Hi, I am analysing 1-color Agilent microarray data and I wonder what is the best variable(s) to use among the numerous variables provided by the Feature Extraction software from Agilent. Should I use the "ProcessedSignal", which according to Agilent documentation is the signal left after all pre-processing steps have been completed and contains the "Multiplicatively Detrended BackgroundSubtracted Signal" , or the "BGSubSignal" which equals to the feature signal after background subtraction (using a spatial detrend algorithm for background correction), or is it better to import the raw MeanSignal and BGMeanSignal (or Median Signal) and use the limma package to do background correction (as done in the Agi4x44preprocess package)? Does anybody have some experience in using these different feature signals ? Thank you for any help Christian -- Christian Brière UMR CNRS-UPS 5546 BP42617 Auzeville F-31326 Castanet-Tolosan (France) tel: +33(0)5 62 19 35 90 Fax: +33(0)5 62 19 35 02 E-mail: briere@scsv.ups-tlse.fr <mailto:briere@scsv.ups-tlse.fr> http://www.scsv.ups-tlse.fr http://www.gdr2688.ups-tlse.fr <http: www.gdr2688.ups-="" tlse.fr="" index.php=""> http://www.ifr40.cnrs.fr [[alternative HTML version deleted]]

Salut Christian, It depends on the normalization scheme that you want. The Feature Extraction software offers one set of normalization among many. We use the r/gMeanSignal and then do the background correction and normalization ourselves (using limma, but others exist). This grants us more control and more choice over what happens. Other people prefer the median signals instead, but we haven't found it to make much of a difference. A lot depends on your experiments and which kinds of technical variation are the most prevalent. You would probably be better to explore the data by yourself and decide what works well for you. Francois Christian Bri?re wrote: > Hi, > > I am analysing 1-color Agilent microarray data and I wonder what is the > best variable(s) to use among the numerous variables provided by the > Feature Extraction software from Agilent. > Should I use the "ProcessedSignal", which according to Agilent > documentation is the signal left after all pre-processing steps have > been completed and contains the "Multiplicatively Detrended > BackgroundSubtracted Signal" , or the "BGSubSignal" which equals to the > feature signal after background subtraction (using a spatial detrend > algorithm for background correction), or is it better to import the raw > MeanSignal and BGMeanSignal (or Median Signal) and use the limma package > to do background correction (as done in the Agi4x44preprocess package)? > Does anybody have some experience in using these different feature signals ? > Thank you for any help > Christian > > > > > -------------------------------------------------------------------- ---- > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

Hi, With Agi4x44PreProcess you can use either the Raw Mean Signal and do some background correction, or you can use the ProcessedSignal and go straight to the normalization between arrays. What sort of signal you use it´s up to you. Usually, I take the Raw Mean Signal and apply the half BG correction. My experience is that the kind of signal used does not influence a lot the results on diferential expression, and you end up with similar lists of genes that are differentially expressed. p.- ________________________________ From: bioconductor-bounces@stat.math.ethz.ch on behalf of Christian Brière Sent: Tue 2/17/2009 11:34 AM To: BioC Subject: [BioC] Analysing Agilent microarray data Hi, I am analysing 1-color Agilent microarray data and I wonder what is the best variable(s) to use among the numerous variables provided by the Feature Extraction software from Agilent. Should I use the "ProcessedSignal", which according to Agilent documentation is the signal left after all pre-processing steps have been completed and contains the "Multiplicatively Detrended BackgroundSubtracted Signal" , or the "BGSubSignal" which equals to the feature signal after background subtraction (using a spatial detrend algorithm for background correction), or is it better to import the raw MeanSignal and BGMeanSignal (or Median Signal) and use the limma package to do background correction (as done in the Agi4x44preprocess package)? Does anybody have some experience in using these different feature signals ? Thank you for any help Christian -- Christian Brière UMR CNRS-UPS 5546 BP42617 Auzeville F-31326 Castanet-Tolosan (France) tel: +33(0)5 62 19 35 90 Fax: +33(0)5 62 19 35 02 E-mail: briere@scsv.ups-tlse.fr <mailto:briere@scsv.ups-tlse.fr> http://www.scsv.ups-tlse.fr http://www.gdr2688.ups-tlse.fr <http: www.gdr2688.ups-="" tlse.fr="" index.php=""> http://www.ifr40.cnrs.fr [[alternative HTML version deleted]] [[alternative HTML version deleted]]