To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GraphPAC")

In most cases, you don't need to download the package archive at all.

GraphPAC

 

   

Identification of Mutational Clusters in Proteins via a Graph Theoretical Approach.

Bioconductor version: Release (3.4)

Identifies mutational clusters of amino acids in a protein while utilizing the proteins tertiary structure via a graph theoretical model.

Author: Gregory Ryslik, Hongyu Zhao

Maintainer: Gregory Ryslik <gregory.ryslik at yale.edu>

Citation (from within R, enter citation("GraphPAC")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GraphPAC")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("GraphPAC")

 

PDF R Script iPAC: identification of Protein Amino acid Mutations
PDF   Reference Manual
Text   NEWS

Details

biocViews Clustering, Proteomics, Software
Version 1.16.0
In Bioconductor since BioC 2.12 (R-3.0) (4 years)
License GPL-2
Depends R (>= 2.15), iPAC, igraph, TSP, RMallow
Imports
LinkingTo
Suggests RUnit, BiocGenerics
SystemRequirements
Enhances
URL
Depends On Me QuartPAC
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source GraphPAC_1.16.0.tar.gz
Windows Binary GraphPAC_1.16.0.zip
Mac OS X 10.9 (Mavericks) GraphPAC_1.16.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/GraphPAC/tree/release-3.4
Package Short Url http://bioconductor.org/packages/GraphPAC/
Package Downloads Report Download Stats

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