pcaMethods
This is the released version of pcaMethods; for the devel version, see pcaMethods.
A collection of PCA methods
Bioconductor version: Release (3.20)
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("pcaMethods")):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
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")| Data with outliers | R Script | |
| Introduction | R Script | |
| Missing value imputation | R Script | |
| Reference Manual |
Details
| biocViews | Bayesian, Software |
| Version | 1.98.0 |
| In Bioconductor since | BioC 1.9 (R-2.4) (18 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 |
See More
| Suggests | matrixStats, lattice, ggplot2 |
| Linking To | Rcpp |
| Enhances | |
| Depends On Me | DeconRNASeq, crmn, DiffCorr, imputeLCMD |
| Imports Me | FRASER, MAI, MSPrep, MSnbase, MatrixQCvis, MultiBaC, OUTRIDER, PhosR, SomaticSignatures, consensusDE, destiny, pmp, scde, ADAPTS, CopSens, geneticae, lfproQC, LOST, MetabolomicsBasics, missCompare, multiDimBio, pmartR, polyRAD, promor, RAMClustR, santaR, scMappR |
| Suggests Me | MsCoreUtils, QFeatures, autonomics, cardelino, qmtools, mtbls2, pagoda2, rsvddpd |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | pcaMethods_1.98.0.tar.gz |
| Windows Binary (x86_64) | pcaMethods_1.98.0.zip |
| macOS Binary (x86_64) | pcaMethods_1.98.0.tgz |
| macOS Binary (arm64) | pcaMethods_1.98.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/pcaMethods |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/pcaMethods |
| Bioc Package Browser | https://code.bioconductor.org/browse/pcaMethods/ |
| Package Short Url | https://bioconductor.org/packages/pcaMethods/ |
| Package Downloads Report | Download Stats |