Bayesian Hierarchical Compositional Models for Analysing Longitudinal Abundance Data from Microbiome Studies

Autor: I. Creus Martí, A. Moya, F. J. Santonja
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Complexity, Vol 2022 (2022)
Druh dokumentu: article
ISSN: 1099-0526
DOI: 10.1155/2022/4907527
Popis: Gut microbiome plays a significant role in defining the health status of subjects, and recent studies highlight the importance of using time series strategies to analyse microbiome dynamics. In this paper, we develop a Bayesian model for microbiota longitudinal data, based on Dirichlet distribution with time-varying parameters, that take into account the compositional paradigm and consider principal balances. The proposed model can be effective for predicting the future dynamics of a microbial community in the short term and for analysing the microbial interactions using the value of the estimated parameters. The usefulness of the proposed model is illustrated with six different datasets, and a comparison study with four alternative models is provided.
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