Package: epiregulon 2.3.2

Xiaosai Yao

epiregulon: Gene regulatory network inference from single cell epigenomic data

Gene regulatory networks model the underlying gene regulation hierarchies that drive gene expression and observed phenotypes. Epiregulon infers TF activity in single cells by constructing a gene regulatory network (regulons). This is achieved through integration of scATAC-seq and scRNA-seq data and incorporation of public bulk TF ChIP-seq data. Links between regulatory elements and their target genes are established by computing correlations between chromatin accessibility and gene expressions.

Authors:Xiaosai Yao [aut, cre], Tomasz Włodarczyk [aut], Aaron Lun [aut], Shang-Yang Chen [aut]

epiregulon_2.3.2.tar.gz
epiregulon_2.3.2.zip(r-4.7)epiregulon_2.3.2.zip(r-4.6)epiregulon_2.3.2.zip(r-4.5)
epiregulon_2.3.2.tgz(r-4.6-x86_64)epiregulon_2.3.2.tgz(r-4.6-arm64)epiregulon_2.3.2.tgz(r-4.5-x86_64)epiregulon_2.3.2.tgz(r-4.5-arm64)
epiregulon_2.3.2.tar.gz(r-4.7-arm64)epiregulon_2.3.2.tar.gz(r-4.7-x86_64)epiregulon_2.3.2.tar.gz(r-4.6-arm64)epiregulon_2.3.2.tar.gz(r-4.6-x86_64)
epiregulon_2.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
epiregulon/json (API)
NEWS

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

Bug tracker:https://github.com/xiaosaiyao/epiregulon/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On BioConductor:epiregulon-2.3.1(bioc 3.24)epiregulon-2.2.0(bioc 3.23)

singlecellgeneregulationnetworkinferencenetworkgeneexpressiontranscriptiongenetargetcpp

6.70 score 28 stars 30 scripts 306 downloads 11 exports 114 dependencies

Last updated from:4d04502f71. Checks:1 NOTE, 8 WARNING, 2 OK, 3 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE400
linux-devel-arm64WARNING1076
linux-devel-x86_64WARNING1007
source / vignettesOK883
linux-release-arm64WARNING1151
linux-release-x86_64WARNING990
macos-release-arm64WARNING573
macos-release-x86_64ERROR1655
macos-oldrel-arm64ERROR553
macos-oldrel-x86_64ERROR1194
windows-develWARNING2088
windows-releaseWARNING1710
windows-oldrelWARNING2613
wasm-releaseOK388

Exports:addLogFCaddMotifScoreaddTFMotifInfoaddWeightsaggregateAcrossCellsFastcalculateActivitycalculateP2GgetRegulongetTFMotifInfooptimizeMetacellNumberpruneRegulon

Dependencies:abindAnnotationDbiAnnotationHubaskpassassortheadbackportsbeachmatBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocIObiocmakeBiocManagerBiocNeighborsBiocParallelBiocVersionBiostringsbitbit64bitopsblobBSgenomeBSgenome.Hsapiens.UCSC.hg19BSgenome.Hsapiens.UCSC.hg38BSgenome.Mmusculus.UCSC.mm10cachemcaToolscheckmatecigarilloclicodetoolscpp11crayoncurlDBIdbplyrDelayedArraydir.expiryDirichletMultinomialdplyrentropyExperimentHubfastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomicAlignmentsGenomicRangesgluegtoolshttrhttr2IRangesjsonliteKEGGRESTlambda.rlatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatsmemoisemetapodmimemotifmatchropensslpillarpkgconfigpngpurrrpwalignR6rappdirsRcppRcppArmadilloRCurlrestfulrRhtslibRigraphlibrjsonrlangRsamtoolsRSQLitertracklayerS4ArraysS4VectorsscrapperSeqinfoseqLogoSingleCellExperimentsnowSparseArraystringistringrSummarizedExperimentsysTFBSToolsTFMPvaluetibbletidyrtidyselectUCSC.utilsutf8vctrswithrXMLXVectoryaml

Epiregulon tutorial with MultiAssayExperiment

Rendered frommultiome.mae.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2026-05-26
Started: 2022-09-12