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Micro-DeMix: A mixture beta-multinomial model for investigating the fecal microbiome compositions
Ruoqian Liu1, Yue Wang2, Dan Cheng1
1School of Mathematical and Statistical Sciences, Arizona State University.
Abstract:
Extensive research has uncovered the involvement of the human gut microbiome in various facets of human health, including metabolism, nutrition, physiology, and immune function. Researchers often study fecal microbiota as a proxy for understanding the gut microbiome. However, it has been demonstrated that this approach may not suffice to yield a comprehensive understanding of the entire gut microbial community. Emerging research is revealing the heterogeneity of the gut microbiome across different gastrointestinal (GI) locations in both composition and functions. While spatial metagenomics approach has been developed to address these variations in mice, limitations arise when applying it to human-subject research, primarily due to its invasive nature. With these restrictions, we introduce Micro-DeMix, a mixture beta-multinomial model that decomposes the fecal microbiome at compositional level to understand the heterogeneity of the gut microbiome across various GI locations and extract meaningful insights about the biodiversity of the gut microbiome. Moreover, Micro-DeMix facilitates the discovery of differentially abundant microbes between GI regions through a hypothesis testing framework. We utilize the Inflammatory Bowel Disease (IBD) data from the NIH Integrative Human Microbiome Project to demonstrate the effectiveness and efficiency of the proposed Micro-DeMix.
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