scPCA
Sparse Contrastive Principal Component Analysis
Bioconductor version: Release (3.19)
A toolbox for sparse contrastive principal component analysis (scPCA) of high-dimensional biological data. scPCA combines the stability and interpretability of sparse PCA with contrastive PCA's ability to disentangle biological signal from unwanted variation through the use of control data. Also implements and extends cPCA.
Author: Philippe Boileau [aut, cre, cph] , Nima Hejazi [aut] , Sandrine Dudoit [ctb, ths]
Maintainer: Philippe Boileau <philippe_boileau at berkeley.edu>
citation("scPCA")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scPCA")
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("scPCA")
Sparse contrastive principal component analysis | HTML | R Script |
Reference Manual | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | DifferentialExpression, GeneExpression, Microarray, PrincipalComponent, RNASeq, Sequencing, Software |
Version | 1.18.0 |
In Bioconductor since | BioC 3.10 (R-3.6) (5 years) |
License | MIT + file LICENSE |
Depends | R (>= 4.0.0) |
Imports | stats, methods, assertthat, tibble, dplyr, purrr, stringr, Rdpack, matrixStats, BiocParallel, elasticnet, sparsepca, cluster, kernlab, origami, RSpectra, coop, Matrix, DelayedArray, ScaledMatrix, MatrixGenerics |
System Requirements | |
URL | https://github.com/PhilBoileau/scPCA |
Bug Reports | https://github.com/PhilBoileau/scPCA/issues |
See More
Suggests | DelayedMatrixStats, sparseMatrixStats, testthat (>= 2.1.0), covr, knitr, rmarkdown, BiocStyle, ggplot2, ggpubr, splatter, SingleCellExperiment, microbenchmark |
Linking To | |
Enhances | |
Depends On Me | OSCA.advanced, OSCA.workflows |
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 | scPCA_1.18.0.tar.gz |
Windows Binary | scPCA_1.18.0.zip |
macOS Binary (x86_64) | scPCA_1.18.0.tgz |
macOS Binary (arm64) | scPCA_1.18.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/scPCA |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/scPCA |
Bioc Package Browser | https://code.bioconductor.org/browse/scPCA/ |
Package Short Url | https://bioconductor.org/packages/scPCA/ |
Package Downloads Report | Download Stats |