crosshybDetector-package {crosshybDetector} | R Documentation |
crosshybDetector
is a package which calculates for each probe on the array the
probability of cross-hybridization by using the probe intensity values. The software provides
the user with the list of probes potentially corrupted and the associated p-values computed
by Monte Carlo simulations. Plots are generated allowing a global overview of the cross-hybridization
events in a microarray experiments. The package contains code from the dismissed pairseqsim package
(removed in BioConductor > 1.9 ), created by Witold Wolski <witek96@users.sourceforge.net> and
released under GNU LGPL license
Package: | crosshybDetector |
Type: | Package |
Version: | 1.0.4 |
Date: | 2009-02-02 |
License: | LGPL |
Paolo Uva <paolo.uva@gmail.com>
Uva, P., and de Rinaldis, E. CrossHybDetector: detection of cross-hybridization events in DNA microarray experiments. BMC Bioinformatics 2008, 9:485
## Not run: # This workflow will produce several images and files # containing the results of crosshybDetector pVal <- 0.01 # Threshold for corruptors data(probeSeq) # Vector of probe sequences data(raw) # Object of class marrayRaw containing one array # Array names arrayNames <- c("myArray") for (k in 1:length(arrayNames)){ # Run crosshyb crosshyb.out <- crosshyb(raw, probeSeq, plate=k, numPermut=10000, probeNameID="Name", probes="probes", satValue = 65535, maxProbes=50) # Write probes analyzed by crosshyb to file # Not nice for reading but useful for tracking crosshyb2xls.putative(crosshyb.out, arrayName=arrayNames[k]) # Plot p-values obtained with Monte Carlo simulations crosshybMCplot(crosshyb.out, pVal, arrayName=arrayNames[k], doPlot=TRUE) # Extract bad probes badProbes <- extractBadProbes(crosshyb.out, pVal) # Plots for RED channel if(length(badProbes$corruptorsR)){ parent <- badProbes$corruptorsR child <- badProbes$corruptedR # Draw image plot crosshybImage(raw, plate = k, parent=parent, children=child, arrayName = arrayNames[k], channel="red", doPlot=TRUE) # Write parents and childrens to tab-delimited files (xls extension) crosshyb2xls(raw, array=k, parent=parent, children=child, arrayName=arrayNames[k], channel="red", probeNameID="Name") } # Plots for GREEN channel if(length(badProbes$corruptorsG)){ parent <- badProbes$corruptorsG child <- badProbes$corruptedG # Draw image plot crosshybImage(raw, plate = k, parent=parent, children=child, arrayName = arrayNames[k], channel="green", doPlot=TRUE) # Write parents and childrens to tab-delimited files (xls extension) crosshyb2xls(raw, array=k, parent=parent, children=child, arrayName=arrayNames[k], channel="green", probeNameID="Name") } # Loess normalization using only probes # Use maNorm function from marray package norm <- maNorm(raw, norm="l", subset=maControls(raw) == "probes") # MA plot showing corruptor and corrupted probes crosshybMAplot(m = maM(norm[,k]), a = maA(norm[,k]), subset=maControls(raw) %in% c("probes", "spike"), badProbes=badProbes, arrayName=arrayNames[k], doPlot=TRUE) rm(badProbes) } ## End(Not run)