Presented by: Siyuan Ma
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 microbial epidemiology, and will inform future population study designs and analysis practices.
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