Variational inference for microbiome survey data with application to global ocean data
Aditya Mishra,
Jesse McNichol,
Jed Fuhrman
et al.
Abstract:Linking sequence-derived microbial taxa abundances to host (patho-)physiology or habitat characteristics in a reproducible and interpretable manner has remained a formidable challenge for the analysis of microbiome survey data. Here, we introduce a flexible probabilistic modeling framework, VI-MIDAS (Variational Inference for MIcrobiome survey DAta analysiS), that enables joint estimation of context-dependent drivers and broad patterns of associations of microbial taxon abundances from microbiome survey data. … Show more
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