SCArray.sat

DOI: 10.18129/B9.bioc.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>

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")

 

HTML	R Script	scRNA-seq data analysis with GDS files and Seurat
PDF		Reference Manual
Text		NEWS

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
LinkingTo
Suggests	RUnit, knitr, markdown, rmarkdown, BiocStyle
SystemRequirements
Enhances
URL
BugReports	https://github.com/AbbVie-ComputationalGenomics/SCArray/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
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