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SCArray.sat

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

Bioconductor version: Release (3.17)

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.

Author: Xiuwen Zheng [aut, cre] , Seurat contributors [ctb] (for the classes and methods defined in Seurat)

Maintainer: Xiuwen Zheng <xiuwen.zheng at abbvie.com>

Citation (from within R, enter citation("SCArray.sat")):

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SCArray.sat")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("SCArray.sat")
scRNA-seq data analysis with GDS files and Seurat HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DataImport, DataRepresentation, RNASeq, SingleCell, Software
Version 1.0.3
In Bioconductor since BioC 3.17 (R-4.3) (< 6 months)
License GPL-3
Depends methods, SCArray(>= 1.7.13), SeuratObject (>= 4.0), Seurat (>= 4.0)
Imports S4Vectors, utils, stats, BiocGenerics, BiocParallel, gdsfmt, DelayedArray, BiocSingular, SummarizedExperiment
Linking To
Suggests RUnit, knitr, markdown, rmarkdown, BiocStyle
System Requirements
Enhances
URL
Bug Reports https://github.com/AbbVie-ComputationalGenomics/SCArray/issues
See More
Depends On Me
Imports Me
Suggests Me
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Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package SCArray.sat_1.0.3.tar.gz
Windows Binary SCArray.sat_1.0.3.zip
macOS Binary (x86_64) SCArray.sat_1.0.3.tgz
macOS Binary (arm64) SCArray.sat_1.0.3.tgz
Source Repository git clone https://git.bioconductor.org/packages/SCArray.sat
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/SCArray.sat
Bioc Package Browser https://code.bioconductor.org/browse/SCArray.sat/
Package Short Url https://bioconductor.org/packages/SCArray.sat/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.17 Source Archive