To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("PAA")
In most cases, you don't need to download the package archive at all.
PAA
PAA (Protein Array Analyzer)
Bioconductor version: 3.0
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")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("PAA")
Documentation
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 |
Details
| biocViews | Classification, Microarray, OneChannel, Proteomics, Software |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | BSD_3_clause + file LICENSE |
| Depends | R (>= 3.0.3), Rcpp (>= 0.10.6.1) |
| 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 |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | PAA_1.0.0.tar.gz |
| Windows Binary | PAA_1.0.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | PAA_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | PAA_1.0.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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