Package: BioNAR 1.9.1

Anatoly Sorokin

BioNAR: Biological Network Analysis in R

the R package BioNAR, developed to step by step analysis of PPI network. The aim is to quantify and rank each protein’s simultaneous impact into multiple complexes based on network topology and clustering. Package also enables estimating of co-occurrence of diseases across the network and specific clusters pointing towards shared/common mechanisms.

Authors:Colin Mclean [aut], Anatoly Sorokin [aut, cre], Oksana Sorokina [aut], J. Douglas Armstrong [aut, fnd], T. Ian Simpson [ctb, fnd]

BioNAR_1.9.1.tar.gz
BioNAR_1.9.1.zip(r-4.5)BioNAR_1.9.1.zip(r-4.4)
BioNAR_1.9.1.tgz(r-4.4-any)
BioNAR_1.9.1.tar.gz(r-4.5-noble)BioNAR_1.9.1.tar.gz(r-4.4-noble)
BioNAR_1.9.1.tgz(r-4.4-emscripten)
BioNAR.pdf |BioNAR.html✨
BioNAR/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/lptolik/bionar/issues

Datasets:

On BioConductor:BioNAR-1.9.0(bioc 3.21)BioNAR-1.8.0(bioc 3.20)

softwaregraphandnetworknetwork

5.87 score 3 stars 35 scripts 187 downloads 72 exports 131 dependencies

Last updated 8 days agofrom:e9d4e8bcaa. Checks:OK: 1 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 11 2024
R-4.5-winNOTEDec 11 2024
R-4.5-linuxNOTEDec 11 2024
R-4.4-winNOTEDec 11 2024
R-4.4-macNOTEDec 11 2024

Exports:addEdgeAttsannotateGeneNamesannotateGoBPannotateGoCCannotateGoMFannotateGOontannotateInterproannotatePresynapticannotateSCHannoannotateTopOntoOVGannotateVertexapplpMatrixToGraphbuildConsensusMatrixbuildNetworkcalcAllClusteringcalcBridgenesscalcCentralitycalcCentralityExternalDistancescalcCentralityInternalDistancescalcClusteringcalcDiseasePairscalcEntropycalcMembershipcalcReclusterMatrixcalcSparsnessclusteringSummaryclusterORAdegreeBinnedGDAsescapeAnnotationevalCentralitySignificancefindLCCfitDegreefitSigmoidgetAnnotationListgetAnnotationVertexListgetBridgenessgetCentralityMatrixgetClusteringgetClusterSubgraphByIDgetCommunityGraphgetDiseasesgetDTypegetDYNAMOgetEntropygetEntropyRategetGNPgetGraphCentralityECDFgetPAgetRandomGraphCentralitygetRobustnessgofslayoutByClusterlayoutByReclustermakeConsensusMatrixmakeMembershipmarkBowTiemetlMatrixnormModularitypermuteplotBridgenessplotEntropyplotRatioplotSigmoidprepareGDAreclusterremoveVertexTermrunPermDiseasesampleDegBinnedGDAsampleGraphClustsummaryStatsunescapeAnnotationzeroNA

Dependencies:AnnotationDbiaskpassbackportsbase64encBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobbslibcachemcheckmatecliclustercodetoolscolorspacecowplotcpp11crayoncurldata.tableDBIdigestdoParalleldplyrdynamicTreeCutevaluatefansifarverfastclusterfastmapfastmatchfgseafontawesomeforeachforeignformatRFormulafsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataggplot2ggrepelglueGO.dbgraphgridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetshttrigraphimputeIRangesisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlatex2explatticelifecyclemagrittrMASSMatrixmatrixStatsmemoisemgcvmimeminpack.lmmunsellnlmennetopensslorg.Hs.eg.dbpillarpkgconfigplogrpngpoweRlawpracmapreprocessCoreR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackrlangrmarkdownrpartRSpectrarSpectralRSQLiterstudioapiS4VectorssassscalessnowstringistringrsurvivalsystibbletidyselecttinytexUCSC.utilsutf8vctrsviridisviridisLiteWGCNAwithrxfunXVectoryamlzlibbioc

BioNAR: Biological Network Analysis in R

Colin Mclean, Anatoly Sorokin, T. I. Simpson, J. Douglas Armstrong, Oksana Sorokina

Rendered fromBioNAR_overview.Rmdusingknitr::rmarkdownon Dec 11 2024.

