Affymetrix data double normalisation
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Hi, I would like to use gcrma to do a within group normalization first (30 groups in total), then input all the normalised 30 groups to do another global gcrma. Is this possible? Does the gcrma accept the inputs from the first normalisation output? Many thanks. Jun -- output of sessionInfo(): > gcrma12<-gcrma(gcrma1,gcrma2) Error in function (classes, fdef, mtable) : unable to find an inherited method for function "indexProbes", for signature "ExpressionSet", "character" -- Sent via the guest posting facility at bioconductor.org.
Normalization gcrma Normalization gcrma • 885 views
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@james-w-macdonald-5106
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Hi Jun, On 9/25/2012 7:11 AM, Jun Han [guest] wrote: > Hi, > I would like to use gcrma to do a within group normalization first (30 groups in total), then input all the normalised 30 groups to do another global gcrma. > Is this possible? Does the gcrma accept the inputs from the first normalisation output? The short answer is no. When you run gcrma(), you do background correction, normalization, and finally summarization of the probe- level data, resulting in probeset-level data. In other words, you are taking the PM probes and summarizing them into a single value at the probeset level (after background correcting and normalizing). Since gcrma() expects you to be inputting an AffyBatch containing PM and MM probe data, it fails when you input an ExpressionSet containing summarized probeset level data. I assume you are trying to combine two groups that you think should not be normalized and summarized together. This leads to two questions - first, why don't you think these data can be combined prior to the gcrma() step, and second, if the answer to the first question is because of a batch effect, have you looked at e.g., sva or comBat? Best, Jim > Many thanks. > Jun > > -- output of sessionInfo(): > >> gcrma12<-gcrma(gcrma1,gcrma2) > Error in function (classes, fdef, mtable) : > unable to find an inherited method for function "indexProbes", for signature "ExpressionSet", "character" > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > 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 Jim, I kindly have a similar question: how to analyze two large affymetrix gene expression datasets. I have >2,000 affymetrix data in a relatively old groups. These data have been normalized a year ago, which took a lot of efforts (miss/mixed sample correction, quality check, etc.) Then recently, we got another 3000 data on the same affymetrix platform, but in a relatively younger group. These data have been normalized separately from the previous data. Now, my question is if I would like to analyze these data together (>5,000 samples), what are your suggestions? Two possible ways that I can think of are the following: 1. Re-normalize all of these 5,000 samples all together 2. double normalize the two datasets, for example, standard-transformation (z-score) or global median normalization for each dataset, then group them together for the down-stream statistical analysis. Thanks in advance for your help, Shirley On Tue, Sep 25, 2012 at 10:21 AM, James W. MacDonald <jmacdon at="" uw.edu=""> wrote: > Hi Jun, > > On 9/25/2012 7:11 AM, Jun Han [guest] wrote: >> >> Hi, >> I would like to use gcrma to do a within group normalization first (30 >> groups in total), then input all the normalised 30 groups to do another >> global gcrma. >> Is this possible? Does the gcrma accept the inputs from the first >> normalisation output? > > > The short answer is no. When you run gcrma(), you do background correction, > normalization, and finally summarization of the probe-level data, resulting > in probeset-level data. In other words, you are taking the PM probes and > summarizing them into a single value at the probeset level (after background > correcting and normalizing). > > Since gcrma() expects you to be inputting an AffyBatch containing PM and MM > probe data, it fails when you input an ExpressionSet containing summarized > probeset level data. > > I assume you are trying to combine two groups that you think should not be > normalized and summarized together. This leads to two questions - first, why > don't you think these data can be combined prior to the gcrma() step, and > second, if the answer to the first question is because of a batch effect, > have you looked at e.g., sva or comBat? > > Best, > > Jim > > >> Many thanks. >> Jun >> >> -- output of sessionInfo(): >> >>> gcrma12<-gcrma(gcrma1,gcrma2) >> >> Error in function (classes, fdef, mtable) : >> unable to find an inherited method for function "indexProbes", for >> signature "ExpressionSet", "character" >> >> -- >> Sent via the guest posting facility at bioconductor.org. >> >> _______________________________________________ >> 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 > > _______________________________________________ > 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
