pcaMethods

This is the development version of pcaMethods; for the stable release version, see pcaMethods.

All versions

3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9, 3.8, 3.7, 3.6, 3.5, 3.4, 3.3, 3.2, 3.1, 3.0, 2.14, 2.13, 2.12, 2.11, 2.10, 2.9, 2.8, 2.7, 2.6, 2.5

A collection of PCA methods

Bioconductor version: Development (3.24)

Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany.

Author: Wolfram Stacklies, Henning Redestig, Kevin Wright

Maintainer: Henning Redestig <henning.red at gmail.com>

Citation (from within R, enter citation("pcaMethods")):

Wolfram Stacklies, Henning Redestig, Kevin Wright. pcaMethods: A collection of PCA methods. doi:10.18129/B9.bioc.pcaMethods, R package version 2.5.0, https://bioconductor.org/packages/pcaMethods.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")

BiocManager::install("pcaMethods")

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("pcaMethods")

Missing value imputation	PDF	R Script
Data with outliers	PDF	R Script
Introduction	PDF	R Script
Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Bayesian, Software
Version	2.5.0
In Bioconductor since	BioC 1.9 (R-2.4) (20 years)
License	GPL (>= 3)
Depends	Biobase, methods
Imports	BiocGenerics, Rcpp (>= 0.11.3), MASS
System Requirements	Rcpp
URL	https://github.com/hredestig/pcamethods
Bug Reports	https://github.com/hredestig/pcamethods/issues

Suggests	matrixStats, lattice, ggplot2
Linking To	Rcpp
Enhances
Depends On Me	crmn, DiffCorr, imputeLCMD
Imports Me	ADAPTS, destiny, FRASER, geneticae, lfproQC, LOST, MAI, MatrixQCvis, MetabolomicsBasics, metabom8, metamorphr, MSnbase, MultiBaC, multiDimBio, notameViz, OUTRIDER, PhosR, pmartR, pmp, polyRAD, promor, santaR, scde, sclValid, scMappR, SomaticSignatures
Suggests Me	autonomics, cardelino, MsCoreUtils, mtbls2, notame, pagoda2, QFeatures, qmtools, rsvddpd
Links To Me
Build Report	Build Report, r-universe

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	pcaMethods_2.5.0.tar.gz
Windows Binary (x86_64)	pcaMethods_2.5.0.zip
macOS Binary (big-sur-x86_64)	pcaMethods_2.5.0.tgz
macOS Binary (sonoma-arm64)	pcaMethods_2.5.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/pcaMethods
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/pcaMethods
Package Short Url	https://bioconductor.org/packages/pcaMethods/
Package Downloads Report	Download Stats