Package: PRECAST 1.6.5

Wei Liu

PRECAST: Embedding and Clustering with Alignment for Spatial Datasets

An efficient data integration method is provided for multiple spatial transcriptomics data with non-cluster-relevant effects such as the complex batch effects. It unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, requiring only partially shared cell/domain clusters across datasets. More details can be referred to Wei Liu, et al. (2023) <doi:10.1038/s41467-023-35947-w>.

Authors:Wei Liu [aut, cre], Yi Yang [aut], Jin Liu [aut]

PRECAST_1.6.5.tar.gz
PRECAST_1.6.5.tar.gz(r-4.5-noble)PRECAST_1.6.5.tar.gz(r-4.4-noble)
PRECAST_1.6.5.tgz(r-4.4-emscripten)
PRECAST.pdf |PRECAST.html
PRECAST/json (API)

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

Peer review:

Bug tracker:https://github.com/feiyoung/precast/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

5.34 score 2 packages 73 scripts 339 downloads 28 exports 217 dependencies

Last updated 9 months agofrom:ca0b851412. Checks:OK: 1 WARNING: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-linux-x86_64WARNINGNov 15 2024

Exports:Add_embedAddAdjListAddParSettingAddTSNEAddUMAPboxPlotchooseColorscoordinate_rotateCreatePRECASTObjectdimPlotdoHeatmapdrawFigsfeaturePlotfirstupgetAdj_fixedNumbergetAdj_regICM.EMICM.EM_structureIntegrateSpaDatamodel_setplot_RGBplot_scatterPRECASTSelectModelSelectModel.PRECASTObjSelectModel.SeqK_PRECAST_ObjectSpaPlotvolinPlot

Dependencies:abindaskpassassortheadbackportsbase64encbeachmatbeeswarmBHBiobaseBiocGenericsBiocNeighborsBiocParallelBiocSingularbitopsbootbroombslibcachemCairocarcarDatacaToolscliclustercodetoolscolorspacecommonmarkCompQuadFormcorrplotcowplotcpp11crayoncrosstalkcurldata.tableDelayedArraydeldirDerivdigestdoBydotCall64dplyrdqrngDR.SCevaluatefansifarverfastDummiesfastmapfitdistrplusFNNfontawesomeformatRFormulafsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggbeeswarmggplot2ggpubrggrastrggrepelggridgesggsciggsignifggthemesGiRaFglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenlifecyclelistenvlme4lmtestmagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmclustmemoisemgcvmicrobenchmarkmimeminiUIminqamodelrmunsellnlmenloptrnnetnumDerivopensslparallellypatchworkpbapplypbkrtestpheatmappillarpkgconfigplotlyplyrpngpolyclippolynomprogressrpromisespurrrquantregR6raggRANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppMLRcppProgressRcppTOMLreshape2reticulaterlangrmarkdownROCRrprojrootRSpectrarstatixrsvdRtsneS4ArraysS4VectorssassScaledMatrixscalesscaterscattermoresctransformscuttleSeuratSeuratObjectshinySingleCellExperimentsitmosnowsourcetoolsspspamSparseArraySparseMspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrSummarizedExperimentsurvivalsyssystemfontstensortextshapingtibbletidyrtidyselecttinytexUCSC.utilsutf8uwotvctrsviporviridisviridisLitewithrxfunxtableXVectoryamlzlibbioczoo

PRECAST: installation

Rendered fromPRECAST.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2022-06-22
Started: 2022-06-22

PRECAST: DLPFC Single Sample Analysis

Rendered fromPRECAST.DLPFC.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2023-04-18
Started: 2022-10-18

PRECAST: Four DLPFC Sample Analysis

Rendered fromPRECAST.DLPFC4.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2024-01-26
Started: 2024-01-26

PRECAST: Human Breast Cancer Data Analysis

Rendered fromPRECAST.BreastCancer.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2024-01-26
Started: 2022-10-18

PRECAST: simulation

Rendered fromPRECAST.Simu.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2023-08-09
Started: 2022-06-22

Readme and manuals

Help Manual

Help pageTopics
Add embeddings for a Seurat objectAdd_embed
Add adjacency matrix list for a PRECASTObj objectAddAdjList
Add model settings for a PRECASTObj objectAddParSetting
Add tSNE embeddings for a Seurat objectAddTSNE
Add UMAP embeddings for a Seurat objectAddUMAP
Boxplot for a matrixboxPlot
Choose color schema from a palettechooseColors
Coordinates rotation for visualizationcoordinate_rotate
Create the PRECAST object with preprocessing step.CreatePRECASTObject
Low-dimensional embeddings' plotdimPlot
Heatmap for spots-by-feature matrixdoHeatmap
Draw a figure using a group of ggplot objectsdrawFigs
Spatial expression heatmapfeaturePlot
Set the first letter of a string vector to captialfirstup
Calculate adjacency matrix by user-specified number of neighborsgetAdj_fixedNumber
Calculate adjacency matrix for regular spatial coordinates.getAdj_reg
Human housekeeping genes databaseHuman_HK_genes
ICM-EM algorithm implementationICM.EM
ICM-EM algorithm implementation with organized paramtersICM.EM_structure
Integrate multiple SRT dataIntegrateSpaData
PRECAST model settingmodel_set
Mouse housekeeping genes databaseMouse_HK_genes
Spatial RGB heatmapplot_RGB
Scatter plot for two-dimensional embeddingsplot_scatter
Fit a PRECAST modelPRECAST
A simple PRECASTObj for examplePRECASTObj
Each PRECASTObj object has a number of slots which store information.PRECASTObj-class
Select common genes for multiple data batchesselectIntFeatures
Select best PRECAST model from candidated modelsSelectModel SelectModel.PRECASTObj SelectModel.SeqK_PRECAST_Object
Spatial heatmapSpaPlot
Volin/boxplot plotvolinPlot