareHumansInflammatory Bowel Diseases

Identifiers

PMID39563467
PMCPMC11645251

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.