BRACoD: Bayesian Regression Analysis of Compositional Data

The goal of this method is to identify associations between bacteria and an environmental variable in 16S or other compositional data. The environmental variable is any variable which is measure for each microbiome sample, for example, a butyrate measurement paired with every sample in the data. Microbiome data is compositional, meaning that the total abundance of each sample sums to 1, and this introduces severe statistical distortions. This method takes a Bayesian approach to correcting for these statistical distortions, in which the total abundance is treated as an unknown variable. This package runs the python implementation using reticulate.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("BRACoD.R")

0.0.1.2 by Adrian Verster, 4 months ago


Browse source code at https://github.com/cran/BRACoD.R


Authors: Adrian Verster [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports reticulate

Suggests testthat


See at CRAN