rsgcc: Gini methodology-based correlation and clustering analysis of microarray and RNA-Seq gene expression data

This package provides functions for calculating associations between two genes with five correlation methods(e.g., the Gini correlation coefficient [GCC], the Pearson's product moment correlation coefficient [PCC], the Kendall tau rank correlation coefficient [KCC], the Spearman's rank correlation coefficient [SCC] and the Tukey's biweight correlation coefficient [BiWt], and three non-correlation methods (e.g., mutual information [MI] and the maximal information-based nonparametric exploration [MINE], and the euclidean distance [ED]). It can also been implemented to perform the correlation and clustering analysis of transcriptomic data profiled by microarray and RNA-Seq technologies. Additionally, this package can be further applied to construct gene co-expression networks (GCNs).

Version: 1.0.6
Depends: R (≥ 2.15.1), biwt, cairoDevice, fBasics, grDevices, gplots, gWidgets, gWidgetsRGtk2, minerva, parmigene, stringr, snowfall
Suggests: bigmemory, ctc
Published: 2013-06-18
Author: Chuang Ma, Xiangfeng Wang
Maintainer: Chuang Ma <chuangma2006 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: rsgcc results


Reference manual: rsgcc.pdf
Package source: rsgcc_1.0.6.tar.gz
MacOS X binary: rsgcc_1.0.6.tgz
Windows binary:
Old sources: rsgcc archive

Reverse dependencies:

Reverse depends: mlDNA