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 [[alternative HTML version deleted]]

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 [[alternative HTML version deleted]]

Dear Erika, If you give zero weight to all values for a probe, that has the same effect as regards the linear model as removing the probe entirely. Best wishes Gordon > Date: Mon, 20 Oct 2008 12:22:26 +0200 > From: "Erika Melissari" <erika.melissari at="" bioclinica.unipi.it=""> > Subject: [BioC] Removing control probes before fitting the linear > model > To: <bioconductor at="" stat.math.ethz.ch=""> > Message-ID: <006101c9329d$bff5efb0$ba517283 at maanalysis> > Content-Type: text/plain > > 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