Hi, First you need to read the target file targets=read.targets(infile='target.file.name.txt') and then your data files dd=read.AgilentFE(targets,makePLOT=FALSE) *this* reads the data files into R and and creates an *RGList* object that contains the following variables: the scanned mean raw signal of the feature (*gMeanSignal*), the processed signal computed by the AFE algorithms (* gProcessedSignal*), the median local background signal (*gBGMedianSignal*), the AFE processed background signal (*gBGUsed*). The *gProcessedSignal* is obtained after all the AFE processing signal steps have been completed, so if you use this signal, you only need to normalize between arrays using quantile and not vsn. If you want to use the raw signal, you will probably need to make some background correction first, or just use vsn. You can select the signal and methods that you wanna use, as for example like this: foreground="MeanSignal" background="BGUsed" BGmethod="normexp" NORMmethod="quantile" offset=50 makePLOTpre=FALSE makePLOTpost=TRUE ddNORM=BGandNorm(dd,BGmethod,NORMmethod, foreground,background, offset,makePLOTpre,makePLOTpost) The target file is a tab-delimited text, organized by rows and columns, that assigns each data file to a given experimental condition. Just, open (for example an excel file) and create this file and saved it as txt, as in the example above 'target.file.name.txt'. In more detail, *Agi4x44PreProcess *requires three columns to be defined in the target file with specific names. The first column must be named * FileName* and it includes the data files names as they are in the working directory. The second column must be called *Treatment* and it contains the particular treatment effect level for each data file. The treatment effect defines the levels of the experimental conditions that we want to compare in our study. The third column must be named *GErep* and it defines the levels of the treatment effect using a numeric code, from 1 to *k*, being *k* the number of levels of the treatment effect. The filtering of the probes is done according to the level of the treatment effect. *Agi4x44PreProcess*uses the numerical *GErep* code so a bad codification may originate an error message. HTH. p.- On Tue, Apr 28, 2009 at 8:14 AM, Bernal-Mizrachi, Leon <lbernal@emory.edu>wrote: > Dear Massimo, > > Thanks for your replay. > > I have 2 silly question and I apologize for it. > > 1. In the agilent platform there is several signals: > gProcessedsignal,gMeanProcessedSignal,gMeanSignal and gBGMeanSignal. I > understand that we can used the gMean and the gBGmean to substract the > background. however what are those gProcessed and gMean? > > 2. If I have 18 samples and I want to creat the "targets.txt" data frame, > how can I create it. In another words, looking at the vignette, how can I > create a table such as: > > FileName Treatment GErep Subject Array > Ast Ast.txt st 1 A 1 > Bst Bst.txt st 1 B 1 > Aunst Aunst.txt unst 2 A 1 > Bunst Bunst.txt unst 2 B 1 > > or how can I load my data into one onlyl file that I can call "targets" > and that has only the whatever signal you suggest I could use from question > 1? > > Sorry for this probably elemental question, I am trying to troubleshoot > this platform. > > Thanks again > > > Leon Bernal-Mizrachi, MD > Assistant Professor, Hematology/Medical Oncology > Emory University School of Medicine > Winship Cancer Institute > 1365 Clifton Rd NE, C-3005 > Atlanta, GA 30322 > Phone: 404-778-1839 > Fax: 404-778-5520 > Email: lbernal@emory.edu > > Admin. Asst. > Erica Alston > 404-778-5378 > Erica.alston@emoryhealthcare.org > > ________________________________________ > From: Massimo Pinto [pintarello@gmail.com] > Sent: Monday, April 27, 2009 4:16 AM > To: Bernal-Mizrachi, Leon > Subject: Re: Problem loading data for Agi4x44PreProcess > > Leon, > > you mau need to avoid calling the data() function as at the example. That > function calls in a sample targets file from the bundle, and it will > over-ride yours. > Yours > Massimo > > -- > Massimo Pinto > Post Doctoral Research Fellow > Enrico Fermi Centre and Italian Public Health Research Institute (ISS), > Rome > http://claimid.com/massimopinto > > This e-mail message (including any attachments) is for...{{dropped:13}}