MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package

Koslovsky, Matthew D.; Vannucci, Marina

MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package

Files

MicroBVS.pdf (2.02 MB)

Date

2020

Authors

Koslovsky, Matthew D.

Vannucci, Marina

Publisher

Springer Nature

Abstract

Understanding the relation between the human microbiome and modulating factors, such as diet, may help researchers design intervention strategies that promote and maintain healthy microbial communities. Numerous analytical tools are available to help identify these relations, oftentimes via automated variable selection methods. However, available tools frequently ignore evolutionary relations among microbial taxa, potential relations between modulating factors, as well as model selection uncertainty.

Type

Journal article

Citation

Koslovsky, Matthew D. and Vannucci, Marina. "MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package." BMC Bioinformatics, 21, no. 1 (2020) Springer Nature: https://doi.org/10.1186/s12859-020-03640-0.

Published Version

https://doi.org/10.1186/s12859-020-03640-0

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