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Activity Number: 48 - Longitudinal Modeling and Experimental Design for InvestigatingĀ Host Associated Microbiota
Type: Invited
Date/Time: Sunday, July 29, 2018 : 4:00 PM to 5:50 PM
Sponsor: IMS
Abstract #326782 Presentation
Title: A Microbial Interdependence Association Test in Longitudinal Study
Author(s): Huilin Li* and Yilong Zhang and Sung Won Han and Laura Cox
Companies: New York University and Merck Research Laboratories and Korea University and Brigham and Women's Hospital and Harvard Medical School
Keywords: longitudinal data; MANOVA; microbial interdependence; nonparametric test; Microbiome

Human microbiome is the collection of microbes living in and on the various parts of our body. The microbes living on our body in nature do not live alone. They act as integrated microbial community with massive competing and cooperating and contribute to our human health in a very important way. Most current analyses focus on examining microbial differences at a single time point, which do not adequately capture the dynamic nature of the microbiome data. With the advent of high-throughput sequencing and analytical tools, we are able to probe the interdependent relationship among microbial species through longitudinal study. Here we propose a multivariate distance-based test to evaluate the association between key phenotypic variables and microbial interdependence utilizing the repeatedly measured microbiome data. Extensive simulations were performed to evaluate the validity and efficiency of the proposed method. We also demonstrate the utility of the proposed test using a well-designed longitudinal murine experiment and a longitudinal human study. The proposed methodology has been implemented in the freely distributed open-source R package and Python code.

Authors who are presenting talks have a * after their name.

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