To install this package, start R and enter:

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

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

pvca

 

   

Principal Variance Component Analysis (PVCA)

Bioconductor version: Release (3.4)

This package contains the function to assess the batch sourcs by fitting all "sources" as random effects including two-way interaction terms in the Mixed Model(depends on lme4 package) to selected principal components, which were obtained from the original data correlation matrix. This package accompanies the book "Batch Effects and Noise in Microarray Experiements, chapter 12.

Author: Pierre Bushel <bushel at niehs.nih.gov>

Maintainer: Jianying LI <li11 at niehs.nih.gov>

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

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("pvca")

 

PDF R Script Batch effect estimation in Microarray data
PDF   Reference Manual

Details

biocViews BatchEffect, Microarray, Software
Version 1.14.0
In Bioconductor since BioC 2.12 (R-3.0) (4 years)
License LGPL (>= 2.0)
Depends R (>= 2.15.1)
Imports Matrix, Biobase, vsn, stats, lme4
LinkingTo
Suggests golubEsets
SystemRequirements
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 pvca_1.14.0.tar.gz
Windows Binary pvca_1.14.0.zip
Mac OS X 10.9 (Mavericks) pvca_1.14.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/pvca/tree/release-3.4
Package Short Url http://bioconductor.org/packages/pvca/
Package Downloads Report Download Stats

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