Hello,
I have a large dataset of ~10000 CEL files that needs to be normalized. I
tried using aroma.affy for this, but the job is running for more than 3
weeks and in need of help/suggestions. The data is in standard affy rat2302
chip. I steps I used are (based on:
http://www.aroma-project.org/vignettes/GeneSTArrayAnalysis):
library("aroma.affymetrix")
library(rat2302cdf)
verbose <- Arguments$getVerbose(-8, timestamp=TRUE)
chipType <- "rat2302"
cdf <- AffymetrixCdfFile$byChipType(chipType) #, tags="r3")
cs <- AffymetrixCelSet$byName("tissues", cdf=cdf)
bc <- RmaBackgroundCorrection(cs)
csBC <- process(bc,verbose=verbose)
qn <- QuantileNormalization(csBC, typesToUpdate="pm")
csN <- process(qn, verbose=verbose)
plm <- RmaPlm(csN)
fit(plm, verbose=verbose)
All steps were ok but the last step : fit(plm,verbose=verbose) is running
for nearly 3 weeks. Is this needed for probe summarization? What exactly
does this fit do?
Any suggestion will be helpful.
Thanks,
Rafi
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