Hello, I hybridized for two samples both Cy3-Label and Cy5-Label to one chip (i.e. wtCy3+wtCy5 and mutantCy3+mutantCy5. I would like to normalize that data, but how? I tried to use the array2channel funtion, but how do I use the result? My targets looking like this: FileName Cy3 Cy5 1 e85b.txt WT WT 2 e87b.txt WT WT 3 e88b.txt 139 139 4 e89b.txt 139 139 After array2channel: Channel FileName Target 1.1 1 e85b.txt WT 1.2 2 e85b.txt WT 2.1 1 e87b.txt WT 2.2 2 e87b.txt WT 3.1 1 e88b.txt 139 3.2 2 e88b.txt 139 4.1 1 e89b.txt 139 4.2 2 e89b.txt 139 Can I get a model.Matrix out of that? Or is it not possible to normalize that way of hybridization? Thanks! Sebastian [[alternative HTML version deleted]]

The problem with your method is not normalization but confounding. Genotype differences and array effects cannot be distinguished in this design. --Naomi Altman At 11:23 AM 7/14/2004 +0200, S_Thieme wrote: >Hello, > >I hybridized for two samples both Cy3-Label and Cy5-Label to one chip (i.e. >wtCy3+wtCy5 and mutantCy3+mutantCy5. >I would like to normalize that data, but how? >I tried to use the array2channel funtion, but how do I use the result? > >My targets looking like this: > FileName Cy3 Cy5 >1 e85b.txt WT WT >2 e87b.txt WT WT >3 e88b.txt 139 139 >4 e89b.txt 139 139 > >After array2channel: > Channel FileName Target >1.1 1 e85b.txt WT >1.2 2 e85b.txt WT >2.1 1 e87b.txt WT >2.2 2 e87b.txt WT >3.1 1 e88b.txt 139 >3.2 2 e88b.txt 139 >4.1 1 e89b.txt 139 >4.2 2 e89b.txt 139 > >Can I get a model.Matrix out of that? Or is it not possible to normalize >that way of hybridization? > >Thanks! > >Sebastian > > [[alternative HTML version deleted]] > >_______________________________________________ >Bioconductor mailing list >Bioconductor@stat.math.ethz.ch >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Bioinformatics Consulting Center Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111

> Hello, > > I hybridized for two samples both Cy3-Label and Cy5-Label to one chip > (i.e. > wtCy3+wtCy5 and mutantCy3+mutantCy5. Why did you do this? Your only option now is to do a single-channel analysis, comparing treatments across arrays, and this is an order of magnitude less efficient than a direct comparison using Cy3 and Cy5 channels. Anyway, in limma you could use MA <- normalizeBetweenArrays(yourRGList, method="quantile") targetsC <- array2channel(yourtargets) design <- model.matrix(~factor(targetsC$Target)) cor.fit <- intraspotCorrelation(MA,design) fit <- lmscFit(MA,design,correlation=cor.fit$consensus) fit <- eBayes(fit) topTable(fit,coef=2) You will have to make sure that yourRGList contains no negative or missing background-adjusted intensities before using the above. You could use for example RG <- backgroundCorrect(RG, method="normexp") or similar to ensure this. Gordon > I would like to normalize that data, but how? > I tried to use the array2channel funtion, but how do I use the result? > > My targets looking like this: > FileName Cy3 Cy5 > 1 e85b.txt WT WT > 2 e87b.txt WT WT > 3 e88b.txt 139 139 > 4 e89b.txt 139 139 > > After array2channel: > Channel FileName Target > 1.1 1 e85b.txt WT > 1.2 2 e85b.txt WT > 2.1 1 e87b.txt WT > 2.2 2 e87b.txt WT > 3.1 1 e88b.txt 139 > 3.2 2 e88b.txt 139 > 4.1 1 e89b.txt 139 > 4.2 2 e89b.txt 139 > > Can I get a model.Matrix out of that? Or is it not possible to normalize > that way of hybridization? > > Thanks! > > Sebastian