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Activity Number: 442 - Methods for Single-Cell and Microbiome Sequencing Data
Type: Topic Contributed
Date/Time: Thursday, August 6, 2020 : 10:00 AM to 11:50 AM
Sponsor: Biometrics Section
Abstract #313466
Title: A Hierarchical Model for Microbial Abundance Observations
Author(s): Siyuan Ma*
Companies: Harvard University
Keywords: Microbiome; Hierarichcal modeling; Monte Carlo; Compositional data; Zero inflation

We present a hierarchical model of microbial community count observations, suitable for simulation of such data at population scale. Our model has specialized components targeting characteristics unique to microbiome data, including sparsity, joint effects of biological and sequencing variation, and ecological feature dependencies, and is capable of simulating mock microbial counts that recapitulate the population structures in training template communities. We hope that these methods and findings will be of broad applicability in human transcriptional and microbial epidemiology, and will inform future population study designs and analysis practices.

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

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