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rsgcc (version 1.0.6)

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

Description

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).

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Version

Install

install.packages('rsgcc')

Monthly Downloads

49

Version

1.0.6

License

GPL (>= 2)

Maintainer

Chuang Ma

Last Published

June 18th, 2013

Functions in rsgcc (1.0.6)

cor.pair

compute the correlation between two genes
getsgene

identify tissue(or condtion)-specific genes
gcc.heatmap

heat map
cor.matrix

correlation calculation for a set of genes
onegcc

compute one Gini correlation coefficient
rsgcc-package

Gini methodology-based correlation and clustering analysis of microarray and RNA-Seq gene expression data
gcc.hclust

hierarchical cluster
rsgcc.gui

graphical user interface (GUI) of rsgcc package
adjacencymatrix

adjacency matrix calculation
uniqueTissues

get tissue information
gcc.tsheatmap

correlaiton and clustering analysis of tissue-specific genes
gcc.dist

compute distance matrix for hierarchical clustering
gcc.corfinal

get the final correlaiton and p-value of Gini method
data

example of RNA-Seq gene expression data