metamicrobiomeR: Analysis of Microbiome Relative Abundance Data using Zero Inflated Beta GAMLSS and Meta-Analysis Across Studies using Random Effects Model

Generalized Additive Model for Location, Scale and Shape (GAMLSS) with zero inflated beta (BEZI) family for analysis of microbiome relative abundance data (with various options for data transformation/normalization to address compositional effects) and random effects meta-analysis models for meta-analysis pooling estimates across microbiome studies are implemented. Random Forest model to predict microbiome age based on relative abundances of shared bacterial genera with the Bangladesh data (Subramanian et al 2014), comparison of multiple diversity indexes using linear/linear mixed effect models and some data display/visualization are also implemented. The reference paper is published by Ho NT, Li F, Wang S, Kuhn L (2019) <doi:10.1186/s12859-019-2744-2> .

Package details

AuthorNhan Ho [aut, cre]
MaintainerNhan Ho <[email protected]>
LicenseGPL-2
Version1.1
URL https://github.com/nhanhocu/metamicrobiomeR
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("metamicrobiomeR")

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metamicrobiomeR documentation built on Sept. 3, 2019, 9:04 a.m.