PAA

PAA (Protein Array Analyzer)

Bioconductor version: Release (3.20)

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 "4.4") 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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	Classification, Microarray, OneChannel, Proteomics, Software
Version	1.40.0
In Bioconductor since	BioC 3.0 (R-3.1) (10 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/

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_1.40.0.tar.gz
Windows Binary (x86_64)	PAA_1.40.0.zip
macOS Binary (x86_64)	PAA_1.40.0.tgz
macOS Binary (arm64)	PAA_1.40.0.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