[BioC] Normalize background on marray Agilent object

[Gordon K Smyth]

Dear Guillermo,

I already gave you all the code you need to use.  The code already parses 
the header for you.  Could you not posssibly try it before asking more 
questions?

Thanks
Gordon

> Date: Wed, 03 Jul 2013 09:59:42 +0200
> From: Guillermo Marco Puche <guillermo.marco at sistemasgenomicos.com>
> To: bioconductor at r-project.org
> Cc: "James W. MacDonald" <jmacdon at uw.edu>
> Subject: Re: [BioC] Normalize background on marray Agilent object
>
> 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 at sistemasgenomicos.com>
>>>>>> To: "bioconductor at r-project.org"<bioconductor at 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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