Network Correlation Analysis (NECorr)

Contents

• Overview
• Repo Contents
• System Requirements
• Installation Guide
• Instructions for Use
• License
• Citation

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

• R: R package code.
• man: package manual for help in R session.
• int: test data using dummies datasets and model.
• tests: R test with the data.

System Requirements

Hardware Requirements

The package require a long running time depending of the size of molecular network. A computer with 16 GB RAM is recommended to run the package. The necessary C++ or GCC libraries are needed as the software is running partially on Rccp.

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; and 12.6

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 3.5 on Linux

The latest version of R can be installed as follows on Linux:

wget https://cran.rstudio.com/bin/macosx/R-3.4.2.pkg
sudo installer -pkg R-3.5.2.pkg -target /

Installation Guide

Devtools

From an R session, type:

require(devtools)
install_github('warelab/NECorr', build_vignettes=TRUE, dependencies=TRUE, upgrade_dependencies=TRUE)  

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

Package Versions

The NECorr package dependencies will be installed automatically. The following BioConductor package will need to be installed separately

Biobase: 2.54.0
BiocGenerics: 0.40.0
limma: 3.50.3 
AnnotationDbi: 1.56.2
GenomeInfoDbData: 1.2.7 
supraHex: 1.14.0

Instructions for Use

Please see the vignettes for help using the package:

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

Citation

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