Nothing
library("aroma.affymetrix")
verbose <- Arguments$getVerbose(-50, timestamp=TRUE)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Setup
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
dataSet <- "Affymetrix-CytoSampleData"
chipType <- "Cytogenetics_Array"
cdf <- AffymetrixCdfFile$byChipType(chipType)
print(cdf)
csR <- AffymetrixCelSet$byName(dataSet, cdf=cdf)
print(csR)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Allelic-crosstalk calibration
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
acc <- AllelicCrosstalkCalibration(csR)
print(acc)
csC <- process(acc, verbose=verbose)
print(csC)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Plot allele pairs before and after calibration
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
for (what in c("input", "output")) {
toPNG(getFullName(acc), tags=c("allelePairs", what), aspectRatio=0.7, {
plotAllelePairs(acc, array=1, what=what, verbose=verbose)
})
}
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Probe-level summarization
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
plm <- AvgSnpPlm(csC, mergeStrands=TRUE)
print(plm)
if (length(findUnitsTodo(plm)) > 0) {
# Fit CN probes quickly (~5-10s/array + some overhead)
units <- fitCnProbes(plm, verbose=verbose)
str(units)
# int [1:2377527] 401698 401699 401700 401701 401702 401703 ...
# Fit remaining units, i.e. SNPs (~5-10min/array)
units <- fit(plm, verbose=verbose)
str(units)
# int [1:418181] 1 2 3 4 5 6 7 8 9 10 ...
}
ces <- getChipEffectSet(plm)
print(ces)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Export (theta, beta) for all arrays
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
dsList <- exportTotalAndFracB(ces, verbose=verbose)
print(dsList)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# TCN Segmentation and plotting
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
cns <- CbsModel(dsList$total)
print(cns)
ce <- ChromosomeExplorer(cns, zooms=2^(0:5))
print(ce)
process(ce, chromosomes=c(19, 22, 23), verbose=verbose)
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