EMMIXgene: A Mixture Model-Based Approach to the Clustering of Microarray Expression Data

Provides unsupervised selection and clustering of microarray data using mixture models. Following the methods described in McLachlan, Bean and Peel (2002) <doi:10.1093/bioinformatics/18.3.413> a subset of genes are selected based one the likelihood ratio statistic for the test of one versus two components when fitting mixtures of t-distributions to the expression data for each gene. The dimensionality of this gene subset is further reduced through the use of mixtures of factor analyzers, allowing the tissue samples to be clustered by fitting mixtures of normal distributions.

Version: 0.1.0
Depends: R (≥ 3.3.0)
Imports: Rcpp (≥ 0.12.5), stats, mclust, reshape, ggplot2, scales, tools
LinkingTo: Rcpp, RcppArmadillo, BH
Suggests: R.rsp
Published: 2018-04-03
Author: Andrew Thomas Jones
Maintainer: Andrew Thomas Jones <andrewthomasjones at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: C++11
Citation: EMMIXgene citation info
Materials: NEWS
CRAN checks: EMMIXgene results

Downloads:

Reference manual: EMMIXgene.pdf
Vignettes: R packages: EMMIXgene
Package source: EMMIXgene_0.1.0.tar.gz
Windows binaries: r-devel: EMMIXgene_0.1.0.zip, r-release: EMMIXgene_0.1.0.zip, r-oldrel: EMMIXgene_0.1.0.zip
OS X binaries: r-release: EMMIXgene_0.1.0.tgz, r-oldrel: EMMIXgene_0.1.0.tgz

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