combining hgu133a and hgu133b
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@mayte-suarez-farinas-2068
Last seen 9.0 years ago
United States
Hi all, I have HGU133a , HGU133b chips done in the same set of samples. Additionally I have hgu133plus2 chips in a different set of samples. Since "a+b" is almost "plus2", is tehre a way to combinethose two affybatchs ? Any guidance will be appreciated!! Mayte Suarez-Farinas Research Assistant Professor, Laboratory of Investigative Dermatology Biostatistician, Center for Clinical and Translational Science The Rockefeller University 1230 York Ave, Box 178, New York, NY, 10065 Phone: +1(212) 327-8213 Fax: +1(212) 327-8232
hgu133a hgu133b hgu133plus2 hgu133a hgu133b hgu133plus2 • 1.4k views
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@mayte-suarez-farinas-2068
Last seen 9.0 years ago
United States
Hi all, I have HGU133a , HGU133b chips done in the same set of samples. Additionally I have hgu133plus2 chips in a different set of samples. Since "a+b" is almost "plus2", is tehre a way to combinethose two affybatchs ? Any guidance will be appreciated!! Mayte Suarez-Farinas Research Assistant Professor, Laboratory of Investigative Dermatology Biostatistician, Center for Clinical and Translational Science The Rockefeller University 1230 York Ave, Box 178, New York, NY, 10065 Phone: +1(212) 327-8213 Fax: +1(212) 327-8232
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Hi Mayte, The short answer is no. You could hypothetically create a mixture cdf that only contains probesets that are in the intersection of these three chip types and then normalize. Ben Bolstad has a page containing mixture cdfs for some arrays (http://bmbolstad.com/misc/mixtureCDF/MixtureCDF.html) but he never to my knowledge made one for the arrays you have. In general, I think you would be better off to normalize separately and then combine. Best, Jim On 4/27/2012 4:27 PM, Mayte Suarez-Farinas wrote: > Hi all, > > I have HGU133a , HGU133b chips done in the same set of samples. Additionally I have hgu133plus2 chips in a different set of samples. > Since "a+b" is almost "plus2", is tehre a way to combinethose two affybatchs ? > > Any guidance will be appreciated!! > > > > Mayte Suarez-Farinas > Research Assistant Professor, Laboratory of Investigative Dermatology > Biostatistician, Center for Clinical and Translational Science > The Rockefeller University > 1230 York Ave, Box 178, > New York, NY, 10065 > Phone: +1(212) 327-8213 > Fax: +1(212) 327-8232 > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > 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 University of Washington Environmental and Occupational Health Sciences 4225 Roosevelt Way NE, # 100 Seattle WA 98105-6099
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Hi, On Fri, Apr 27, 2012 at 4:51 PM, James W. MacDonald <jmacdon at="" uw.edu=""> wrote: > Hi Mayte, > > The short answer is no. > > You could hypothetically create a mixture cdf that only contains probesets > that are in the intersection of these three chip types and then normalize. > Ben Bolstad has a page containing mixture cdfs for some arrays > (http://bmbolstad.com/misc/mixtureCDF/MixtureCDF.html) but he never to my > knowledge made one for the arrays you have. > > In general, I think you would be better off to normalize separately and then > combine. Wouldn't another approach be to use one of them there meta-analysis type approaches, such as: http://www.bioconductor.org/packages/2.10/bioc/html/RankProd.html or http://www.bioconductor.org/packages/2.10/bioc/html/metaArray.html or? Never used them myself, but my mental note for these packages was there for when I wanted to tackle such a situation (notes can be wrong, of course -- mental ones, even more so since no ink was actually invested). -steve -- Steve Lianoglou Graduate Student: Computational Systems Biology ?| Memorial Sloan-Kettering Cancer Center ?| Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact
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