Sounds like the aroma.affymetrix package is what you want - it's preprocessing takes CEL files as input and outputs CEL files; http://www.braju.com/R/aroma.affymetrix/ /H On Thu, Oct 15, 2009 at 1:23 PM, Leonardo K. Shikida <shikida at="" gmail.com=""> wrote: > wow > > I'll give it a try! thanks! > > [] > > Kenji > > > > On Thu, Oct 15, 2009 at 5:22 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/xp sPreprocess.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 >>>>> >>>>> _______________________________________________ >>>>> Bioconductor mailing list >>>>> Bioconductor at stat.math.ethz.ch >>>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>>> Search the archives: >>>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>>> >>>> >>>> -- >>>> 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 >>>> >>>> >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at stat.math.ethz.ch >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >>> >> >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >

Dear Kenji, Please have a look at the help file "?export" which shows you how to save the results as text files. If you set parameter "as.dataframe=TRUE" the text file will be automatically imported into R as data.frame. Best regards Christian Leonardo K. Shikida wrote: > 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/xp sPreprocess.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 >>>>> >>>>> _______________________________________________ >>>>> Bioconductor mailing list >>>>> Bioconductor at stat.math.ethz.ch >>>>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>>>> Search the archives: >>>>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>>>> >>>>> >>>> -- >>>> 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 >>>> >>>> >>>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor at stat.math.ethz.ch >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >>> >>> >> > >