On Mon, 2006-09-11 at 16:44 +0200, k. brand wrote: > Ben, > > Thankyou for your fast response. > > I tried your suggested script as: > > library(affyPLM) > dat <- ReadAffy() > datrma <- rma(dat, normalize=FALSE) > datrma.postqnorm <- normalize(datrma) > boxplot(datrma) > try boxplot(datrma.postqnorm) Here is my test code that shows it works library(affyPLM) data(Dilution) rma.nonorm <- rma(Dilution,normalize=FALSE) rma.postnorm <- normalize(rma.nonorm) boxplot(rma.nonorm) boxplot(rma.postnorm) > Im convinced RMA is a superior approach to MAS5. The variation of the > spreads however, compared to normalising in the last stage is > surprising. From "RMA no norm.jpeg" you can see my data is quite > 'divergent' which is exactly why i want to normalize as best i can. But > perhaps RMA is not 'strong' enough to push around such divergence? Based on the plot you sent me: 1) is there a biological reason for the pattern I see (ie first two low, next two high, next two low ....) or is this some sort of technical artifact. 2) Have you carried out any quality assessment?