Dear James,

thanks for the support and good remarks.


Amanda Freire de Assis, MSc
Molecular Immunogenetics Group
University of São Paulo
Av. Bandeirantes, 3900
14049-900 - Ribeirão Preto - Brazil
+55 16 36023246

----- James W. MacDonald <jmacdon@uw.edu> escreveu:
> Hi Amanda,
> 
> Please don't take conversations off-list (e.g., use Reply-All).
> 
> On 1/23/2014 1:21 PM, amandafassis@usp.br wrote:
> > Thank you very much James!
> >
> > In fact I had already done a test using readmaimages from limma 
> > package that worked very well inputting the data. :
> >
> > >library(limma)
> > > targets<-readTargets("targets.txt")
> >
> > >x<-read.maimages(targets, source="agilent", green.only=TRUE)
> >
> > But I couldn't go further on pre processing data wijt Agi4x44 because 
> > I got another error:
> >
> > Erro em BGandNorm(x, BGmethod = normexp, NORMmethod = quantile, 
> > foreground = MedianSignal, :
> >  'input' must be a RGList
> >
> > It seems that this package doesn't deal with single channel arrays... 
> > Do you know something about that?
> 
> I haven't used Agi4x44PreProcess for a while now. I am not that familiar 
> with the Agilent 4x44 arrays - I have only used the Salmonid arrays 
> designed by the Koop lab, which are single color, so maybe there are two 
> color 4x44 arrays out there that I don't know about. But if you look at 
> the code for read.AgilentFE and BGandNorm, you can see that the author 
> has done a bunch of work to stuff the results into an RGList, and then 
> work within that framework. In other words, Agi4x44PreProcess sort of 
> pretends that these arrays are two color even if they are not, and has 
> to do a bunch of extra work because there is only data in one channel.
> 
> That is weird to me, as there is the EList structure, which is designed 
> specifically for single color spotted arrays, but maybe 
> Agi4x44PreProcess precedes the addition of EList to limma. I really 
> don't know. But anyway, it is much easier and (to me) safer to just use 
> limma directly:
> 
> x <- read.maimages(targets, source = "agilent", green.only = TRUE)
> x <- backgroundCorrect(x, method = "normexp")
> x <- normalizeBetweenArrays(x, method = "quantile")
> 
> Then you can filter out probes that are just above background if you 
> like, and go directly on to model fitting. There is a worked example for 
> these arrays in the limma User's Guide, starting on page 110 that you 
> might like to read.
> 
> Best,
> 
> Jim
> 
> 
> >
> >
> > Amanda Freire de Assis, MSc
> > Molecular Immunogenetics Group
> > University of São Paulo
> > Av. Bandeirantes, 3900
> > 14049-900 - Ribeirão Preto - Brazil
> > +55 16 36023246
> >
> > ----- James W. MacDonald  escreveu:
> > > Hi Amanda,
> > >
> > > On 1/23/2014 12:04 PM, Amanda F A Riccardi [guest] wrote:
> > > > Hello everybody!
> > > >
> > > > I'm using Agi4x44Preprocess package to deal with pre processing 
> > Agilent single color 4x44 whole mouse genome array, which data were 
> > obtained using feature extraction software.
> > > > The problem is that I can't download my data with the function 
> > read.AgilentFE, I got an error - showed below - and the script just 
> > stop and, instead mine, the author's example data is imported... I 
> > used read.maimages function of the package limma as an alternative, 
> > but I really would like to know what is wrong using read.AglentFE.
> > > > Regards,
> > > > Amanda
> > > >
> > > > -- output of sessionInfo():
> > > >
> > > >> targets <- read.targets(infile="targets.txt")
> > > >
> > > > Target File
> > > > FileName Treatment Gerep
> > > > CT1 CT1.txt CT 1
> > > > CT2 CT2.txt CT 1
> > > > CT3 CT3.txt CT 1
> > > > TT1 TT1.txt TT 2
> > > > TT2 TT2.txt TT 2
> > > > TT3 TT3.txt TT 2
> > > > PT1 PT1.txt PT 3
> > > > PT2 PT2.txt PT 3
> > > > PT3 PT3.txt PT 3
> > > >
> > > >> dd <-read.AgilentFE(targets,makePLOT=TRUE)
> > > > Read CT1.txt
> > > > Read CT2.txt
> > > > Read CT3.txt
> > > > Read TT1.txt
> > > > Read TT2.txt
> > > > Read TT3.txt
> > > > Read PT1.txt
> > > > Read PT2.txt
> > > > Read PT3.txt
> > > > INPUT DATA DOES NOT CONTAIN - Sequence and chr_coord
> > > > SCANN THE DATA USING AFE 9.5.3.1
> > >
> > > ^^^^^^^^^ That is supposed to be your hint. What it means is that the
> > > sequence and chromosome coordinate data are not available, and that you
> > > should use Agilent Feature Extraction version 9.5.3.1 (or higher, I
> > > presume).
> > >
> > > If you don't have these data available, read.AgilentFE() will fail, as
> > > this test is hard-coded into the function. In other words, unless you
> > > upgrade your AFE version, you will have to use read.maimages() directly.
> > >
> > > Best,
> > >
> > > Jim
> > >
> > >
> > > > Erro em read.AgilentFE(targets, makePLOT = TRUE) :
> > > > the script will stop now
> > > >
> > > >
> > > > --
> > > > Sent via the guest posting facility at bioconductor.org.
> > > >
> > > > _______________________________________________
> > > > Bioconductor mailing list
> > > > Bioconductor@r-project.org
> > > > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > > > Search the archives: 
> > http://news.gmane.org/gmane.science.biology.informatics.conductor
> > >
> > > --
> > > James W. MacDonald, M.S.
> > > Biostatistician
> > > University of Washington
> > > Environmental and Occupational Health Sciences
> > > 4225 Roosevelt Way NE, # 100
> > > Seattle WA 98105-6099
> > >
> 
> -- 
> James W. MacDonald, M.S.
> Biostatistician
> University of Washington
> Environmental and Occupational Health Sciences
> 4225 Roosevelt Way NE, # 100
> Seattle WA 98105-6099
> 


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