PAA

DOI: 10.18129/B9.bioc.PAA  

PAA (Protein Array Analyzer)

Bioconductor version: Release (3.16)

PAA imports single color (protein) microarray data that has been saved in gpr file format - esp. ProtoArray data. After preprocessing (background correction, batch filtering, normalization) univariate feature preselection 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 (version "4.2") and enter:

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

BiocManager::install("PAA")

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("PAA")

 

PDF R Script PAA tutorial
PDF PAA_1.7.1.pdf
PDF   Reference Manual
Text   README
Text   NEWS
Text   LICENSE

Details

biocViews Classification, Microarray, OneChannel, Proteomics, Software
Version 1.32.0
In Bioconductor since BioC 3.0 (R-3.1) (8.5 years)
License BSD_3_clause + file LICENSE
Depends R (>= 3.2.0), Rcpp (>= 0.11.6)
Imports e1071, gplots, gtools, limma, MASS, mRMRe, randomForest, ROCR, sva
LinkingTo Rcpp
Suggests BiocStyle, RUnit, BiocGenerics, vsn
SystemRequirements C++ software package Random Jungle
Enhances
URL http://www.ruhr-uni-bochum.de/mpc/software/PAA/
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package PAA_1.32.0.tar.gz
Windows Binary PAA_1.32.0.zip (64-bit only)
macOS Binary (x86_64) PAA_1.32.0.tgz
macOS Binary (arm64) PAA_1.32.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/PAA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/PAA
Bioc Package Browser https://code.bioconductor.org/browse/PAA/
Package Short Url https://bioconductor.org/packages/PAA/
Package Downloads Report Download Stats

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