Package: SCArray.sat 1.5.0

Xiuwen Zheng

SCArray.sat: Large-scale single-cell RNA-seq data analysis using GDS files and Seurat

Extends the Seurat classes and functions to support Genomic Data Structure (GDS) files as a DelayedArray backend for data representation. It relies on the implementation of GDS-based DelayedMatrix in the SCArray package to represent single cell RNA-seq data. The common optimized algorithms leveraging GDS-based and single cell-specific DelayedMatrix (SC_GDSMatrix) are implemented in the SCArray package. SCArray.sat introduces a new SCArrayAssay class (derived from the Seurat Assay), which wraps raw counts, normalized expressions and scaled data matrix based on GDS-specific DelayedMatrix. It is designed to integrate seamlessly with the Seurat package to provide common data analysis in the SeuratObject-based workflow. Compared with Seurat, SCArray.sat significantly reduces the memory usage without downsampling and can be applied to very large datasets.

Authors:Xiuwen Zheng [aut, cre], Seurat contributors [ctb]

SCArray.sat_1.5.0.tar.gz
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SCArray.sat.pdf |SCArray.sat.html
SCArray.sat/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/abbvie-computationalgenomics/scarray/issues

On BioConductor:SCArray.sat-1.5.0(bioc 3.20)SCArray.sat-1.4.0(bioc 3.19)

bioconductor-package

6 exports 0.82 score 175 dependencies

Last updated 2 months agofrom:17b97a4cf1

Exports:CreateAssayObject2scGetFilesscMemoryscNewAssayGDSscNewSeuratGDSsubset.SCArrayAssay

Dependencies:abindaskpassbase64encbeachmatBHBiobaseBiocGenericsBiocParallelBiocSingularbitopsbslibcachemcaToolscliclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDelayedArrayDelayedMatrixStatsdeldirdigestdotCall64dplyrdqrngevaluatefansifarverfastDummiesfastmapfitdistrplusFNNfontawesomeformatRfsfutile.loggerfutile.optionsfuturefuture.applygdsfmtgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenlifecyclelistenvlmtestmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUImunsellnlmeopensslparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLreshape2reticulaterlangrmarkdownROCRrprojrootRSpectrarsvdRtsneS4ArraysS4VectorssassScaledMatrixscalesSCArrayscattermoresctransformSeuratSeuratObjectshinySingleCellExperimentsitmosnowsourcetoolsspspamSparseArraysparseMatrixStatsspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.utilsstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytexUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzlibbioczoo

Large-scale single-cell RNA-seq data analysis using GDS files and Seurat

Rendered fromSCArray.sat.Rmdusingknitr::rmarkdownon Jul 01 2024.

Last update: 2024-01-13
Started: 2023-01-22

Readme and manuals

Help Manual

Help pageTopics
Large-scale single-cell RNA-seq data analysis using GDS files and SeuratSCArray.sat-package SCArray.sat
Create an Assay objectCreateAssayObject2
Normalize Count DataNormalizeData NormalizeData.SC_GDSMatrix
Run PCARunPCA RunPCA.SCArrayAssay RunPCA.SC_GDSMatrix
Scale and Center the DataScaleData ScaleData.SC_GDSMatrix
GDS-specific Assay ClassSCArrayAssay SCArrayAssay-class
SCArrayAssay S3 methodsGetAssayData GetAssayData.SCArrayAssay SCArrayAssay-methods SetAssayData SetAssayData.SCArrayAssay subset subset.SCArrayAssay
File names for on-disk backendscGetFiles scGetFiles,Assay-method scGetFiles,SCArrayAssay-method scGetFiles,Seurat-method
Load Data to MemoryscMemory scMemory,SCArrayAssay-method scMemory,Seurat-method scMemory,Seurat_g-method
Create Assay ObjectscNewAssayGDS
Create Seurat ObjectscNewSeuratGDS
GDS-based Seurat ClassSeurat_g Seurat_g-class