Package: RegEnrich 1.22.1

Weiyang Tao

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:Weiyang Tao [cre, aut], Aridaman Pandit [aut]

RegEnrich_1.22.1.tar.gz
RegEnrich_1.22.1.zip(r-4.7)RegEnrich_1.22.1.zip(r-4.6)RegEnrich_1.22.1.zip(r-4.5)
RegEnrich_1.22.1.tgz(r-4.6-any)RegEnrich_1.22.1.tgz(r-4.5-any)
RegEnrich_1.22.1.tar.gz(r-4.7-any)RegEnrich_1.22.1.tar.gz(r-4.6-any)
RegEnrich_1.22.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
RegEnrich/json (API)
NEWS

# Install 'RegEnrich' in R:

install.packages('RegEnrich', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

Lyme_GSE63085 - Example RNAseq dataset [Human]
TFs - Human gene regulators

On BioConductor:RegEnrich-1.23.1(bioc 3.24)RegEnrich-1.22.1(bioc 3.23)

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

geneexpression transcriptomics rnaseq twochannel transcription genetarget networkenrichment differentialexpression network networkinference genesetenrichment functionalprediction

4.05 score 28 scripts 384 downloads 1 mentions 23 exports 137 dependencies

Last updated from:ada7c3725a (on RELEASE_3_23). Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: no.

Target	Result	Time
bioc-checks	ERROR	234
linux-devel-x86_64	NOTE	533
source / vignettes	OK	377
linux-release-x86_64	NOTE	434
macos-release-arm64	NOTE	284
macos-oldrel-arm64	NOTE	286
windows-devel	NOTE	331
windows-release	NOTE	351
windows-oldrel	NOTE	435
wasm-release	OK	207

Exports:%>%getResultsNames head newDeaSet newScore newTopNetwork plot_Enrich plotOrders plotRegTarExpr plotSoftPower regenrich_diffExpr regenrich_enrich regenrich_network regenrich_network<-regenrich_rankScore RegenrichSet results_DEA results_enrich results_expr results_score results_topNet show tail

Dependencies:abind AnnotationDbi askpass backports base64enc BH Biobase BiocGenerics BiocIO BiocManager BiocParallel BiocSet BiocStyle Biostrings bit bit64 blob bookdown bslib cachem checkmate cli cluster codetools colorspace cowplot cpp11 crayon curl data.table DBI DelayedArray DESeq2 digest doParallel DOSE dplyr dynamicTreeCut enrichit evaluate farver fastcluster fastmap fastmatch fgsea fontawesome foreach foreign formatR Formula fs futile.logger futile.options generics GenomicRanges ggplot2 glue GO.db GOSemSim gridExtra gson gtable highr Hmisc htmlTable htmltools htmlwidgets httr impute IRanges isoband iterators jquerylib jsonlite KEGGREST knitr labeling lambda.r lattice lifecycle limma locfit magrittr Matrix MatrixGenerics matrixStats memoise mime nnet ontologyIndex openssl pillar pkgconfig plyr png preprocessCore purrr qvalue R6 randomForest rappdirs RColorBrewer Rcpp RcppArmadillo reshape2 rlang rmarkdown rpart RSQLite rstudioapi S4Arrays S4Vectors S7 sass scales Seqinfo snow SparseArray statmod stringi stringr SummarizedExperiment survival sys tibble tidyr tidyselect tinytex utf8 vctrs viridisLite WGCNA withr xfun XVector yaml yulab.utils

RegEnrich: an R package for gene regulator enrichment analysis

Weiyang Tao, Aridaman Pandit

Rendered fromRegEnrich.Rmdusingknitr::rmarkdownon Jun 11 2026.

Last update: 2020-07-21
Started: 2020-03-07

Citation

Development and contributors

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