PAA
PAA (Protein Array Analyzer)
Bioconductor version: 3.23 · Package version: 1.46.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("PAA") Details
| Maintainer | Michael Turewicz <michael.turewicz@rub.de>, Martin Eisenacher <martin.eisenacher@rub.de> |
| Author | Michael Turewicz [aut, cre], Martin Eisenacher [ctb, cre] |
| License | BSD_3_clause + file LICENSE |
| URL | http://www.ruhr-uni-bochum.de/mpc/software/PAA/ |
| System Requirements | C++ software package Random Jungle |
| Downloads rank | 641 |
| Source branch | RELEASE_3_23 |
| biocViews | Classification, Microarray, OneChannel, Proteomics, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | PAA_1.46.0.tar.gz |
| Windows binary (x86_64) | PAA_1.46.0.zip |
| macOS binary (arm64) | PAA_1.46.0.tgz |
| macOS binary (x86_64) | PAA_1.46.0.tgz |
Dependencies
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