To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("BioNet")
In most cases, you don't need to download the package archive at all.
This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see BioNet.
Bioconductor version: 3.2
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")
):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("BioNet")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("BioNet")
BioNet Tutorial | ||
Reference Manual |
biocViews | DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software |
Version | 1.30.0 |
In Bioconductor since | BioC 2.7 (R-2.12) (5.5 years) |
License | GPL (>= 2) |
Depends | R (>= 2.10.0), graph, RBGL |
Imports | igraph (>= 1.0.1), AnnotationDbi, Biobase |
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 |
Follow Installation instructions to use this package in your R session.
Package Source | BioNet_1.30.0.tar.gz |
Windows Binary | BioNet_1.30.0.zip |
Mac OS X 10.6 (Snow Leopard) | BioNet_1.30.0.tgz |
Mac OS X 10.9 (Mavericks) | BioNet_1.30.0.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/BioNet/tree/release-3.2 |
Package Short Url | http://bioconductor.org/packages/BioNet/ |
Package Downloads Report | Download Stats |
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