Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/warelab/necorr
https://github.com/warelab/necorr
Last synced: 20 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/warelab/necorr
- Owner: warelab
- License: mit
- Created: 2016-12-07T19:08:38.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2024-06-18T17:17:45.000Z (7 months ago)
- Last Synced: 2024-06-18T23:34:51.786Z (7 months ago)
- Language: R
- Size: 131 MB
- Stars: 2
- Watchers: 6
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
title: "Network Correlation Analysis (NECorr)"
output: github_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# Contents
- [Overview](#overview)
- [Repo Contents](#repo-contents)
- [System Requirements](#system-requirements)
- [Installation Guide](#installation-guide)
- [Instructions for Use](#instructions-for-use)
- [License](./LICENSE)
- [Citation](#citation)
# Overview {#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 {#repo-contents}
- [R](./R): `R` package code.
- [man](./man): package manual for help in R session.
- [int](./data): test data using dummies datasets and model.
- [tests](./tests): `R` test with the data.
# System Requirements {#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*:
```{bash eval=FALSE, include=TRUE}
wget https://cran.rstudio.com/bin/macosx/R-3.4.2.pkg
sudo installer -pkg R-3.5.2.pkg -target /
```
# Installation Guide {#installation-guide}
## Devtools
From an `R` session, type:
```{r eval=FALSE, include=TRUE}
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](https://www.bioconductor.org/) package will need to be installed separately
```{r eval=FALSE, include=TRUE}
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 {#instructions-for-use}
Please see the vignettes for help using the package:
```{r eval=FALSE, include=TRUE}
vignette("Necorr", package="NECorr")
vignette("gini", package="NECorr")
```
# Citation {#citation}
For citing code or the paper, please use [this citation](https://www.biorxiv.org/content/early/2018/05/21/326868).