Hello,

To read.maimages with Limma do you need to parse Agilent headers from 
txt files ?
I had some troubles with marray pacakge using read.Agilent function.

Best,

Guillermo.

On 06/21/2013 04:18 PM, James W. MacDonald wrote:
> Hi Guillermo,
>
> On 6/21/2013 3:06 AM, Guillermo Marco Puche wrote:
>> Dear Gordon,
>>
>> Thank you for your answer. I'll look further into Agilent array image
>> files with limma.
>>
>> As I said the problem is that i'm not currently reading image from
>> Agilent array, but the text data file with marray library and loading it
>> into a maData object like this:
>
> Please note that the read.maimages function doesn't read image files - 
> it reads in the same text files you are reading with read.Agilent.
>
> Your original question had to do with the 'correct' background 
> correction to use for your Agilent array data. Gordon has therefore 
> suggested that you use the 'normexp' method in limma. This does of 
> course require you to switch to a different package, but limma tends 
> to get better support than marray, so you might be wise to make the 
> switch.
>
> But to your original point, you are asking a question that might not 
> have a definitive answer. There is no 'best' way to do a background 
> correction. There are methods that seem to do a reasonable job over a 
> range of experiments, and if I understand correctly, this is why 
> Gordon is suggesting you use normexp. But which method might be best 
> for your particular situation will be difficult for anybody to predict.
>
> Best,
>
> Jim
>
>
>>
>> maData = read.Agilent(fnames=input , path=NULL, name.Gf = 
>> "gMedianSignal", name.Gb = "gBGMedianSignal", name.Rf = 
>> "rMedianSignal", name.Rb = "rBGMedianSignal", name.W= NULL, layout = 
>> NULL, gnames = NULL, targets = NULL, notes=NULL, skip=NULL, sep="\t", 
>> quote="\"", DEBUG=FALSE, info.id=NULL)
>>
>>
>>
>>
>>> On 06/20/2013 01:11 PM, Gordon K Smyth wrote:
>>>> Dera Guillermo,
>>>>
>>>> The usual process is to (1) background correct the foreground
>>>> intensities with respect to the background, then (2) normalize the
>>>> M-values (log-ratios).
>>>>
>>>> For an Agilent two colour array, I do this by:
>>>>
>>>>    library(limma)
>>>>    RG<- read.maimages(files, source="agilent")
>>>>    RGb<- backgroundCorrect(RG, method="normexp")
>>>>    MA<- normalizeWithinArrays(RGb, method="loess")
>>>>
>>>> although it is sometimes a good idea to remove positive control
>>>> probes before the normalization step.
>>>>
>>>> A recent example using this pipeline is:
>>>>
>>>> http://www.biomedcentral.com/1471-2105/14/165
>>>>
>>>> Best wishes
>>>> Gordon
>>>>
>>>>> Date: Wed, 19 Jun 2013 22:38:34 +0200
>>>>> From: Guillermo Marco Puche<guillermo.marco@sistemasgenomicos.com>
>>>>> To: "bioconductor@r-project.org"<bioconductor@r-project.org>
>>>>> Subject: [BioC] Normalize background on marray Agilent object
>>>>>
>>>>> Hello,
>>>>>
>>>>> I'm currently trying to normalize rBG values for a marray object.
>>>>> Data origin is Agilent dual channel array. I've loaded information 
>>>>> with
>>>>> readAgilent() function.
>>>>>
>>>>> What's the correct way to normalize the data? I would like to 
>>>>> normalize
>>>>> background information first maNorm function manual isn't very
>>>>> clarifying for me.
>>>>>
>>>>> Thanks !
>>>>>
>>>>> Best regards,
>>>>> Guillermo.
>>>>
>>>> ______________________________________________________________________
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