Package: scTensor 2.17.0
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:
scTensor_2.17.0.tar.gz
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scTensor.pdf |scTensor.html✨
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-2.17.0(bioc 3.21)scTensor-2.16.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
dimensionreductionsinglecellsoftwaregeneexpression
Last updated 23 days agofrom:dceaf02b39. Checks:OK: 1 WARNING: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | WARNING | Oct 31 2024 |
| R-4.5-linux | WARNING | Oct 31 2024 |
| R-4.4-win | WARNING | Oct 31 2024 |
| R-4.4-mac | WARNING | Oct 31 2024 |
| R-4.3-win | WARNING | Oct 31 2024 |
| R-4.3-mac | WARNING | Oct 31 2024 |
Exports:cellCellDecompcellCellRankscellCellReportcellCellSettingcellCellSimulategetParamnewCCSParamssetParam<-
Dependencies:abindannotateAnnotationDbiAnnotationForgeAnnotationHubapeaplotaskpassassertthatbackportsbase64encBHBiobaseBiocFileCacheBiocGenericsBiocManagerBiocParallelBiocStyleBiocVersionBiostringsbitbit64bitopsblobbookdownbslibcacachemcallrCategoryccTensorcheckmateclassclassIntcliclustercodetoolscolorspacecommonmarkconcavemancowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArraydendextenddigestDOSEdotCall64dplyre1071eggenrichplotentropyevaluatefansifarverfastmapfastmatchfdrtoolfgseafieldsfilelockfontawesomeforeachformatRfsfutile.loggerfutile.optionsgclusgenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggforceggfunggnewscaleggplot2ggplotifyggraphggrepelggtangleggtreeglueGO.dbGOSemSimGOstatsgraphgraphitegraphlayoutsgridExtragridGraphicsGSEABasegsongtableheatmaplyhexbinhighrhtmltoolshtmlwidgetshttrigraphIRangesisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelazyevallifecyclemagrittrmapsmarkdownMASSMatrixMatrixGenericsmatrixStatsmemoiseMeSHDbimeshrmgcvmimemisc3dmunsellnlmennTensoropenssloutlierspatchworkpermutepillarpkgconfigplogrplot3DplotlyplotrixplyrpngpolyclipprocessxpromisesproxypspurrrqapqvalueR.methodsS3R.ooR.utilsR6rappdirsRBGLRColorBrewerRcppRcppArmadilloRcppEigenRCurlreactome.dbReactomePAregistryreshape2RgraphvizrlangrmarkdownRSQLiterTensors2S4ArraysS4VectorssassscalesscatterpieschexseriationsfSingleCellExperimentsnowspamSparseArraystringistringrSummarizedExperimentsurvivalsyssystemfontstagcloudtibbletidygraphtidyrtidyselecttidytreetinytextreeioTSPtweenrUCSC.utilsunitsutf8V8vctrsveganviridisviridisLitevisNetworkwebshotwithrwkxfunXMLxtableXVectoryamlyulab.utilszlibbioc
Detection and visualization of cell-cell interactions using LRBase and scTensor
Rendered fromscTensor.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2021-12-16
Started: 2018-06-27
Roadmap to prepare the input matrix for scTensor
Rendered fromscTensor_1_Data_format_ID_Conversion.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2021-10-18
Started: 2019-06-19
How to interpret the HTML report generated by cellCellReport function
Rendered fromscTensor_2_Report_Interpretation.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2020-09-15
Started: 2019-06-19
How to perform CCI simulation by cellCellSimulate function
Rendered fromscTensor_3_CCI_Simulation.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2020-09-15
Started: 2019-06-19
How to reanalyze the results of scTensor
Rendered fromscTensor_4_Reanalysis.Rmdusingknitr::rmarkdownon Oct 31 2024.Last update: 2021-10-18
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 |
