To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("PAA")

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

PAA

PAA (Protein Array Analyzer)

Bioconductor version: 3.1

PAA imports single color (protein) microarray data that has been saved in gpr file format - esp. ProtoArray data. After pre-processing (background correction, batch filtering, normalization) univariate feature pre-selection is performed (e.g., using the "minimum M statistic" approach - hereinafter referred to as "mMs"). Subsequently, a multivariate feature selection is conducted to discover biomarker candidates. Therefore, either a frequency-based backwards elimination aproach or ensemble feature selection can be used. PAA provides a complete toolbox of analysis tools including several different plots for results examination and evaluation.

Author: Michael Turewicz [aut, cre], Martin Eisenacher [ctb, cre]

Maintainer: Michael Turewicz <michael.turewicz at rub.de>, Martin Eisenacher <martin.eisenacher at rub.de>

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

Installation

To install this package, start R and enter:

## try http if https is not available
source("https://bioconductor.org/biocLite.R")
biocLite("PAA")

Documentation

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

browseVignettes("PAA")

 

PDF R Script PAA tutorial
PDF   Reference Manual
Text   README
Text   NEWS
Text   LICENSE

Details

biocViews Classification, Microarray, OneChannel, Proteomics, Software
Version 1.3.3
In Bioconductor since BioC 3.0 (R-3.1) (1 year)
License BSD_3_clause + file LICENSE
Depends R (>= 3.2.0), Rcpp (>= 0.11.6)
Imports e1071, limma, MASS, mRMRe, randomForest, ROCR, sva
LinkingTo Rcpp
Suggests BiocStyle, RUnit, BiocGenerics, vsn
SystemRequirements C++ software package Random Jungle
Enhances
URL http://www.medizinisches-proteom-center.de/PAA
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source PAA_1.3.3.tar.gz
Windows Binary PAA_1.3.3.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) PAA_1.3.3.tgz
Mac OS X 10.9 (Mavericks) PAA_1.3.3.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/PAA/tree/release-3.1
Package Short Url http://bioconductor.org/packages/PAA/
Package Downloads Report Download Stats

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