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Bioconductor - PAA (development version)

PAA

This is the development version of PAA; for the stable release version, see PAA.

PAA (Protein Array Analyzer)

Bioconductor version: Development (3.22)

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 "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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")
Details biocViews Classification, Microarray, OneChannel, Proteomics, Software Version 1.43.0 In Bioconductor since BioC 3.0 (R-3.1) (10.5 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 Package Archives

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


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