To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("PAA")
In most cases, you don't need to download the package archive at all.
Bioconductor version: Release (3.1)
PAA imports single color (protein) microarray data that has been saved in gpr file format - esp. ProtoArray data. After pre-processing (background correction, batch filtering, normalization) univariate feature pre-selection 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")
):
To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("PAA")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("PAA")
R Script | PAA tutorial | |
Reference Manual | ||
Text | README | |
Text | NEWS | |
Text | LICENSE |
biocViews | Classification, Microarray, OneChannel, Proteomics, Software |
Version | 1.3.3 |
In Bioconductor since | BioC 3.0 (R-3.1) (1 year) |
License | BSD_3_clause + file LICENSE |
Depends | R (>= 3.2.0), Rcpp (>= 0.11.6) |
Imports | e1071, limma, MASS, mRMRe, randomForest, ROCR, sva |
LinkingTo | Rcpp |
Suggests | BiocStyle, RUnit, BiocGenerics, vsn |
SystemRequirements | C++ software package Random Jungle |
Enhances | |
URL | http://www.medizinisches-proteom-center.de/PAA |
Depends On Me | |
Imports Me | |
Suggests Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | PAA_1.3.3.tar.gz |
Windows Binary | PAA_1.3.3.zip (32- & 64-bit) |
Mac OS X 10.6 (Snow Leopard) | PAA_1.3.3.tgz |
Mac OS X 10.9 (Mavericks) | PAA_1.3.3.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/PAA/tree/release-3.1 |
Package Short Url | http://bioconductor.org/packages/PAA/ |
Package Downloads Report | Download Stats |
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