SCArray.sat
Large-scale single-cell RNA-seq data analysis using GDS files and Seurat
Bioconductor version: 3.24 · Package version: 1.13.0
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
| Maintainer | Xiuwen Zheng <xiuwen.zheng@abbvie.com> |
| Author | Xiuwen Zheng [aut, cre] (ORCID: <https://orcid.org/0000-0002-1390-0708>), Seurat contributors [ctb] (for the classes and methods defined in Seurat) |
| License | GPL-3 |
| Bug Reports | https://github.com/AbbVie-ComputationalGenomics/SCArray/issues |
| Downloads rank | 326 |
| Source branch | devel |
| biocViews | DataImport, DataRepresentation, RNASeq, SingleCell, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | SCArray.sat_1.13.0.tar.gz |
| Windows binary (x86_64) | SCArray.sat_1.13.0.zip |
| macOS binary (arm64) | SCArray.sat_1.13.0.tgz |
| macOS binary (x86_64) | SCArray.sat_1.13.0.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