DESCRIPTION

Package: CSMR
Type: Package
Title: A novel supervised clustering algorithm using penalized mixture regression model
Version: 0.0.1
Date: 2020-07-20
Authors@R: c(
             person("Wennan", "Chang", email = "wnchang@iu.edu", role = c("aut", "cre"))
             )
Author: 
  Wennan Chang [aut, cre]
Maintainer: Wennan Chang <wnchang@iu.edu>
Description: Identifying relationships between molecular variations and their clinical presentations has been challenged by the heterogeneous causes of a disease. It is imperative to unveil the relationship between the high dimensional molecular manifestations and the clinical presentations, while taking into account the possible heterogeneity of the study subjects.We proposed a novel supervised clustering algorithm using penalized mixture regression model, called CSMR, to deal with the challenges in studying the heterogeneous relationships between high dimensional molecular features to a phenotype. The algorithm was adapted from the classification expectation maximization algorithm, which offers a novel supervised solution to the clustering problem, with substantial improvement on both the computational efficiency and biological interpretability.
Depends: R (>= 3.5.0)
License: GPL
Encoding: UTF-8
LazyData: true
Imports:  stats,dplyr,lars,gplots,grDevices,scales,graphics,rlang
RoxygenNote: 6.1.1
URL: https://github.com/zcslab/CSMR
BugReports: https://github.com/zcslab/CSMR/issues