Network Correlation Analysis (NECorr)

Contents

Overview

NECorr is a R package based on multiple-criteria decision-making algorithms. With the objective of ranking genes and their interactions in a selected condition or tissue, NECorr uses molecular network topology as well as global transcriptomics analysis to find condition/tissue-specific hub genes and their regulators.

Repo Contents

System Requirements

Hardware Requirements

The runtimes below are generated using a computer with the recommended specs (16 GB RAM, 4 cores@3.3 GHz) and internet of speed 25 Mbps.

Software Requirements

OS Requirements

This package is supported for Mac OS, Windows and Linux operating systems. The package has been tested on the following systems:

Linux: Redhat RHEL 7.4
Mac OSX: OS X 11.2.3

The NECorr packages requires the R version 3.4.2 or higher and a standard computer with enough RAM to support the operations defined by a user. For minimal performance, this will be a computer with about 1 GB of RAM.

Installing R version 3.4.2 on MacOs

the latest version of R can be installed as follows:

wget https://cran.rstudio.com/bin/macosx/R-3.4.2.pkg
sudo installer -pkg R-3.4.2.pkg -target /
rm R-3.2.3.pkg

Two minutes will be required to install R on Mac Os.

Installing R on Linux (yum package manager)

sudo yum install R.x86_64

Package dependencies

Users should install the following packages prior to installing NECorr, from an R terminal:

install.packages(c("Rcpp", "RcppParallel", "klaR", "igraph", "foreach", "doSNOW", "RColorBrewer", "gplots", "devtools", "hash"))
source("https://bioconductor.org/biocLite.R")
biocLite(c("Biobase", "limma", "supraHex"))
install.packages("dnet")

Package Versions

The NECorr package functions with all packages in their latest versions as they appear on CRAN on October 15, 2017. Users can check CRAN snapshot and BioConductor for details. The versions of software are, specifically:

Rcpp: 0.12.17
klaR: 0.6-12
igraph: 1.0.1
dnet: 1.1.3 
foreach: 1.4.3
doSNOW: 1.0.15 
RColorBrewer: 1.1-2
gplots: 3.0.1
devtools: 1.13.2
Biobase: 2.36.2
limma: 3.32.10 
hash: 2.2.6
supraHex: 1.14.0

Installation Guide

From an R session, type:

require(devtools)
install_github('warelab/NECorr', build_vignettes=TRUE, dependencies=FALSE, upgrade_dependencies=FALSE)  # install NECorr with the vignettes

The package should take approximately 20 seconds to install with vignettes on a recommended computer.

Instructions for Use

Please see the vignettes for help using the package:

vignette("Necorr", package="NECorr")
vignette("gini", package="NECorr")

Demo

Use the the scripts with the small demo dataset present in the data folder:

tests/test.script.R

Citation

For citing code or the paper, please use this citation.



warelab/NECorr documentation built on April 29, 2021, 6:47 a.m.