[BioC] LIMMAing normalized and background corrected MA-data derived by a text file

["Gläßer, Christine"]

Dear all,

I have two-color microarray data, which was given to me after normalization (lowess) and background correction in a text file. Thus, the data looks like: probe ID - Gene name - red signal - green signal, no background information is left. I use read.maimages for reading the data in:

MA <- read.maimages(targets,  columns=list(G="mutant",R="control"), annotation=c("Name", "ID"))

Subsequently, I'd like to analyze these data ommitting the normalization and background correction, since it is already normalized and background corrected. However, lmFit only accepts MALists (and others, just as example here), and I'm not sure how to convert the data appropriate. How should I set the M-value and the A-value, for example? Is it even possible to analyze those data ommitting normalization and background correction and directly start with lmFit and subsequent steps? Or did someone else encounter a similar problem and could tell me her/his way of dealing with these data?

Best regards, and thank you,


Christine Gläßer


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Christine Gläßer
Institute of Bioinformatics and Systems Biology

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