[BioC] cDNA raw intensities

[Sean Davis]

On Wed, Dec 3, 2008 at 3:17 AM, santana sarma <aimanusarma at gmail.com> wrote:
> Thanks !
>
> Well, it is the simplest type of microarray experiment, with replicate
> two-color arrays of the same two RNA sources. It has its dyes swapped for
> one of the arrays:
>
> -------------------------------------------------------------
>
> File                               cy3                   cy5
>
> -------------------------------------------------------------
>
> a                                  wt                    mu
>
> b                                  wt                    mu
>
> c_DyeSwap                 mu                    wt
>
>
>
> Wonder how to go for the annotated output for my gene list (before
> downstream statistical analysis). User guides of LIMMA and others mainly
> focus on how to obtain statistics with regards to differential expression et
> al.

The annotation is in RG$genes.  You can make a data.frame that
includes the gene annotation and your values using cbind().  Then, you
can use write.csv on that data.frame to make a text file.

Sean


> On Wed, Dec 3, 2008 at 3:42 AM, Naomi Altman <naomi at stat.psu.edu> wrote:
>
>> Dear Santana
>>
>> This does not really help much, because the "normalized expression" depends
>> on the treatment.  Do both channels have the same treatment?  Is this a
>> reference design?
>>
>> Anyways, to do what you want, what I generally do is use cbind to merge the
>> expression values with the annotation information and write.csv to write a
>> comma separated table which can be read into a spreadsheet such as Excel.  I
>> do not expect to be able to do all my processing in R.  However, some of the
>> R gurus on the list can probably do everything in R.  I meant
>> to cc the list when I first wrote, and I am returning this to you.
>>
>> Best of luck,
>> Naomi
>>
>>
>> At 04:31 AM 12/2/2008, you wrote:
>>
>> Hi Naomi,
>>
>> Thanks for your prompt reply !
>>
>> Well, I wanted to experiment something, and accordingly thought that I
>> would examine the individual raw data. But I believe, I should follow the
>> conventional way, atleast for the time-being.
>>
>> Anyways, even then I have a bit of problem.
>>
>> I am uncertain as to how I can have each gene's normalised expression along
>> with its annotation in one file. I am able to do it for Affymetrix data
>> which is not very complicated, but I'm having problems in trying to do it
>> with cDNA microarrays (for 3-biological replicates where one of them is a
>> dye-swap).
>>
>> Let's say, in a nutshell, I have already done with the following :
>>
>> library(arrayQuality); library(graphics); library(RColorBrewer)
>>
>> targets <- readTargets("target77.txt")
>>
>> files <- c("a.gpr", "b.gpr", "c_DyeSwap.gpr")                 # Suppose
>> these are my files
>>
>> RG <- read.maimages (files,source="genepix")
>>
>> RG$printer <- getLayout(RG$genes)                        # to set print
>> layout
>>
>> RG.b <- backgroundCorrect(RG)
>>
>> MA.RG <- normalizeWithinArrays (RG.b)
>>
>> MA.BT <http://ma.bt/> <- normalizeBetweenArrays (MA.RG)
>>
>> design  <- c(1,1,-1)
>>
>> # from here, I don't know how to move ahead that would give me a file
>> (.HTML/.csv) that would contain each gene's normalised expression with its
>> annotation.
>>
>> I would highly appreciate your suggestion(s).
>>
>> Thanks !!
>>
>> Kind regards,
>>
>> Santana
>> = = = = = = = = =
>>
>> On Tue, Dec 2, 2008 at 5:43 PM, Naomi Altman <naomi at stat.psu.edu> wrote:
>>  Are you sure you want the RAW intensities.  That would mean unaltered
>> data.  I think you want a normalized
>> mean intensity.  You could do that in limma using the single channel
>> analysis.   Limma can produce means - not just differences.
>>
>> Naomi Altman
>>
>>
>> At 11:23 PM 12/1/2008, you wrote:
>>  Hi All,
>>
>> I am in need of some basic 2-color (cDNA) microarray help.
>>
>> With 3-biological replicates (one of them is a dye-swap), I wish to merge
>> ONLY the raw intensities of the 3 cDNA files. This merging should take into
>> account of the dye-swap file too. Finally, it should produce an HTML (or,
>> CSV) file that contains ONE raw expression against each available gene with
>> the relevant annotation.
>>
>> I am not confident as to how I should script it. I did go through some
>> packages like LIMMA, but couldn't really extract what I wanted, as they
>> focus mainly on statistics for differential expression.
>>
>> Thank you !
>>
>> Cheers,
>> Santana
>>
>>        [[alternative HTML version deleted]]
>>
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>>
>>
>> Naomi S. Altman                                814-865-3791 (voice)
>> Associate Professor
>> Dept. of Statistics                              814-863-7114 (fax)
>> Penn State University                         814-865-1348 (Statistics)
>> University Park, PA 16802-2111
>>
>>  Naomi S. Altman                                814-865-3791 (voice)
>> Associate Professor
>> Dept. of Statistics                              814-863-7114 (fax)
>> Penn State University                         814-865-1348 (Statistics)
>> University Park, PA 16802-2111
>>
>
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>
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