Zero-Inflated gaussian mixed models for analyzing longitudinal microbiome data

MOTIVATION: The human microbiome is variable and dynamic in nature. Longitudinal studies could explain the mechanisms in maintaining the microbiome in health or causing dysbiosis in disease. However, it remains challenging to properly analyze the longitudinal microbiome data from either 16S rRNA or...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Xinyan, Guo, Boyi, Yi, Nengjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652264/
https://www.ncbi.nlm.nih.gov/pubmed/33166356
http://dx.doi.org/10.1371/journal.pone.0242073

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652264/
https://www.ncbi.nlm.nih.gov/pubmed/33166356
http://dx.doi.org/10.1371/journal.pone.0242073

Ejemplares similares