Package: PAA 1.39.0

Michael Turewicz

PAA: PAA (Protein Array Analyzer)

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.

Authors:Michael Turewicz [aut, cre], Martin Eisenacher [ctb, cre]

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PAA.pdf |PAA.html✨
PAA/json (API)
NEWS

# Install 'PAA' in R:

install.packages('PAA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

c++– GNU Standard C++ Library v3

On BioConductor:PAA-1.39.0(bioc 3.20)PAA-1.38.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

19 exports 0.91 score 77 dependencies 19 mentions

Last updated 2 months agofrom:ac79f3ed5f

Exports:batchAdjust batchFilter batchFilter.anova diffAnalysis loadGPR mMsMatrix normalizeArrays plotArray plotFeatures plotFeaturesHeatmap plotFeaturesHeatmap.2 plotMAPlots plotNormMethods preselect printFeatures pvaluePlot selectFeatures shuffleData volcanoPlot

Dependencies:annotate AnnotationDbi askpass BH Biobase BiocGenerics BiocParallel Biostrings bit bit64 bitops blob cachem caTools class cli codetools cpp11 crayon curl DBI e1071 edgeR fastmap formatR futile.logger futile.options genefilter GenomeInfoDb GenomeInfoDbData glue gplots gtools httr igraph IRanges jsonlite KEGGREST KernSmooth lambda.r lattice lifecycle limma locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise mgcv mime mRMRe nlme openssl pkgconfig plogr png proxy R6 randomForest Rcpp rlang ROCR RSQLite S4Vectors snow statmod survival sva sys UCSC.utils vctrs XML xtable XVector zlibbioc

PAA tutorial

Rendered fromPAA_vignette.Rnwusingutils::Sweaveon Jun 22 2024.

Last update: 2018-08-30
Started: 2014-10-03

Help page	Topics
Adjust microarray data for batch effects.	batchAdjust
Remove differential features regarding array batches/lots.	batchFilter
Remove features which are differential regarding microarray batches / lots in a multi-batch scenario.	batchFilter.anova
Differential analysis.	diffAnalysis
Importing raw data from gpr files.	loadGPR
Compute a reference minimum M statistic (n1 x n2)-matrix.	mMsMatrix
Normalize microarray data.	normalizeArrays
Plot ProtoArray expression intensities in the original arrangement mimicking the original scan image.	plotArray
Plot intensities of features.	plotFeatures
Plot feature intensities as a heatmap.	plotFeaturesHeatmap
Alternative function to plot feature intensities as a heatmap.	plotFeaturesHeatmap.2
Check normalization results with MA plots.	plotMAPlots
Check normalization results with boxplots.	plotNormMethods
Score and preselect features.	preselect
Print features into a table.	printFeatures
Draw a p-value plot.	pvaluePlot
Select features using frequency-based or ensemble feature selection.	selectFeatures
Shuffles class labels to obtain random groups.	shuffleData
Draw a volcano plot.	volcanoPlot

Package: PAA 1.39.0

PAA: PAA (Protein Array Analyzer)

PAA tutorial

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Help Manual

Usage by other packages (reverse dependencies)