To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("BioNet")

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

BioNet

 

Routines for the functional analysis of biological networks

Bioconductor version: Release (3.1)

This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork.

Author: Marcus Dittrich and Daniela Beisser

Maintainer: Marcus Dittrich <marcus.dittrich at biozentrum.uni-wuerzburg.de>

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

Installation

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("BioNet")

Documentation

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

browseVignettes("BioNet")

 

PDF R Script BioNet Tutorial
PDF   Reference Manual

Details

biocViews DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software
Version 1.28.0
In Bioconductor since BioC 2.7 (R-2.12) (5 years)
License GPL (>= 2)
Depends R (>= 2.10.0), Biobase, graph, RBGL
Imports igraph (>= 0.7), AnnotationDbi
LinkingTo
Suggests rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML
SystemRequirements
Enhances
URL http://bionet.bioapps.biozentrum.uni-wuerzburg.de/
Depends On Me
Imports Me HTSanalyzeR
Suggests Me SANTA
Build Report  

Package Archives

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

Package Source BioNet_1.28.0.tar.gz
Windows Binary BioNet_1.28.0.zip
Mac OS X 10.6 (Snow Leopard) BioNet_1.28.0.tgz
Mac OS X 10.9 (Mavericks) BioNet_1.28.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/BioNet/tree/release-3.1
Package Short Url http://bioconductor.org/packages/BioNet/
Package Downloads Report Download Stats

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