SCArray

DOI: 10.18129/B9.bioc.SCArray  

This is the development version of SCArray; for the stable release version, see SCArray.

Large-scale single-cell RNA-seq data manipulation with GDS files

Bioconductor version: Development (3.18)

Provides large-scale single-cell RNA-seq data manipulation using Genomic Data Structure (GDS) files. It combines dense and sparse matrices stored in GDS files and the Bioconductor infrastructure framework (SingleCellExperiment and DelayedArray) to provide out-of-memory data storage and large-scale manipulation using the R programming language.

Author: Xiuwen Zheng [aut, cre]

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

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

Installation

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

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("SCArray")

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")

 

HTML Overview
HTML R Script Single-cell RNA-seq data manipulation using GDS files
PDF   Reference Manual
Text   NEWS

Details

biocViews DataImport, DataRepresentation, Infrastructure, RNASeq, SingleCell, Software
Version 1.9.1
In Bioconductor since BioC 3.13 (R-4.1) (2 years)
License GPL-3
Depends R (>= 3.5.0), gdsfmt(>= 1.35.4), methods, DelayedArray(>= 0.27.2)
Imports S4Vectors, utils, Matrix, BiocParallel, DelayedMatrixStats, SummarizedExperiment, SingleCellExperiment, BiocSingular
LinkingTo
Suggests BiocGenerics, scater, scuttle, uwot, RUnit, knitr, markdown, rmarkdown, rhdf5, HDF5Array
SystemRequirements
Enhances
URL https://github.com/AbbVie-ComputationalGenomics/SCArray
Depends On Me SCArray.sat
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_1.9.1.tar.gz
Windows Binary SCArray_1.9.1.zip (64-bit only)
macOS Binary (x86_64) SCArray_1.9.1.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/SCArray
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/SCArray
Bioc Package Browser https://code.bioconductor.org/browse/SCArray/
Package Short Url https://bioconductor.org/packages/SCArray/
Package Downloads Report Download Stats

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