Package: RegionalST 1.3.0

Ziyi Li

RegionalST: Investigating regions of interest and performing cross-regional analysis with spatial transcriptomics data

This package analyze spatial transcriptomics data through cross-regional analysis. It selects regions of interest (ROIs) and identifys cross-regional cell type-specific differential signals. The ROIs can be selected using automatic algorithm or through manual selection. It facilitates manual selection of ROIs using a shiny application.

Authors:Ziyi Li [aut, cre]

RegionalST_1.3.0.tar.gz
RegionalST_1.3.0.zip(r-4.5)RegionalST_1.3.0.zip(r-4.4)RegionalST_1.3.0.zip(r-4.3)
RegionalST_1.3.0.tgz(r-4.4-any)RegionalST_1.3.0.tgz(r-4.3-any)
RegionalST_1.3.0.tar.gz(r-4.5-noble)RegionalST_1.3.0.tar.gz(r-4.4-noble)
RegionalST_1.3.0.tgz(r-4.4-emscripten)RegionalST_1.3.0.tgz(r-4.3-emscripten)
RegionalST.pdf |RegionalST.html
RegionalST/json (API)
NEWS

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

Peer review:

Datasets:

On BioConductor:RegionalST-1.3.0(bioc 3.20)RegionalST-1.2.0(bioc 3.19)

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

bioconductor-package

15 exports 0.71 score 247 dependencies

Last updated 2 months agofrom:889b990e85

Exports:DoGSEADrawDotplotDrawRegionProportionDrawRegionProportion_withPropFindRegionalCellsGetCrossRegionalDE_rawGetCrossRegionalDE_withPropGetOneRadiusEntropyGetOneRadiusEntropy_withPropgetProportionManualSelectCentermySpatialPreprocessPlotOneSelectedCenterRankCenterByEntropyRankCenterByEntropy_withProp

Dependencies:abindaskpassassertthatbackportsbase64encBayesSpacebeachmatbeeswarmBHBiobaseBiocFileCacheBiocGenericsBiocNeighborsBiocParallelBiocSingularbitbit64bitopsblobblusterbroombroom.helpersbslibcachemCairocaToolsclassclicliprclustercodacodetoolscolorspacecommonmarkcorpcorcowplotcpp11crayoncrosstalkcurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsdeldirdigestDirichletRegdoParalleldotCall64dplyrdqrnge1071edgeREpiDISHevaluatefansifarverfastDummiesfastmapfastmatchfgseafilelockfitdistrplusFNNfontawesomeforcatsforeachformatRFormulafsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesGGallyggbeeswarmggplot2ggrastrggrepelggridgesggstatsglobalsgluegoftestgplotsgridExtragtablegtoolshavenherehighrhmshtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglabelledlambda.rlaterlatticelazyevalleidenlifecyclelimmalistenvlmtestlocfdrlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmaxLikmclustmemoisemetapodmgcvmimeminiUImiscToolsmunsellnlmennlsopensslparallellypatchworkpbapplypheatmappillarpkgconfigplogrplotlyplyrpngpolyclipprettyunitsprogressprogressrpromisesproxypurrrquadprogR6raggRANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppDistRcppEigenRcppHNSWRcppMLRcppProgressRcppTOMLRCurlreadrreshape2reticulaterhdf5rhdf5filtersRhdf5librlangrmarkdownROCRrprojrootRSpectraRSQLitersvdRtsneS4ArraysS4VectorssandwichsassScaledMatrixscalesscaterscattermorescransctransformscuttleSeuratSeuratObjectshinySingleCellExperimentsitmosnowsourcetoolsspspamSparseArraysparseMatrixStatsspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.utilsstatmodstringistringrSummarizedExperimentsurvivalsyssystemfontstensortextshapingtibbletidyrtidyselecttinytexTOASTtzdbUCSC.utilsutf8uwotvctrsviporviridisviridisLitevroomwithrxfunxgboostxtableXVectoryamlzlibbioczoo

Understanding Intrasample Heterogeneity from ST data with RegionalST

Rendered fromRegionalST.Rmdusingknitr::rmarkdownon Jul 02 2024.

Last update: 2023-08-07
Started: 2023-05-02