Package: BioNet 1.73.0

Marcus Dittrich

BioNet: Routines for the functional analysis of biological networks

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.

Authors:Marcus Dittrich and Daniela Beisser

BioNet_1.73.0.tar.gz
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BioNet_1.73.0.tgz(r-4.6-any)BioNet_1.73.0.tgz(r-4.5-any)
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manual.pdf |manual.html✨
card.svg |card.png
BioNet/json (API)

# Install 'BioNet' in R:
install.packages('BioNet', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On BioConductor:BioNet-1.73.0(bioc 3.24)BioNet-1.72.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

microarraydataimportgraphandnetworknetworknetworkenrichmentgeneexpressiondifferentialexpression

6.15 score 2 packages 117 scripts 788 downloads 40 mentions 42 exports 42 dependencies

Last updated from:52d7a61b57. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR191
linux-devel-x86_64NOTE284
source / vignettesOK275
linux-release-x86_64NOTE282
macos-release-arm64NOTE375
macos-oldrel-arm64NOTE243
windows-develNOTE711
windows-releaseNOTE592
windows-oldrelNOTE574
wasm-releaseOK190

Exports:aggrPvalsbumOptimcompareNetworksconsensusScoresfbumfbumLLfdrThresholdfitBumModelgetCompScoresgetEdgeListhist.bumlargestComplargestScoreComploadNetwork.sifloadNetwork.tabmakeNetworkmapByVarpermutateNodespiUpperplot.bumplot3dModuleplotLLSurfaceplotModuleprint.bumreadHeinzGraphreadHeinzTreeresamplingPvaluesrmSelfLoopsrunFastHeinzrunHeinzsave3dModulesaveNetworkscanFDRscoreFunctionscoreNodesscoreOffsetsortedEdgeListsubNetworksummary.bumwriteHeinzwriteHeinzEdgeswriteHeinzNodes

Dependencies:AnnotationDbiaskpassBHBiobaseBiocGenericsBiostringsbitbit64blobcachemclicpp11crayoncurlDBIfastmapgenericsgluegraphhttrigraphIRangesjsonliteKEGGRESTlatticelifecyclemagrittrMatrixmemoisemimeopensslpkgconfigpngR6RBGLrlangRSQLiteS4VectorsSeqinfosysvctrsXVector

BioNet Tutorial

Rendered fromTutorial.Rnwusingutils::Sweaveon May 29 2026.

Last update: 2020-10-05
Started: 2013-11-01

Readme and manuals

Help Manual

Help pageTopics
Routines for the functional analysis of biological networksBioNet-package BioNet
Aggregate several p-values into one p-valueaggrPvals
Fitting a beta-uniform mixture model to p-value distributionbumOptim
Compare parameters of two networkscompareNetworks
Calculation of a consensus score for a networkconsensusScores
Compute the density of the bum distributionfbum
Calculate log likelihood of BUM modelfbumLL
Calculate p-value threshold for given FDRfdrThreshold
Fit beta-uniform mixture model to a p-value distributionfitBumModel
Partition scores for subgraphs of the networkgetCompScores
Get representation of graph as edgelistgetEdgeList
Histogram of the p-value distribution with the fitted bum modelhist.bum
Extract largest component of networklargestComp
Component with largest scorelargestScoreComp
Load network from Cytoscape sif fileloadNetwork.sif
Load network from tabular formatloadNetwork.tab
Create graph from source and target vectorsmakeNetwork
Select probeset by variance and get PPI IDmapByVar
Permute node labelspermutateNodes
Upper bound pi for the fraction of noisepiUpper
Quantile-quantile plot for the beta-uniform mixture modelplot.bum
3D plot of the networkplot3dModule
Log likelihood surface plotplotLLSurface
Plot of the networkplotModule
Print information about bum modelprint.bum
Example p-values for aggregation statisticspvaluesExample
Convert HEINZ output to graphreadHeinzGraph
Convert HEINZ output to treereadHeinzTree
Resampling of microarray expression values and test for differential expression.resamplingPvalues
Remove self-loops in a graphrmSelfLoops
Calculate heuristically maximum scoring subnetworkrunFastHeinz
Start HEINZrunHeinz
Save a 3D plot of the networksave3dModule
Save undirected network in various formatssaveNetwork
Dataframe of scores over a given range of FDRsscanFDR
Scoring function for p-valuesscoreFunction
Score the nodes of a networkscoreNodes
Change score offset for 2 FDRsscoreOffset
Get a sorted edgelistsortedEdgeList
Create a subGraphsubNetwork
Print summary of informations about bum modelsummary.bum
Write input files for HEINZwriteHeinz
Write edge input file for HEINZwriteHeinzEdges
Write node input file for HEINZwriteHeinzNodes