[BioC] affy: expresso in separated steps

[Leonardo K. Shikida]

Hi Christian

this seems to be in the right direction, but I could not find any
example of how it explicitly saves intermediary results as text files

thanks in advance

Kenji



On Thu, Oct 15, 2009 at 6:22 PM, cstrato <cstrato at aon.at> wrote:
> Dear Kenji,
>
> Maybe you could use package xps, which has a similar function "express"
> which allows you to do normalization stepwise and save interim results as
> text files for reuse, see e.g. the recent vignette:
> http://bioconductor.org/packages/2.5/bioc/vignettes/xps/inst/doc/xpsPreprocess.pdf
> and the script in xps/examples/script4xpsPreprocess.R
>
> Best regards
> Christian
> _._._._._._._._._._._._._._._._._._
> C.h.r.i.s.t.i.a.n   S.t.r.a.t.o.w.a
> V.i.e.n.n.a           A.u.s.t.r.i.a
> e.m.a.i.l:        cstrato at aon.at
> _._._._._._._._._._._._._._._._._._
>
>
> Leonardo K. Shikida wrote:
>>
>> Hi James
>>
>> thanks for the fast answer
>>
>> I am afraid I can't do that. The idea here is to reuse some other
>> normalization methods (not implemented in R), so I'd have to, somehow,
>> save these intermediary results, perform another normalization method,
>> then restore this normalized data to perform summarization, etc
>>
>> The problem, as you've pointed out, is that affy abstracts the
>> internal data structure to make my life easier. My work will probably
>> need to deal with this internal structure somehow.
>>
>> Maybe I could just save the object, export PM and MM data as CSV,
>> perform the normalization, then restore the object using the load
>> command and overwrite its PM and MM data with the normalized CSV
>> files...
>>
>> Sounds like an horrible way to deal with this situation :-) so I am
>> open to better ideas...
>>
>> []
>>
>> Kenji
>>
>>
>>
>> On Thu, Oct 15, 2009 at 5:00 PM, James W. MacDonald
>> <jmacdon at med.umich.edu> wrote:
>>
>>>
>>> Hi Kenji,
>>>
>>> Leonardo K. Shikida wrote:
>>>
>>>>
>>>> Hi
>>>>
>>>> I'd like to know how to perform affy expresso in separate steps
>>>>
>>>> for example
>>>>
>>>> what I'd like is
>>>>
>>>> CEL data => bg correction => save corrected data into a file X
>>>> load file X => normalization => save normalized data into file Y
>>>> load file Y => summarization => save summarized data into file Z
>>>>
>>>
>>> I wouldn't save things in files. The objects designed to contain your
>>> data
>>> are pretty complex, but are designed to make manipulation of your data
>>> simple. If you write out to files you increase the complexity of dealing
>>> with your data and lose all of the nice functions designed to make your
>>> life
>>> simpler.
>>>
>>> You can instead keep your data in an AffyBatch (until you summarize) and
>>> just save the objects as you go through your process. For instance:
>>>
>>> dat <- ReadAffy()
>>> bgdat <- bg.correct(dat, method)
>>>
>>> ## for methods see bgcorrect.methods()
>>>
>>> normdat <- normalize(bgdat, method)
>>>
>>> ## for methods see normalize.methods(dat)
>>>
>>> eset <- computeExprSet(normdat, summary.method = method, pmcorrect.method
>>> =
>>> pmmethod)
>>>
>>> ## for summary and pmcorrect methods see
>>> express.summary.stat.methods()
>>> pmcorrect.methods()
>>>
>>>
>>>
>>>>
>>>> and so on
>>>>
>>>> it's not clear to me
>>>>
>>>> [1] how to access these intermediary datasets. should I save both
>>>> pm(Data) and mm(Data)?
>>>> [2] if the only thing I need is the intermediary dataset or if I need
>>>> anything alse such as platform info (CDF files for example)
>>>>
>>>
>>> You will need a cdf package. If you are using a commercially available
>>> chip
>>> and just want to use the 'regular' Affy cdf, then you don't need to do
>>> anything. If you don't have the required package it will be downloaded
>>> for
>>> you. If you want to use a different cdf, there is the cdfname argument to
>>> ReadAffy (if BioC has these cdfs; an example would be the MBNI cdfs). If
>>> the
>>> chip isn't commercial, you will need to get the cdf from Affy, build a
>>> package using the makecdfenv package, and then build and install
>>> yourself.
>>>
>>> Best,
>>>
>>> Jim
>>>
>>>
>>>
>>>>
>>>> I hope I've been clear about my doubt
>>>>
>>>> thanks in advance
>>>>
>>>> Kenji
>>>>
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>>>>
>>>
>>> --
>>> James W. MacDonald, M.S.
>>> Biostatistician
>>> Douglas Lab
>>> University of Michigan
>>> Department of Human Genetics
>>> 5912 Buhl
>>> 1241 E. Catherine St.
>>> Ann Arbor MI 48109-5618
>>> 734-615-7826
>>>
>>>
>>
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>
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