SCArray.sat
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 abbvie.com>
citation("SCArray.sat")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SCArray.sat")
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.sat")| scRNA-seq data analysis with GDS files and Seurat | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DataImport, DataRepresentation, RNASeq, SingleCell, Software |
| Version | 1.4.0 |
| In Bioconductor since | BioC 3.17 (R-4.3) (1.5 years) |
| 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 |
| System Requirements | |
| URL | |
| Bug Reports | https://github.com/AbbVie-ComputationalGenomics/SCArray/issues |
See More
| Suggests | future, RUnit, knitr, markdown, rmarkdown, BiocStyle |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | SCArray.sat_1.4.0.tar.gz |
| Windows Binary (x86_64) | SCArray.sat_1.4.0.zip |
| macOS Binary (x86_64) | SCArray.sat_1.4.0.tgz |
| macOS Binary (arm64) | SCArray.sat_1.4.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/SCArray.sat |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/SCArray.sat |
| Bioc Package Browser | https://code.bioconductor.org/browse/SCArray.sat/ |
| Package Short Url | https://bioconductor.org/packages/SCArray.sat/ |
| Package Downloads Report | Download Stats |