Hello,

I found out that in some examples (11.5 and 11.6) of Limma userguide it is suggested the removal of the control probes from the data before fitting the linear model.
Usually I flag negative or positive control spots as "not good" by using a wt.fun function during the loading of the data (e.g. I flag witn 0 all the "not good" spots and with 1 all the "good" spots) and this is because I do not use control spots in order to perform normalizzation of raw data.
So, I do not exclude those spots explicitly before fitting the lienar model, but they receive a weight that differentiate them by the rest of the data.
Is it correct or I have to completely eliminate the control spots?

Thank you very much

Erika

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