Cargando…
Bayesian hierarchical negative binomial models for multivariable analyses with applications to human microbiome count data
The analyses of large volumes of metagenomic data extracted from aggregate populations of microscopic organisms residing on and in the human body are advancing contemporary understandings of the integrated participation of microbes in human health and disease. Next generation sequencing technology f...
Autores principales: | Pendegraft, Amanda H., Guo, Boyi, Yi, Nengjun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6706006/ https://www.ncbi.nlm.nih.gov/pubmed/31437194 http://dx.doi.org/10.1371/journal.pone.0220961 |
Ejemplares similares
-
Negative Binomial Mixed Models for Analyzing Longitudinal Microbiome Data
por: Zhang, Xinyan, et al.
Publicado: (2018) -
Negative binomial mixed models for analyzing microbiome count data
por: Zhang, Xinyan, et al.
Publicado: (2017) -
Infants’ gut microbiome data: A Bayesian Marginal Zero-inflated Negative Binomial regression model for multivariate analyses of count data
por: Hajihosseini, Morteza, et al.
Publicado: (2023) -
NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis
por: Zhang, Xinyan, et al.
Publicado: (2020) -
A Bayesian Negative Binomial Hierarchical Model for Identifying Diet–Gut Microbiome Associations
por: Revers, Alma, et al.
Publicado: (2021)