I would like to know if there are any recommendations on re-running
'aroma' on a subset of samples.  In my case, the first pass through a
dataset (Affy Mouse expression) revealed an outlier array.  I would
now like to re-run with the outlier array removed.

1) Is extract() the recommended way to do sample subsetting:
 cs <- extract(cs, 2:length(cs))  ## first array is the outlier
Using brackets [] produced a list, so I presume that does not work.

2) An aroma re-run quickly returns at this point, because the output
files already exist.  It appears necessary to remove the output files
first.  The following code appears apropos (pulled from
http://www.agron-omics.eu/uploads/Tiling%20array%20files/agronomicsTools01.r):
>>>  CODE
force <- TRUE
bc <- RmaBackgroundCorrection(celSet);
if (force & !is.null(getOutputFiles(bc))){
    file.remove(getOutputFiles(bc))
}
csBC <- process(bc, verbose=verbose, force=force, overwrite=force);
qn <- QuantileNormalization(csBC, typesToUpdate="pm");
if (force) file.remove(getTargetDistributionPathname(qn))
clearCache(qn)
if (force & !is.null(getOutputFiles(qn))){
    file.remove(getOutputFiles(qn))
}
csN <- process(qn, verbose=verbose, force=force);
plm <- RmaPlm(csN);
fit(plm, unit=NULL, verbose=verbose, force=force)
<<<   END OF CODE

I feel having the output files consistent (i.e. not mixed from
different runs) is a good idea.  The flip side is, analyzing subsets
of samples in parallel (e.g. before a strict decision on outliers has
been made) is probably best handled by treating each one as a separate
dataset, starting from the original CEL files.

Regards,

_Taku

-- 
When reporting problems on aroma.affymetrix, make sure 1) to run the latest 
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