Package: scTensor 2.23.0
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:
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)
scTensor_2.23.0.tar.gz(r-4.7-any)scTensor_2.23.0.tar.gz(r-4.6-any)
scTensor_2.23.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
scTensor/json (API)
NEWS
| # Install 'scTensor' in R: |
| install.packages('scTensor', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- 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
Last updated from:8da1a464dc. Checks:1 ERROR, 7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 441 | ||
| linux-devel-x86_64 | WARNING | 726 | ||
| source / vignettes | OK | 531 | ||
| linux-release-x86_64 | WARNING | 717 | ||
| macos-release-arm64 | WARNING | 406 | ||
| macos-oldrel-arm64 | WARNING | 282 | ||
| windows-devel | WARNING | 1130 | ||
| windows-release | WARNING | 715 | ||
| windows-oldrel | WARNING | 1089 | ||
| wasm-release | OK | 381 |
Exports:cellCellDecompcellCellRankscellCellReportcellCellSettingcellCellSimulategetParamnewCCSParamssetParam<-
Dependencies:abindannotateAnnotationDbiAnnotationForgeAnnotationHubapeaplotaskpassassertthatbackportsbase64encBHBiobaseBiocBaseUtilsBiocFileCacheBiocGenericsBiocManagerBiocStyleBiocVersionBiostringsbitbit64bitopsblobbookdownbslibcacachemcallrCategoryccTensorcheckmateclassclassIntcliclustercodetoolscolorspacecommonmarkconcavemancpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArraydendextenddigestdir.expiryDOSEdotCall64dplyre1071eggenrichitenrichplotentropyevaluatefarverfastmapfdrtoolfieldsfilelockfontawesomefontBitstreamVerafontLiberationfontquiverforeachfsgclusgdtoolsgenefiltergenericsGenomicRangesggforceggfunggiraphggnewscaleggplot2ggplotifyggraphggrepelggtangleggtreeglueGO.dbGOSemSimGOstatsgraphgraphitegraphlayoutsgridExtragridGraphicsGSEABasegsongtableheatmaplyhexbinhighrhtmltoolshtmlwidgetshttrhttr2igraphIRangesisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglaterlatticelazyevallifecyclelitedownmagrittrmapsmarkdownMASSMatrixMatrixGenericsmatrixStatsmemoiseMeSHDbimeshrmgcvmimemisc3dnlmennTensoropenssloteloutlierspatchworkpermutepillarpkgconfigplot3DplotlyplotrixplyrpngpolyclipprocessxpromisesproxypspurrrqapR6RANNrappdirsRBGLRColorBrewerRcppRcppArmadilloRcppEigenRCurlreactome.dbReactomePAregistryreshape2RgraphvizrlangrmarkdownRSpectraRSQLiterTensors2S4ArraysS4VectorsS7sassscalesscatterpieschexSeqinfoseriationsfSingleCellExperimentspamSparseArraystringistringrSummarizedExperimentsurvivalsyssystemfontstagcloudtibbletidydrtidygraphtidyrtidyselecttidytreetinytextreeioTSPtweenrunitsutf8V8vctrsveganVicusviridisviridisLitevisNetworkwebshotwithrwkxfunXMLxtableXVectoryamlyulab.utils
Detection and visualization of cell-cell interactions using LRBase and scTensor
Rendered fromscTensor.Rmdusingknitr::rmarkdownon May 30 2026.Last update: 2025-06-19
Started: 2018-06-27
Roadmap to prepare the input matrix for scTensor
Rendered fromscTensor_1_Data_format_ID_Conversion.Rmdusingknitr::rmarkdownon May 30 2026.Last update: 2025-05-23
Started: 2019-06-19
How to interpret the HTML report generated by cellCellReport function
Rendered fromscTensor_2_Report_Interpretation.Rmdusingknitr::rmarkdownon May 30 2026.Last update: 2020-09-15
Started: 2019-06-19
How to perform CCI simulation by cellCellSimulate function
Rendered fromscTensor_3_CCI_Simulation.Rmdusingknitr::rmarkdownon May 30 2026.Last update: 2020-09-15
Started: 2019-06-19
How to reanalyze the results of scTensor
Rendered fromscTensor_4_Reanalysis.Rmdusingknitr::rmarkdownon May 30 2026.Last update: 2025-05-23
Started: 2019-10-23
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition | scTensor-package scTensor |
| Class "CCSParams" | CCSParams-class |
| Performing scTensor | cellCellDecomp cellCellDecomp,SingleCellExperiment-method |
| Rank estimation of the CCI-tensor | cellCellRanks cellCellRanks,SingleCellExperiment-method |
| HTML report of the result of scTensor | cellCellReport cellCellReport,SingleCellExperiment-method |
| Parameter setting for scTensor | cellCellSetting cellCellSetting,SingleCellExperiment-method |
| Parameter Simulate for scTensor | cellCellSimulate cellCellSimulate,SingleCellExperiment-method |
| The matrix which is used as test data of scTensor. | GermMale |
| Get a parameter | getParam getParam,CCSParams-method |
| The vector contains the celltype information and color scheme of GermMale | labelGermMale |
| The gene-wise mean vector of Quartz-Seq data. | m |
| New Params | newCCSParams |
| Set a parameter | setParam setParam,CCSParams,ANY-method setParam,CCSParams-method setParam<- setParam<-,CCSParams,ANY-method setParam<-,CCSParams-method |
| The result of Rtsne against GermMale | tsneGermMale |
| The gene-wise variance vector of Quartz-Seq data. | v |
