Package: RegEnrich 1.15.0
RegEnrich: Gene regulator enrichment analysis
This package is a pipeline to identify the key gene regulators in a biological process, for example in cell differentiation and in cell development after stimulation. There are four major steps in this pipeline: (1) differential expression analysis; (2) regulator-target network inference; (3) enrichment analysis; and (4) regulators scoring and ranking.
Authors:
RegEnrich_1.15.0.tar.gz
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RegEnrich.pdf |RegEnrich.html✨
RegEnrich/json (API)
NEWS
# Install 'RegEnrich' in R: |
install.packages('RegEnrich', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- Lyme_GSE63085 - Example RNAseq dataset [Human]
- TFs - Human gene regulators
On BioConductor:RegEnrich-1.15.0(bioc 3.20)RegEnrich-1.14.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:bba0b4e15f
Exports:%>%getResultsNamesheadnewDeaSetnewScorenewTopNetworkplot_EnrichplotOrdersplotRegTarExprplotSoftPowerregenrich_diffExprregenrich_enrichregenrich_networkregenrich_network<-regenrich_rankScoreRegenrichSetresults_DEAresults_enrichresults_exprresults_scoreresults_topNetshowtail
Dependencies:abindAnnotationDbiaskpassbackportsbase64encBHBiobaseBiocGenericsBiocIOBiocManagerBiocParallelBiocSetBiocStyleBiostringsbitbit64blobbookdownbslibcachemcheckmatecliclustercodetoolscolorspacecowplotcpp11crayoncurldata.tableDBIDelayedArrayDESeq2digestdoParallelDOSEdplyrdynamicTreeCutevaluatefansifarverfastclusterfastmapfastmatchfgseafontawesomeforeachforeignformatRFormulafsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2glueGO.dbGOSemSimgridExtragtableHDO.dbhighrHmischtmlTablehtmltoolshtmlwidgetshttrimputeIRangesisobanditeratorsjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmennetontologyIndexopensslpillarpkgconfigplogrplyrpngpreprocessCorepurrrqvalueR6randomForestrappdirsRColorBrewerRcppRcppArmadilloreshape2rlangrmarkdownrpartRSQLiterstudioapiS4ArraysS4VectorssassscalessnowSparseArraystatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttinytexUCSC.utilsutf8vctrsviridisviridisLiteWGCNAwithrxfunXVectoryamlyulab.utilszlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
DeaSet class | DeaSet-class |
dimention of `TopNetwork` object | dim,TopNetwork-method |
Enrich class | Enrich-class |
Inference the name of results of DESeq analysis by a formula (or model matrix) and sample information | getResultsNames |
head or tail of Score object | head,Score-method tail,Score-method |
Example RNAseq dataset [Human] | Lyme_GSE63085 |
DeaSet object creator | newDeaSet |
TopNetwork object creator | newTopNetwork |
Plot results of FET/GSEA enrichment analysis | plot_Enrich plot_Enrich,RegenrichSet-method |
Compare the orders of two vectors | plotOrders |
Plot regulator and its targets expression | plotRegTarExpr |
Plot soft power for WGCNA analysis | plotSoftPower |
Print Score object | print.Score |
Differential expression analysis step | regenrich_diffExpr regenrich_diffExpr,RegenrichSet-method |
Enrichment analysis step | regenrich_enrich regenrich_enrich,RegenrichSet-method |
Regulator-target network inference step | regenrich_network regenrich_network,RegenrichSet-method regenrich_network<- regenrich_network<-,RegenrichSet,data.frame-method regenrich_network<-,RegenrichSet,TopNetwork-method |
Regulator scoring and ranking | regenrich_rankScore regenrich_rankScore,RegenrichSet-method |
RegenrichSet object creator | RegenrichSet |
RegenrichSet class | RegenrichSet-class |
Result accessor functions | results_DEA results_enrich results_expr results_score results_topNet |
Score class | newScore Score-class |
methods of generic function "show" | show,DeaSet-method show,Enrich-method show,RegenrichSet-method show,Score-method show,TopNetwork-method |
Human gene regulators | TFs |
TopNetwork class | TopNetwork-class |