SCArray.sat
This is the released version of SCArray.sat; for the devel version, see SCArray.sat.
Large-scale single-cell RNA-seq data analysis using GDS files and Seurat
Bioconductor version: Release (3.23)
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")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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 | 1.12.0 |
| In Bioconductor since | BioC 3.17 (R-4.3) (3.5 years) |
| License | GPL-3 |
| Depends | methods, SCArray(>= 1.13.1), 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_1.12.0.tar.gz |
| Windows Binary (x86_64) | SCArray.sat_1.12.0.zip |
| macOS Binary (big-sur-x86_64) | SCArray.sat_1.12.0.tgz |
| macOS Binary (sonoma-arm64) | SCArray.sat_1.12.0.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 |