Hi Patricia
your paramters are as follows

min.exp - the minimum expression level you would typically expect to see in
your experiment. For Affymetrix experiments, the default here has been set
at log2(10), but that would obviously depend on your experiment and also how
you have normalised the data

min.exp.no - the minimum number of arrays you want your probeset to show the
min.exp on. In your experiment, it is set at 2 so you  are filtering results
to only show probesets with a minimum expression of log2(10) on at least two
arrays

min.present.no. - this is the minimum number of arrays a probeset must be
called present on to be included in the analysis...in your case you have it
set at 4.This means you are filtering your results to only include probesets
that are present on at least 4 arrays.  Again the number here very much
depends on your experiment, the number of groups you have and the number of
arrays. In a simple experiment comparing 2 conditions using 3 arrays in each
condition, I would set it at 2 or 3 (so the probeset has to be called
present on half of the arrays in your experiment)

present.by.group - this allows you to further specify how your present calls
are. You have set it at FALSE, so your results are filtered to only show
those probesets that are called present on at least 4 arrays in the whole
experiment. If you set it to TRUE, then the probeset must be called present
on at least 4 arrays in one of your conditions. Again what you set it at
depends on your experiment. In my simple 6 array, 2 condition experiment I
would set it to TRUE meaning my results will only include probesets that are
present on at least 2 arrays in either condition. This allows you to account
for probesets which may be absent in one condition, but present in another

try typing openVignette() in your R session and selecting simpleaffy.

hope this helps

claire

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