| 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.
| Package: | crosshybDetector |
| Type: | Package |
| Version: | 1.0.1 |
| Date: | 2007-07-31 |
| License: | LGPL |
Paolo Uva <paolo_uva@merck.com>
Uva, P., and de Rinaldis, E. CrosshybDetector: detection of cross-hybridization events in DNA microarray experiments. Submitted.
## 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=100)
# 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)