To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("pcaMethods")

In most cases, you don't need to download the package archive at all.

pcaMethods

   

This package is for version 2.8 of Bioconductor; for the stable, up-to-date release version, see pcaMethods.

A collection of PCA methods.

Bioconductor version: 2.8

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 unique interface to the PCA results. Initiated at the Max-Planck Institute for Molecular Plant Physiology, Golm, Germany. Now developed at CAS-MPG Partner Institute for Computational Biology (PICB) Shanghai, P.R. China and RIKEN Plant Science Center, Yokohama Japan.

Author: Wolfram Stacklies, Henning Redestig, Kevin Wright

Maintainer: Wolfram Stacklies <wolfram.stacklies at gmail.com>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("pcaMethods")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("pcaMethods")

 

PDF missingValues.pdf
PDF outliers.pdf
PDF pcaMethods.pdf
PDF   Reference Manual

Details

biocViews Bioinformatics, Software
Version 1.36.0
In Bioconductor since BioC 1.9 (R-2.4) (9.5 years)
License GPL (>= 3)
Depends Biobase, MASS, pls, methods, Rcpp (>= 0.8.7)
Imports
LinkingTo Rcpp
Suggests aroma.light
SystemRequirements Rcpp
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source pcaMethods_1.36.0.tar.gz
Windows Binary pcaMethods_1.36.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard)
Mac OS X 10.9 (Mavericks)
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/pcaMethods/tree/release-2.8
Package Short Url http://bioconductor.org/packages/pcaMethods/
Package Downloads Report Download Stats

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