PAA
This is the released version of PAA; for the devel version, see PAA.
PAA (Protein Array Analyzer)
DOI: 10.18129/B9.bioc.PAA
Bioconductor version: Release (3.23)
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("PAA")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") 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 | R Script | |
| PAA_1.7.1.pdf | ||
| Reference Manual | ||
| README | Text | |
| NEWS | Text | |
| LICENSE | Text |
Details
| biocViews | Classification, Microarray, OneChannel, Proteomics, Software |
| Version | 1.46.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) (12 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_1.46.0.tar.gz |
| Windows Binary (x86_64) | PAA_1.46.0.zip |
| macOS Binary (big-sur-x86_64) | PAA_1.46.0.tgz |
| macOS Binary (sonoma-arm64) | PAA_1.46.0.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 |