BioNet

This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see BioNet.

Routines for the functional analysis of biological networks


Bioconductor version: 3.7

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 (version "3.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("BioNet")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

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

browseVignettes("BioNet")
BioNet Tutorial PDF R Script
Reference Manual PDF

Details

biocViews DataImport, DifferentialExpression, GeneExpression, GraphAndNetwork, Microarray, Network, NetworkEnrichment, Software
Version 1.40.0
In Bioconductor since BioC 2.7 (R-2.12) (13.5 years)
License GPL (>= 2)
Depends R (>= 2.10.0), graph, RBGL
Imports igraph (>= 1.0.1), AnnotationDbi, Biobase
System Requirements
URL http://bionet.bioapps.biozentrum.uni-wuerzburg.de/
See More
Suggests rgl, impute, DLBCL, genefilter, xtable, ALL, limma, hgu95av2.db, XML
Linking To
Enhances
Depends On Me
Imports Me HTSanalyzeR, SMITE
Suggests Me SANTA
Links To Me
Build Report Build Report

Package Archives

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

Source Package BioNet_1.40.0.tar.gz
Windows Binary BioNet_1.40.0.zip
Mac OS X 10.11 (El Capitan) BioNet_1.40.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/BioNet
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/BioNet
Package Short Url https://bioconductor.org/packages/BioNet/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.7 Source Archive