Dear Erika,
I am learning to use the same package and it is suitable for both single and 2 color analyses.

Harrys

--- On Tue, 2/3/09, Erika Melissari <erika.melissari@bioclinica.unipi.it> wrote:
From: Erika Melissari <erika.melissari@bioclinica.unipi.it>
Subject: Re: [BioC] agi4x44kpreprocess package
To: "Sean Davis" <seandavi@gmail.com>
Cc: bioconductor@stat.math.ethz.ch
Date: Tuesday, February 3, 2009, 5:09 PM

Hello Sean,

then perhaps does agi4x44preprocess package analyze only Agilent one-color
microarray?
Vignette of this package
(http://www.bioconductor.org/packages/2.3/bioc/vignettes/Agi4x44PreProcess/inst/doc/Agi4x44PreProcess.pdf)

indicates a template of targets like this:

> targets

            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

and specify that:

In the target le, the fields Filename, Treatment and GErep are mandatory.

For each microarray, the target file reports information for only one subject
on each array and not two. Moreover, for each array only one treatment is
defined.

Is  this a clue of analysis of one-color microarray only?

If the answer is yes...could you suggest to me an R or Bioconductor package
that performs the same as agi4x44preprocess package but for two color
microarrays?

thank you a lot

Erika


----- Original Message ----- 
  From: Sean Davis 
  To: Erika Melissari 
  Cc: Francois Pepin ; bioconductor@stat.math.ethz.ch 
  Sent: Tuesday, February 03, 2009 17:33 PM
  Subject: Re: [BioC] agi4x44kpreprocess package





  On Tue, Feb 3, 2009 at 10:54 AM, Erika Melissari
<erika.melissari@bioclinica.unipi.it> wrote:

    Hello Francois,

    thank you for your help.

    here is the sessionInfo() output

    R version 2.8.0 (2008-10-20)
    i386-pc-mingw32

    locale:
    LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

    attached base packages:
    [1] splines   tools     stats     graphics  grDevices utils     datasets
methods
    [9] base

    other attached packages:
    [1] hgug4112a.db_2.2.5      RSQLite_0.7-1           DBI_0.2-4
    [4] Agi4x44PreProcess_1.2.0 genefilter_1.22.0       survival_2.34-1
    [7] annotate_1.20.1         xtable_1.5-4            AnnotationDbi_1.4.1
    [10] limma_2.16.3            Biobase_2.2.1

    I realized that this package is wrapped around limma, but the result of
read.maimages is not the same.
    I have checked, comparing the loaded data with raw data, what date have
been loaded by using read.AgilentFe of agi4x44preprocess and, really, only the
green signals are loaded. Obviously, the read.maimages() load the correct data
(I have checked).
    The problem is that agi4x44preprocess vignette also affirm that the signals
loaded are the green signals...but I do not understand why only green!

  For gene expression arrays, Agilent has been advocating single-channel
protocols for a couple of years.  There are groups for which that is the
standard.

  Sean

   

    I am evaluating this package because it offer some functions for managing
the huge amount of data (processed signals, mean signals and, above all, the
flags) extracted by using Feature extraction software by Agilent. I would like
to use the complicated system of Agilent flags for quality control of my
microarray data and only this package manages to do this.
    Thank you for any suggestion.

    Erika

    ----- Original Message ----- From: "Francois Pepin"
<fpepin@cs.mcgill.ca>
    To: "Erika Melissari" <erika.melissari@bioclinica.unipi.it>
    Cc: <bioconductor@stat.math.ethz.ch>
    Sent: Tuesday, February 03, 2009 16:20 PM
    Subject: Re: [BioC] agi4x44kpreprocess package



      Hi Erika,

      I have never used that package, but it seems to be mostly a wrapper
      around limma for those steps. What happens if you use
      read.maimages(files, source='agilent') directly?

      You might also want to make sure that you have red values if you look
      directly in your raw text file.

      And please post the output from sessionInfo(). This will make it easier
      for people to understand which type of installation you have, and
      generally makes it easier to catch if the problem.

      Francois

      Erika Melissari wrote:

        Hello all,

        does anyone know Agi4x44kPreProcess package?
        I'm exploring it to perform pre-process steps on human 4x44k
Agilent microarrays, but I have a question or perhaps a doubt: why does this
package load only the green signals (processed, mean, ect.) and not the red
signals?
        Is it an error of this package or a characteristic?
        Thank you so much for any indication

        Erika

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