A Graphical Model for Fusing Diverse Microbiome Data. (arXiv:2208.09934v1 [stat.ME])

This paper develops a Bayesian graphical model for fusing disparate types of
count data. The motivating application is the study of bacterial communities
from diverse high dimensional features, in this case transcripts, collected
from different treatments. In such datasets, there are no explicit
correspondences between the communities and each correspond to different
factors, making data fusion challenging. We introduce a flexible
multinomial-Gaussian generative model for jointly modeling such count data.
This latent variable model jointly characterizes the observed data through …

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