Thanks Mark - your suggestions have solved my problems and everything is 
running quickly and smoothly now!

Mark Robinson wrote:
> Hi Sebastien.
>
> Comments below.
>
>
> On 04/03/2009, at 11:34 AM, Sebastien Gerega wrote:
>
>   
>> Hi Mark,
>> I understand there may be some interesting genes with > 100 probes - I
>> just wanted to test it out to see how it impacted on the run  
>> time......
>> After changing the skip threshold to 500 probes the analysis completed
>> in a similar time to what is required for mogene10st and hugene10st  
>> arrays.
>>
>> I then examined which probes I eliminated by changing the threshold  
>> to 500:
>>     
>>> getUnitNames(cdf)[which((cpu1 > 500))]
>>>       
>> [1] "10700001" "10700003" "10700004" "10700027" "10700052" "10700055"
>> "10700058" "10700059" "10700063" "10700064" "10700065" "10700066"  
>> "10700067"
>>
>> It turns out that all 13 of these probes are listed in the Affymetrix
>> annotation file as being "control->affx". Therefore I assume I can
>> safely remove them from the analysis.
>>
>> I also noticed in the annotation file that there are additional  
>> control
>> probes listed as "control->bgp->antigenomic". Any idea what this  
>> means?
>> Would it be safe to remove them?
>>     
>
> Indeed, you can safely NOT fit a probe level model for these probesets  
> and not be missing anything.  I'm guessing that "bgp" means background  
> probes and "antigenomic" meaning the 25mer sequence does not map  
> anywhere to the (in this case, rat) genome.
>
>
>   
>> And finally, how would I go about removing probes from the analysis?
>>     
>
> You probably just want to remove these probesets at the fitting  
> stage.  My suggestion from before to do this is:
>
> [...]
> plmTr <- RmaPlm(csN, verbose=verbose)
> fit(plmTr, units=u, verbose=verbose)
>
> ... where 'u' is the set of units you want to fit.
>
> Note: if you are reading expression summaries from the ChipEffectSet  
> later, you'll probably also want to specify 'units=u' as well.  If you  
> don't fit a PLM for a given probeset and read ALL the chip effects  
> into a matrix/data.frame, there'll be NAs for those probesets that you  
> didn't fit on.
>
> Hope that helps.
> Mark
>
>
>
>   
>> thanks,
>> Sebastien
>>     
>
>
>
>
>
> >
>
>   


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