cma2015/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).

Getting started

Package details

AuthorChuang Ma, Xiangfeng Wang
MaintainerChuang Ma <[email protected]>
LicenseGPL (>= 2)
Version1.0.6
URL http://www.cmbb.arizona.edu/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("cma2015/rsgcc")
cma2015/rsgcc documentation built on May 24, 2019, 7:33 a.m.