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SCArray.sat

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

Bioconductor version: 3.23 · Package version: 1.12.0

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.

Installation

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

BiocManager::install("SCArray.sat")

Details

MaintainerXiuwen Zheng <xiuwen.zheng@abbvie.com>
AuthorXiuwen Zheng [aut, cre] (ORCID: <https://orcid.org/0000-0002-1390-0708>), Seurat contributors [ctb] (for the classes and methods defined in Seurat)
LicenseGPL-3
Bug Reportshttps://github.com/AbbVie-ComputationalGenomics/SCArray/issues
Downloads rank326
Source branchRELEASE_3_23
biocViewsDataImport, DataRepresentation, RNASeq, SingleCell, Software

Documentation

Download

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

Source packageSCArray.sat_1.12.0.tar.gz
Windows binary (x86_64)SCArray.sat_1.12.0.zip
macOS binary (arm64)SCArray.sat_1.12.0.tgz
macOS binary (x86_64)SCArray.sat_1.12.0.tgz
Dependencies

Depends: methods, SCArray (>= 1.13.1), SeuratObject (>= 5.0), Seurat (>= 5.0)

Imports: S4Vectors, utils, stats, BiocGenerics, BiocParallel, gdsfmt, DelayedArray, BiocSingular, SummarizedExperiment, Matrix

Suggests: future, RUnit, knitr, markdown, rmarkdown, BiocStyle