/bayesianmice

A Bayesian model-based investigation of Candida albicans colonization in a preclinical mouse model.

Primary LanguageRMIT LicenseMIT

Scope

The script, bayesianmice_visualization.R, provides the complete underlying data and code for all the figures in the Results section on the main project website and in the manuscript:

Shankar, J. et al. Using Bayesian modelling to investigate factors governing antibiotic-induced Candida albicans colonization of the GI tract. Scientific Reports. 5, 8131; DOI:10.1038/srep08131 (2015). Available at: http://dx.doi.org/10.1038/srep08131

The main website, data and additional documentation is @ the main project website

For model specifications, underlying theory as well as a comparative evaluation of BMA ensemble regression against other ensemble regression models, please review:

Shankar J, Szpakowski S et al. A systematic evaluation of high-dimensional, ensemble-based regression for exploring large model spaces in microbiome analyses. BMC Bioinformatics. 2015 Feb;16(1):31+. DOI:10.1186/s12859-015-0467-6. Available at: http://dx.doi.org/10.1186/s12859-015-0467-6.

Code and documentation for the BMA models can be found in the regeval repository @ https://github.com/openpencil/regeval

Citing bayesianmice

Shankar, J. et al. Using Bayesian modelling to investigate factors governing antibiotic-induced Candida albicans colonization of the GI tract. Scientific Reports. 5, 8131; DOI:10.1038/srep08131 (2015). Available at: http://dx.doi.org/10.1038/srep08131

BibTeX

@ARTICLE{Shankar2015bayesianmice,
  title       = "Using Bayesian modelling to investigate factors governing
                 antibiotic-induced Candida albicans colonization of the {GI}
                 tract",
  author      = "Shankar, Jyoti and Solis, Norma V and Mounaud, Stephanie and
                 Szpakowski, Sebastian and Liu, Hong and Losada, Liliana and
                 Nierman, William C and Filler, Scott G",
  journal     = "Scientific reports",
  publisher   = "Nature Publishing Group",
  volume      =  5,
  pages       = "8131",
  month       =  "3~" # feb,
  year        =  2015,
  url         = "http://dx.doi.org/10.1038/srep08131",
  issn        = "2045-2322, 2045-2322",
  pmid        = "25644850",
  doi         = "10.1038/srep08131",
  note        = "bayesianmice repository: https://github.com/openpencil/regeval"
}