Package: scTensor 2.23.0

Koki Tsuyuzaki

scTensor: Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition

The algorithm is based on the non-negative tucker decomposition (NTD2) of nnTensor.

Authors:Koki Tsuyuzaki [aut, cre], Kozo Nishida [aut]

scTensor_2.23.0.tar.gz
scTensor_2.23.0.zip(r-4.7)scTensor_2.23.0.zip(r-4.6)scTensor_2.23.0.zip(r-4.5)
scTensor_2.23.0.tgz(r-4.6-any)scTensor_2.23.0.tgz(r-4.5-any)
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scTensor_2.23.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
scTensor/json (API)

# Install 'scTensor' in R:
install.packages('scTensor', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • GermMale - The matrix which is used as test data of scTensor.
  • labelGermMale - The vector contains the celltype information and color scheme of GermMale
  • m - The gene-wise mean vector of Quartz-Seq data.
  • tsneGermMale - The result of Rtsne against GermMale
  • v - The gene-wise variance vector of Quartz-Seq data.

On BioConductor:scTensor-2.23.0(bioc 3.24)scTensor-2.22.0(bioc 3.23)

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

dimensionreductionsinglecellsoftwaregeneexpression

4.00 score 2 scripts 1 mentions 8 exports 222 dependencies

Last updated from:8da1a464dc. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksERROR391
linux-devel-x86_64WARNING706
source / vignettesOK731
linux-release-x86_64WARNING673
macos-release-arm64WARNING327
macos-oldrel-arm64WARNING335
windows-develWARNING743
windows-releaseWARNING731
windows-oldrelWARNING847
wasm-releaseOK414

Exports:cellCellDecompcellCellRankscellCellReportcellCellSettingcellCellSimulategetParamnewCCSParamssetParam<-

Dependencies:abindannotateAnnotationDbiAnnotationForgeAnnotationHubapeaplotaskpassassertthatbackportsbase64encBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocManagerBiocStyleBiocVersionBiostringsbitbit64bitopsblobbookdownbslibcacachemcallrCategoryccTensorcheckmateclassclassIntcliclustercodetoolscolorspacecommonmarkconcavemancpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArraydendextenddigestdir.expiryDOSEdotCall64dplyre1071eggenrichitenrichplotentropyevaluatefarverfastmapfdrtoolfieldsfilelockfontawesomefontBitstreamVerafontLiberationfontquiverforeachfsgclusgdtoolsgenefiltergenericsGenomicRangesggforceggfunggiraphggnewscaleggplot2ggplotifyggraphggrepelggtangleggtreeglueGO.dbGOSemSimGOstatsgraphgraphitegraphlayoutsgridExtragridGraphicsGSEABasegsongtableheatmaplyhexbinhighrhtmltoolshtmlwidgetshttrhttr2igraphIRangesisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglaterlatticelazyevallifecyclelitedownmagrittrmapsmarkdownMASSMatrixMatrixGenericsmatrixStatsmemoiseMeSHDbimeshrmgcvmimemisc3dnlmennTensoropenssloteloutlierspatchworkpermutepillarpkgconfigplot3DplotlyplotrixplyrpngpolyclipprocessxpromisesproxypspurrrqapR6RANNrappdirsRBGLRColorBrewerRcppRcppArmadilloRcppEigenRCurlreactome.dbReactomePAregistryreshape2RgraphvizrlangrmarkdownRSpectraRSQLiterTensors2S4ArraysS4VectorsS7sassscalesscatterpieschexSeqinfoseriationsfSingleCellExperimentspamSparseArraystringistringrSummarizedExperimentsurvivalsyssystemfontstagcloudtibbletidydrtidygraphtidyrtidyselecttidytreetinytextreeioTSPtweenrunitsutf8V8vctrsveganVicusviridisviridisLitevisNetworkwebshotwithrwkxfunXMLxtableXVectoryamlyulab.utils

Detection and visualization of cell-cell interactions using LRBase and scTensor
Specification change of LRBase and scTensor from BioC 3.14 (Nov. 2021) | Introduction | About Cell-Cell Interaction (CCI) databases | LRBase and scTensor framework | Usage | LRBase objects (ligand-receptor database for 134 organisms) | Data retrieval from AnnotationHub | columns, keytypes, keys, and select | Other functions | scTensor (CCI-tensor construction, decomposition, and HTML reporting) | Creating a SingleCellExperiment object | Parameter setting: cellCellSetting | CCI-tensor construction and decomposition: cellCellDecomp | HTML Report: cellCellReport | Session Information

Last update: 2025-06-19
Started: 2018-06-27

Roadmap to prepare the input matrix for scTensor
Introduction | Step.1: Create a gene-level expression matrix | Case I: Gene-level quantification | Case II: Transcript-level quantification | Case III: UMI-count | Step.2: Convert the row names of a matrix as NCBI Gene ID (ENTREZID) | Case I: Ensembl Gene ID to NCBI Gene ID | Case II: Gene Symbol to NCBI Gene ID | Step.3: Normalize the count matrix | Session information

Last update: 2025-05-23
Started: 2019-06-19

How to reanalyze the results of scTensor
Summary of the output objects of scTensor | Execution of scTensor with the different options | Session information

Last update: 2025-05-23
Started: 2019-10-23

How to interpret the HTML report generated by cellCellReport function
Introduction | Interpretation of "1. About scTensor Algorithm" | Interpretation of "2. Global statistics and plots" | Interpretation of "3. Ligand-Cell Patterns" | Interpretation of "4. Receptor-Cell Patterns" | Interpretation of "5. CCI-wise Hypergraph" | Interpretation of "6. Gene-wise Hypergraph" | Interpretation of "7. (Ligand-Cell, Receptor-Cell, LR-pair) Patterns" | Session information

Last update: 2020-09-15
Started: 2019-06-19

How to perform CCI simulation by cellCellSimulate function
Introduction | Session information

Last update: 2020-09-15
Started: 2019-06-19

Readme and manuals

Help Manual

Help pageTopics
Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decompositionscTensor-package scTensor
Class "CCSParams"CCSParams-class
Performing scTensorcellCellDecomp cellCellDecomp,SingleCellExperiment-method
Rank estimation of the CCI-tensorcellCellRanks cellCellRanks,SingleCellExperiment-method
HTML report of the result of scTensorcellCellReport cellCellReport,SingleCellExperiment-method
Parameter setting for scTensorcellCellSetting cellCellSetting,SingleCellExperiment-method
Parameter Simulate for scTensorcellCellSimulate cellCellSimulate,SingleCellExperiment-method
The matrix which is used as test data of scTensor.GermMale
Get a parametergetParam getParam,CCSParams-method
The vector contains the celltype information and color scheme of GermMalelabelGermMale
The gene-wise mean vector of Quartz-Seq data.m
New ParamsnewCCSParams
Set a parametersetParam setParam,CCSParams,ANY-method setParam,CCSParams-method setParam<- setParam<-,CCSParams,ANY-method setParam<-,CCSParams-method
The result of Rtsne against GermMaletsneGermMale
The gene-wise variance vector of Quartz-Seq data.v