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PAA

PAA (Protein Array Analyzer)


Bioconductor version: Release (3.18)

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 "4.3") 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")
PAA tutorial PDF R Script
PAA_1.7.1.pdf PDF
Reference Manual PDF
README Text
NEWS Text
LICENSE Text

Details

biocViews Classification, Microarray, OneChannel, Proteomics, Software
Version 1.36.0
In Bioconductor since BioC 3.0 (R-3.1) (9.5 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
System Requirements C++ software package Random Jungle
URL http://www.ruhr-uni-bochum.de/mpc/software/PAA/
See More
Suggests BiocStyle, RUnit, BiocGenerics, vsn
Linking To Rcpp
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package PAA_1.36.0.tar.gz
Windows Binary PAA_1.36.0.zip
macOS Binary (x86_64) PAA_1.36.0.tgz
macOS Binary (arm64) PAA_1.36.0.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