[BioC] RMA + loess normalisation and filtering

[Katleen De Preter]

Dear BioC-users,

question 1: I have performed *RMA normalisation *of my Affymetrix data. 
However, for further analysis I think it is necessary to *filter* the 
data (non-expressed genes or below background). However I don't know the 
best way to filter the genes that are not expressed or very low 
expressed (below the background), based on the RMA normalisation data.

question 2: In a paper of Choe et al (2005, Genome Biology) I have read 
that *loess normalisation *after the first normalisation step is 
important in order to detect most true positive differentially expressed 
genes. However when I perform
/>normdatabis<-normalize.exprSet.loess(RMAdata,transfn="antilog")/
following warnings appear: /k-d tree limited by memory ncmax=5002/
I guess that the loess normalization was only based on the 5002 first 
probe set id's or what does this mean?
Is it ok or do I need to follow another strategy for the second loess 
normalisation step?

Best regards,
katleen de preter









-- 
*dr. ir. Katleen De Preter*
Center for Medical Genetics Ghent (CMGG)
Ghent University Hospital
Medical Research Building (MRB), 2nd floor, room 120.038
De Pintelaan 185, B-9000 Ghent, Belgium
+32 9 240 5533 (phone) | +32 9 240 6549 (fax)
http://medgen.ugent.be
Katleen.DePreter at UGent.be <mailto:Katleen.DePreter at UGent.be>

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