Package: SingleCellSignalR 2.3.0

Jean-Philippe Villemin

SingleCellSignalR: Cell Signalling Using Single-Cell RNA-seq or Proteomics Data

Inference of ligand-receptor (L-R) interactions from single-cell expression (transcriptomics/proteomics) data. SingleCellSignalR v2 inferences rely on the statistical model we introduced in the BulkSignalR package as well as the original SingleCellSignalR LR-score (both are available). SingleCellSignalR v2 can be regarded as a wrapper to BulkSignalR fundamental classes. This also enables v2 users to work with any species, whereas only Mus musculus & Homo sapiens were available before in SingleCellSignalR v1.

Authors:Jacques Colinge [aut], Jean-Philippe Villemin [cre]

SingleCellSignalR_2.3.0.tar.gz
SingleCellSignalR_2.3.0.zip(r-4.7)SingleCellSignalR_2.3.0.zip(r-4.6)SingleCellSignalR_2.3.0.zip(r-4.5)
SingleCellSignalR_2.3.0.tgz(r-4.6-any)SingleCellSignalR_2.3.0.tgz(r-4.5-any)
SingleCellSignalR_2.3.0.tar.gz(r-4.7-any)SingleCellSignalR_2.3.0.tar.gz(r-4.6-any)
SingleCellSignalR_2.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SingleCellSignalR/json (API)
NEWS

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

Bug tracker:https://github.com/jcolinge/singlecellsignalr/issues

Datasets:

On BioConductor:SingleCellSignalR-2.3.0(bioc 3.24)SingleCellSignalR-2.2.0(bioc 3.23)

networkrnaseqsoftwareproteomicstranscriptomicssinglecellnetworkinference

6.56 score 1 stars 49 scripts 571 downloads 7 mentions 12 exports 194 dependencies

Last updated from:8b72731b79. Checks:1 NOTE, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksNOTE235
linux-devel-x86_64OK495
source / vignettesOK293
linux-release-x86_64OK493
macos-release-arm64OK309
macos-oldrel-arm64OK355
windows-develOK407
windows-releaseOK387
windows-oldrelOK350
wasm-releaseOK184

Exports:autocrinesbsrdmCompcellNetBubblePlotcellNetHeatmapgetAutocrinesgetParacrinesinfParamSCparacrinesperformInferencespopulationsSCSRNetSCSRNoNet

Dependencies:abindapeaplotaskpassbabelgenebackportsbase64encBiobaseBiocFileCacheBiocGenericsbitbit64bitopsblobbootbroombslibBulkSignalRcachemcarcarDatacirclizeclicliprclueclustercodetoolscolorspaceComplexHeatmapcorrplotcowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArrayDerivdigestdoBydoParalleldplyrevaluatefarverfastmapfilelockfontawesomefontBitstreamVerafontLiberationfontquiverforeachforecastFormulafracdifffsgdtoolsgenericsGenomicRangesGetoptLongggalluvialggfunggiraphggplot2ggplotifyggpubrggrepelggsciggsignifggtreeglmnetGlobalOptionsgluegprofiler2gridExtragridGraphicsgtablehighrhmshomologenehtmltoolshtmlwidgetshttrhttr2igraphIRangesisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelme4lmtestmagickmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmatrixTestsmemoisemgcvmicrobenchmarkmimeminqamodelrmulttestnlmenloptrnnetnumDerivopensslorthogeneotelpatchworkpbkrtestpillarpkgconfigplotlyplyrpngpolynomprettyunitsprogresspromisespurrrquantregR.cacheR.methodsS3R.ooR.utilsR6RANNrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRCurlRdpackreadrreformulasrepmisrjsonrlangrmarkdownRSQLiterstatixRtsneS4ArraysS4VectorsS7sassscalesSeqinfoshapeSingleCellExperimentSparseArraySparseMSpatialExperimentstablediststringistringrSummarizedExperimentsurvivalsyssystemfontstibbletidyrtidyselecttidytreetimeDatetinytextreeiotzdburcautf8vctrsviridisLitevroomwithrxfunXVectoryamlyulab.utilszoo

SingleCellSignalR : Inference of ligand-receptor interactions from single-cell data

Jacques Colinge, Jean-Philippe Villemin

Rendered fromSingleCellSignalR-Main.Rmdusingknitr::rmarkdownon May 30 2026.

Last update: 2026-04-16
Started: 2025-09-28

Readme and manuals

Help Manual

Help pageTopics
autocrines accessorautocrines autocrines,SCSRNet-method autocrines,SCSRNoNet-method
BSRDataModelComp object accessorbsrdmComp bsrdmComp,SCSRNet-method bsrdmComp,SCSRNoNet-method
Overview of cellular networks with a bubble plotcellNetBubblePlot
Heatmap overview of cellular networkscellNetHeatmap
An example of single-cell RNA-seq data setexample_dataset
Method to retrieve autocrine interactionsgetAutocrines getAutocrines,SCSRNet-method getAutocrines,SCSRNoNet-method
Method to retrieve paracrine interactionsgetParacrines getParacrines,SCSRNet-method getParacrines,SCSRNoNet-method
Inference parameters accessorinfParamSC infParamSC,SCSRNet-method infParamSC,SCSRNoNet-method
paracrines accessorparacrines paracrines,SCSRNet-method paracrines,SCSRNoNet-method
Inference of ligand-receptor interactions based on regulationperformInferences performInferences,SCSRNet-method performInferences,SCSRNoNet-method
populations accessorpopulations populations,SCSRNet-method populations,SCSRNoNet-method
Instantiate a SCSRNet object from expression dataSCSRNet
SingleCellSignalR cellular network objectSCSRNet-class
Prepare a SCSRNoNet object from expression dataSCSRNoNet
SingleCellSignalR no network objectSCSRNoNet-class