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.
Bioconductor version: Release (3.5)
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")
R Script | BioNet Tutorial | |
Reference Manual |
biocViews | DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software |
Version | 1.36.0 |
In Bioconductor since | BioC 2.7 (R-2.12) (7 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, SMITE |
Suggests Me | SANTA |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | BioNet_1.36.0.tar.gz |
Windows Binary | BioNet_1.36.0.zip |
Mac OS X 10.11 (El Capitan) | BioNet_1.36.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/BioNet |
Package Short Url | http://bioconductor.org/packages/BioNet/ |
Package Downloads Report | Download Stats |
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