This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see BiocSingular.
Bioconductor version: 3.17
Implements exact and approximate methods for singular value decomposition and principal components analysis, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Where possible, parallelization is achieved using the BiocParallel framework.
Author: Aaron Lun [aut, cre, cph]
Maintainer: Aaron Lun <infinite.monkeys.with.keyboards at gmail.com>
Citation (from within R,
enter citation("BiocSingular")
):
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("BiocSingular")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("BiocSingular")
HTML | R Script | 1. SVD and PCA |
HTML | R Script | 2. Matrix classes |
Reference Manual | ||
Text | NEWS |
biocViews | DimensionReduction, PrincipalComponent, Software |
Version | 1.16.0 |
In Bioconductor since | BioC 3.9 (R-3.6) (4.5 years) |
License | GPL-3 |
Depends | |
Imports | BiocGenerics, S4Vectors, Matrix, methods, utils, DelayedArray, BiocParallel, ScaledMatrix, irlba, rsvd, Rcpp, beachmat |
LinkingTo | Rcpp, beachmat |
Suggests | testthat, BiocStyle, knitr, rmarkdown, ResidualMatrix |
SystemRequirements | C++11 |
Enhances | |
URL | https://github.com/LTLA/BiocSingular |
BugReports | https://github.com/LTLA/BiocSingular/issues |
Depends On Me | compartmap |
Imports Me | batchelor, BayesSpace, clusterExperiment, DelayedTensor, Dino, GSVA, miloR, mumosa, NanoMethViz, NewWave, PCAtools, SCArray, SCArray.sat, scater, scDblFinder, scMerge, scran, scry, SingleR, velociraptor |
Suggests Me | chihaya, HCAData, ResidualMatrix, ScaledMatrix, spatialHeatmap, splatter, Voyager |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | BiocSingular_1.16.0.tar.gz |
Windows Binary | BiocSingular_1.16.0.zip (64-bit only) |
macOS Binary (x86_64) | BiocSingular_1.16.0.tgz |
macOS Binary (arm64) | BiocSingular_1.16.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/BiocSingular |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/BiocSingular |
Bioc Package Browser | https://code.bioconductor.org/browse/BiocSingular/ |
Package Short Url | https://bioconductor.org/packages/BiocSingular/ |
Package Downloads Report | Download Stats |
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