Package: iNETgrate 1.3.0

Habil Zare

iNETgrate: Integrates DNA methylation data with gene expression in a single gene network

The iNETgrate package provides functions to build a correlation network in which nodes are genes. DNA methylation and gene expression data are integrated to define the connections between genes. This network is used to identify modules (clusters) of genes. The biological information in each of the resulting modules is represented by an eigengene. These biological signatures can be used as features e.g., for classification of patients into risk categories. The resulting biological signatures are very robust and give a holistic view of the underlying molecular changes.

Authors:Isha Mehta [aut], Ghazal Ebrahimi [aut], Hanie Samimi [aut], Habil Zare [aut, cre]

iNETgrate_1.3.0.tar.gz
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iNETgrate_1.3.0.tgz(r-4.4-any)iNETgrate_1.3.0.tgz(r-4.3-any)
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iNETgrate.pdf |iNETgrate.html✨
iNETgrate/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/bioconductor/biocmanager/issues

Datasets:
  • toyCleanedAml - A subset of cleaned TCGA-LAML data
  • toyComputEloci - A subset of weighted DNA methylation profile of TCGA-LAML data
  • toyEigengenes - A subset of weighted average of gene expression present in each module
  • toyRawAml - A subset of TCGA-LAML data

On BioConductor:iNETgrate-1.3.0(bioc 3.20)iNETgrate-1.2.0(bioc 3.19)

bioconductor-package

26 exports 0.91 score 277 dependencies

Last updated 2 months agofrom:0966b8f728

Exports:accelFailAnalysisanalyzeSurvivalbestInetgratorcleanAllDatacomputEigengenescomputEigenlocicomputeInetgratorcomputeUnioncoxAnalysiscreateLocusGenedistanceToTsselectGenesfilterLowCorfindAliveCutofffindCorefindTcgaDuplicatesiNETgrateinferEigengenesmakeNetworkplotKMplotLociNumplotLociTssprepareSurvivalpreprocessDnamsample2patsampleData

Dependencies:abindannotateAnnotationDbiapeaplotaskpassbackportsbase64base64encbeanplotBHBiobaseBiocFileCacheBiocGenericsBiocIOBiocManagerBiocParallelBiocStylebiomaRtBiostringsbitbit64bitopsblobbnlearnbookdownbslibbumphunterC50cachemcaretcaToolscheckmateclassclicliprclockclusterclusterProfilercodetoolscolorspacecowplotcpp11crayonCubistcurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsdiagramdigestdoParalleldoRNGDOSEdownloaderdplyrdynamicTreeCute1071ellipsisenrichplotevaluatefansifarverfastclusterfastmapfastmatchfgseafilelockfontawesomeforeachforeignformatRFormulafsfutile.loggerfutile.optionsfuturefuture.applygdatagenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicFeaturesGenomicRangesGEOqueryggforceggfunggnewscaleggplot2ggplotifyggraphggrepelggtreeglmnetglobalsglueGO.dbGOSemSimgowergplotsgraphgraphitegraphlayoutsgridExtragridGraphicsgsongtablegtoolshardhatHDF5ArrayHDO.dbhighrHmischmsHomo.sapienshtmlTablehtmltoolshtmlwidgetshttrhttr2igraphilluminaioimputeinumipredIRangesisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlatticelavalazyevallibcoinlifecyclelimmalistenvlocfitlubridatemagrittrMASSMatrixMatrixGenericsmatrixStatsmclustmemoisemgcvmimeminfiModelMetricsmulttestmunsellmvtnormnlmennetnor1mixnumDerivopensslopenxlsxorg.Hs.eg.dbOrganismDbiparallellypartykitpatchworkpheatmapPigengenepillarpkgconfigplogrplyrpngpolyclippreprocessCoreprettyunitspROCprodlimprogressprogressrproxypurrrquadprogqvalueR.methodsS3R.ooR.utilsR6rappdirsRBGLRColorBrewerRcppRcppArmadilloRcppEigenRcppGSLRcppParallelRcppZigguratRCurlreactome.dbReactomePAreadrrecipesreshapereshape2restfulrRfastRgraphvizrhdf5rhdf5filtersRhdf5libRhtslibrjsonrlangrmarkdownrngtoolsrpartRsamtoolsRSQLiterstudioapirtracklayerS4ArraysS4VectorssassscalesscatterpiescrimeshadowtextshapesiggenessnowSparseArraysparseMatrixStatsSQUAREMstatmodstringistringrSummarizedExperimentsurvivalsyssystemfontstibbletidygraphtidyrtidyselecttidytreetimechangetimeDatetinytextreeiotweenrTxDb.Hsapiens.UCSC.hg19.knownGenetxdbmakertzdbUCSC.utilsutf8vctrsviridisviridisLitevroomWGCNAwithrxfunXMLxml2xtableXVectoryamlyulab.utilszipzlibbioc

iNETgrate: Integrating gene expression and DNA methylation data in a gene network

Rendered fromiNETgrate_inference.Rnwusingknitr::knitron Jun 13 2024.

Last update: 2023-06-27
Started: 2023-03-24

Readme and manuals

Help Manual

Help pageTopics
Integrates DNA methylation data with gene expression in a single gene networkiNETgrate-package
Accelerated Failure AnalysisaccelFailAnalysis
Survival analysisanalyzeSurvival
Identifies the bestInetgratorbestInetgrator
Cleans and preprocesses datacleanAllData
Compute eigengenes of combined modules.computEigengenes computEigengloci rename
Computes an eigenloci for each genecomputEigenloci
Computes an inetgratorcomputeInetgrator
Computes union gene setcomputeUnion
Cox analysiscoxAnalysis
Mapping one locus to one gene.createLocusGene
Computes distance of loci to the closest TSSdistanceToTss
Download and save TCGA datadownloaData
Selects input genes for iNETgrate analysis.electGenes
Filters out genes or locifilterLowCor
Find Alive CutofffindAliveCutoff
Finds the most connected cluster of pointsfindCore
Identify and remove duplicate samplesfindTcgaDuplicates
iNETgrate - Runs entire iNETgrate pipeline.iNETgrate
Infers features for the test(validation) datasetinferEigengenes
Make networkmakeNetwork
Survival (Kaplan-Meier estimator) plotsplotKM
Plot number of loci per gene.plotLociNum
Plots distance of loci to genesplotLociTss
Prepare survival dataprepareSurvival
Cleans DNA methylation datapreprocessDnam
Maps sample IDs to corresponding patient IDssample2pat
Sample DatasampleData
A subset of cleaned TCGA-LAML datatoyCleanedAml
A subset of weighted DNA methylation profile of TCGA-LAML datatoyComputEloci
A subset of weighted average of gene expression present in each moduletoyEigengenes
A subset of TCGA-LAML datatoyRawAml