Variational Bayes for Latent Patient Phenotypes in EHR.

VBphenoR

Variational Bayes for Latent Patient Phenotypes in Electronic Health Records (EHR)

Overview

VBphenoR is an R package for discovering latent patient phenotypes from realistically large EHR data using Bayesian statistics. In order to computationally support EHR data, we employ variational Bayes (VB). Currently, it supports latent class discovery using VB Gaussian Mixture Model implemented with Coordinate-ascent Variational Inference (CAVI) and VB Logistic Regression for biomarker levels shifted for the latent phenotype. Please note this package is still under development.

Installation

Prior to analyzing your EHR data, the R package needs to be installed. The easiest way to install VBphenoR is through CRAN:

install.packages("VBphenoR")

VBphenoR can also be downloaded and installed via GitHub. This is most useful for downloading a specific version of the package (which can be found at https://github.com/buckleybrian/VBphenoR/releases):

devtools::install_github("buckleybrian/[email protected]")

# or 

devtools::install_version("VBphenoR", version = "x.x.x", repos = "http://cran.us.r-project.org")

The latest developmental version of the package can be downloaded and installed by running:

devtools::install_github("buckleybrian/VBphenoR", build_vignettes = TRUE, build_manual=TRUE)

After successful installation, the package must be loaded into the working space:

library(VBphenoR)

Usage

See the vignette for usage instructions and example.

License

VBphenoR is available under the open source MIT License.