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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.
R
package code.R
test with the data.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.
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.
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 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.
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
Please see the vignettes for help using the package:
vignette("Necorr", package="NECorr") vignette("gini", package="NECorr")
For citing code or the paper, please use this citation.
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