Infants' gut microbiome data: A Bayesian Marginal Zero-inflated Negative Binomial regression model for multivariate analyses of count data.

ABSTRACT: The infants' gut microbiome is dynamic in nature. Literature has shown high inter-individual variability of gut microbial composition in the early years of infancy compared to adulthood. Although next-generation sequencing technologies are rapidly evolving, several statistical analysis aspects need to be addressed to capture the variability and dynamic nature of the infants' gut microbiome. In this study, we proposed a Bayesian Marginal Zero-inflated Negative Binomial (BAMZINB) model, addressing complexities associated with zero-inflation and multivariate structure of the infants' gut microbiome data. Here, we simulated 32 scenarios to compare the performance of BAMZINB with glmFit and BhGLM as the two other widely similar methods in the literature in handling zero-inflation, over-dispersi

SUBMITTER: Hajihosseini M 

PROVIDER: S-EPMC9969297 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature