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

Bioconductor version: Release (3.19)

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>

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


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if (!require("BiocManager", quietly = TRUE))


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


biocViews DataImport, DataRepresentation, RNASeq, SingleCell, Software
Version 1.4.0
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License GPL-3
Depends methods, SCArray(>= 1.7.13), SeuratObject (>= 5.0), Seurat (>= 5.0)
Imports S4Vectors, utils, stats, BiocGenerics, BiocParallel, gdsfmt, DelayedArray, BiocSingular, SummarizedExperiment, Matrix
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Source Package SCArray.sat_1.4.0.tar.gz
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