Last update: 2024-04-26
Started: 2022-10-21

Readme and manuals

Help Manual

Help pageTopics
Copy edge attributes from one graph to anotheraddEdgeAtts
Annotate Human Gene NamesannotateGeneNames
Add GO BP annotation to the graph verticesannotateGoBP
Add GO CC annotation to the graph verticesannotateGoCC
Add GO MF annotation to the graph verticesannotateGoMF
Annotate nodes with GO termsannotateGOont
Add InterPro Family and Domain annotation to the graph verticesannotateInterpro
Add presynaptic functional groupsannotatePresynaptic
Add SCHanno synaptic functional groupsannotateSCHanno
Annotate graph with disease termsannotateTopOntoOVG
Generic annotation functionannotateVertex
Add attributes to the vertex.applpMatrixToGraph
BioNAR: Biological Network Analysis in RBioNAR-package BioNAR
Build network from data.tablebuildNetwork
Calculate memberships for all clustering algorithms and store them on the graph vertices.calcAllClustering
Helper function that uses 'getBridgeness' to calculate graph node bridgeness values for selected algorithm and consensus matrix and save them as a graph attribute 'BRIDGENESS.<alg>' with '<alg>' replaced by the selected algorithm name.calcBridgeness
Calculate the vertex centrality measurescalcCentrality
Function to calculate a distance matrix between a list of permuted vertex centrality matrices and a unperturbed reference matrix.calcCentralityExternalDistances
Function calculates a set of distance metrics between each vertex pair given a list of vertex centrality matricescalcCentralityInternalDistances
Calculate community membership for given clustering algorithm and store the results as new vertex attributes in the graph..calcClustering
Calculate each disease-disease pair overlap given a list of disease terms.calcDiseasePairs
Calculate the graph entropy for each perturbed vertex, and save the results as new vertex attributes in the graph.calcEntropy
Calculate cluster memberships for the graph.calcMembership
Hierarchical graph clusteringcalcReclusterMatrix
Calculate sparsness of the graph.calcSparsness
Matrix of cluster characteristicsclusteringSummary
Calculate annotation enrichment for clusters in the graphclusterORA
Prepare mapping for degree-aware annotation shuffling.degreeBinnedGDAs
Barabasi's Diseasome Networkdiseasome
Escapes elements of list in annotation.escapeAnnotation
Compare distance distributions of internal and external distancesevalCentralitySignificance
Find Largest Connected Component of the graphfindLCC
Fit Power Law to degree distribution.fitDegree
Fit Fold-enrichment distribution to sigmoid functionfitSigmoid
Human Gene Disease Associations (GDA)flatfile_human_gene2HDO.csv
Annotation from Gene Ontology Biological Process (GO_BP)flatfile.go.BP.csv
Annotation from Gene Ontology Cellular Compartment (GO_CC)flatfile.go.CC.csv
Annotation from Gene Ontology Molecular Function (GO_MF)flatfile.go.MF.csv
Extract unique values from annotations.getAnnotationList
Return vertex list for each term in annotation attributegetAnnotationVertexList
Calculate bridginess from consensus matrixgetBridgeness
Calculate centrality measures for graph nodes.getCentralityMatrix
Get clustering results for the graph.getClustering
Return induced subgraph for clustergetClusterSubgraphByID
Create new graph with communities as a nodes.getCommunityGraph
Get HDO disease IDsgetDiseases
Get DiseaseTypesgetDType
Calculate DYNAMO sensitivity matrix.getDYNAMO
Calculates vertex perturbation graph entropy.getEntropy
Calculate the maximum entropy rate and initial entropy rate .getEntropyRate
Generate random graph from referencegetGNP
Convert centrality matrix into ECDFgetGraphCentralityECDF
Utility function to get vertex ids from vertex attributes The function obtain attribute values and check duplicates in it. It fails if any duplicate found.getIDs
Generate random graph from referencegetPA
Centrality measures for random graphs induced by input onegetRandomGraphCentrality
Calculate cluster robustness from consensus matrixgetRobustness
Goodnes of fit KS testgofs
Result of PawerLaw fitlaw-class
Calculate layout based upon membershiplayoutByCluster
Calculate two-level layout from recluster matrixlayoutByRecluster
Function to make random resampling consensus matrix in memorymakeConsensusMatrix
Create membership 'data.frame' from graph for arbitrary annotationmakeMembership
Calculates bow-tie decomposition and marks vertices with one of the following in the 'BowTie' attribute: • SCC -- maximal strong connected component; • IN -- vertices not in SCC, but SCC is reachable from them; • OUT -- vertices not in SCC, but reachable from SCC; • TU -- vertices not in all three above, but reachable from IN and OUT is reachable from them (TUBES); • IDR -- vertices not in SCC, but they are reachable from IN and OUT is NOT reachable from them (INTENDRILS); • ODR -- vertices not is SCC, but they are NOT reachable from IN and OUT is reachable from them (OUTTENDRILS); • OTR -- all other vertices.markBowTie
Convert sparce matrix into triplet 'data.frame'.metlMatrix
Calculates the normalised network modularity value.normModularity
Randomly shuffle annotationspermute
Plot Bridgeness valuesplotBridgeness
Plot graph entropy values versus vertex degree for each perturbed vertex value.plotEntropy
Plot fraction of enriched communitiesplotRatio
Plot results of the sigmoid fitplotSigmoid
Table of protein protein interactions for presynaptic compartmentPPI_Presynaptic.csv
PPI graph for presynaptic compartmentPPI_Presynaptic.gml
Function to return vertex annotation from a graph in the Vertex Annotation form and format it for further analysis.prepareGDA
Presynaptic genes specific functional annotationPresynAn.csv
Hierarchical graph clusteringrecluster
Remove vertex property.removeVertexTerm
Calculate disease-disease pair overlaps on permuted network to estimate its statistical significancerunPermDisease
Function to randomly shuffle vertex annotation terms, whilst preserving the vertex degree originally found with that annotation term..sampleDegBinnedGDA
Perturbe graph and calculate its clusteringsampleGraphClust
Schizopherina related synaptic gene functional annotation.SCH_flatfile.csv
Calculate summary statistics from enrichment tablesummaryStats
Unescape annotation stringsunescapeAnnotation
Auxiliary function to replace NAs with zeros.zeroNA