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SCArray

Large-scale single-cell omics data manipulation with GDS files

Bioconductor version: 3.23 · Package version: 1.20.0

Provides large-scale single-cell omics 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.

Installation

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

BiocManager::install("SCArray")

Details

MaintainerXiuwen Zheng <xiuwen.zheng@abbvie.com>
AuthorXiuwen Zheng [aut, cre] (ORCID: <https://orcid.org/0000-0002-1390-0708>)
LicenseGPL-3
URLhttps://github.com/AbbVie-ComputationalGenomics/SCArray
Downloads rank460
Source branchRELEASE_3_23
biocViewsDataImport, DataRepresentation, Infrastructure, RNASeq, SingleCell, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageSCArray_1.20.0.tar.gz
Windows binary (x86_64)SCArray_1.20.0.zip
macOS binary (arm64)SCArray_1.20.0.tgz
macOS binary (x86_64)SCArray_1.20.0.tgz
Dependencies

Depends: R (>= 3.5.0), gdsfmt (>= 1.36.0), methods, DelayedArray (>= 0.31.5)

Imports: S4Vectors, utils, Matrix, SparseArray (>= 1.5.13), BiocParallel, DelayedMatrixStats, SummarizedExperiment, SingleCellExperiment, BiocSingular

Suggests: BiocGenerics, scater, scuttle, uwot, RUnit, knitr, markdown, rmarkdown, rhdf5, HDF5Array

Reverse dependencies

Depends On Me (1): SCArray.sat