[BioC] summarizing probe intensites before or after normalization- 1. how to do with RMA 2. Opinions?

[k. brand]

Ben,

My apologies, i see my error now.

library(affyPLM)
dat <- ReadAffy()
datrma <- rma(dat, normalize=FALSE)
datrma.postqnorm <- normalize(datrma)
boxplot(datrma.postqnorm)

The above worked a treat!

Id still like very much to hear your opinion on whether i might be 
better to normalize before or after summarizing given the variation i 
have to deal with.

thanks again,

Karl

on 9/11/2006 3:51 PM Ben Bolstad said the following:
>> 1. Help to effect Bolstad normalization of the RMA preprocessed and 
>> summarized data. Whilst I succeed in generating unnormalized RMA 
>> preprocessed data with-
>>
>> library(affy)
>> data <- ReadAffy()
>> datarma <- rma(data, normalize=FALSE)
>>
>> As a result of my limited R experience, I failed in finding a method to 
>> effect Bolstad (quantile) normalization on this output.
> 
> library(affyPLM)
> datarma.postqnorm <- normalize(datarma)
> 
> 
> 
> 

-- 
Karl Brand <k.brand at erasmusmc.nl>
Department of Cell Biology and Genetics
Erasmus MC
Dr Molewaterplein 50
3015 GE Rotterdam
lab +31 (0)10 408 7409 fax +31 (0)10 408 9468