Package: rsgcc
Type: Package
Title: Gini methodology-based correlation and clustering analysis of
        both microarray and RNA-Seq gene expression data
Version: 1.0.1
Author: Chuang Ma, Xiangfeng Wang
Maintainer: Chuang Ma <chuangma2006@gmail.com>
Depends: R (>= 2.14.2), biwt, fBasics, snowfall, grDevices, gplots,
        gWidgets, gWidgetsRGtk2, stringr
Suggests: ctc
Description: This package provides functions for calcluating Gini
        correlation coefficient (GCC) and performing GCC-based
        clustering analysis of gene expression data generated from both
        microarray and next-generation sequencing (RNA-Seq)
        technologies. Gini correlation outperforms Pearson correlation
        and Spearman correlation to identify regulatory relationships
        from both microarray and RNA-Seq data. In addtion, GCC has the
        capability of more robustness on non-distribution, less
        sensitivity to outlier data points and higher comatibility to
        RNA-Seq data.
LazyLoad: yes
License: GPL (>= 2)
Date: 2012-03-13
Packaged: 2012-03-14 04:52:05 UTC; wanglab
Repository: CRAN
Date/Publication: 2012-03-14 17:27:22