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Hi Shirley, A third option is to use fRMA, which is designed specifically for the situation you are in right now. Best, Jim On 9/25/2012 11:19 AM, shirley zhang wrote: > Hi Jim, > > I kindly have a similar question: how to analyze two large affymetrix > gene expression datasets. > > I have>2,000 affymetrix data in a relatively old groups. These data > have been normalized a year ago, which took a lot of efforts > (miss/mixed sample correction, quality check, etc.) > > Then recently, we got another 3000 data on the same affymetrix > platform, but in a relatively younger group. These data have been > normalized separately from the previous data. > > Now, my question is if I would like to analyze these data together > (>5,000 samples), what are your suggestions? Two possible ways that I > can think of are the following: > > 1. Re-normalize all of these 5,000 samples all together > 2. double normalize the two datasets, for example, > standard-transformation (z-score) or global median normalization for > each dataset, then group them together for the down-stream statistical > analysis. > > Thanks in advance for your help, > Shirley > > On Tue, Sep 25, 2012 at 10:21 AM, James W. MacDonald<jmacdon at="" uw.edu=""> wrote: >> Hi Jun, >> >> On 9/25/2012 7:11 AM, Jun Han [guest] wrote: >>> Hi, >>> I would like to use gcrma to do a within group normalization first (30 >>> groups in total), then input all the normalised 30 groups to do another >>> global gcrma. >>> Is this possible? Does the gcrma accept the inputs from the first >>> normalisation output? >> >> The short answer is no. When you run gcrma(), you do background correction, >> normalization, and finally summarization of the probe-level data, resulting >> in probeset-level data. In other words, you are taking the PM probes and >> summarizing them into a single value at the probeset level (after background >> correcting and normalizing). >> >> Since gcrma() expects you to be inputting an AffyBatch containing PM and MM >> probe data, it fails when you input an ExpressionSet containing summarized >> probeset level data. >> >> I assume you are trying to combine two groups that you think should not be >> normalized and summarized together. This leads to two questions - first, why >> don't you think these data can be combined prior to the gcrma() step, and >> second, if the answer to the first question is because of a batch effect, >> have you looked at e.g., sva or comBat? >> >> Best, >> >> Jim >> >> >>> Many thanks. >>> Jun >>> >>> -- output of sessionInfo(): >>> >>>> gcrma12<-gcrma(gcrma1,gcrma2) >>> Error in function (classes, fdef, mtable) : >>> unable to find an inherited method for function "indexProbes", for >>> signature "ExpressionSet", "character" >>> >>> -- >>> Sent via the guest posting facility at bioconductor.org. >>> >>> _______________________________________________ >>> 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 >> >> _______________________________________________ >> 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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Great. Thanks Jim. I will check fRMA. Shirley On Tue, Sep 25, 2012 at 11:21 AM, James W. MacDonald <jmacdon at="" uw.edu=""> wrote: > Hi Shirley, > > A third option is to use fRMA, which is designed specifically for the > situation you are in right now. > > Best, > > Jim > > > > > On 9/25/2012 11:19 AM, shirley zhang wrote: >> >> Hi Jim, >> >> I kindly have a similar question: how to analyze two large affymetrix >> gene expression datasets. >> >> I have>2,000 affymetrix data in a relatively old groups. These data >> have been normalized a year ago, which took a lot of efforts >> (miss/mixed sample correction, quality check, etc.) >> >> Then recently, we got another 3000 data on the same affymetrix >> platform, but in a relatively younger group. These data have been >> normalized separately from the previous data. >> >> Now, my question is if I would like to analyze these data together >> (>5,000 samples), what are your suggestions? Two possible ways that I >> can think of are the following: >> >> 1. Re-normalize all of these 5,000 samples all together >> 2. double normalize the two datasets, for example, >> standard-transformation (z-score) or global median normalization for >> each dataset, then group them together for the down-stream statistical >> analysis. >> >> Thanks in advance for your help, >> Shirley >> >> On Tue, Sep 25, 2012 at 10:21 AM, James W. MacDonald<jmacdon at="" uw.edu=""> >> wrote: >>> >>> Hi Jun, >>> >>> On 9/25/2012 7:11 AM, Jun Han [guest] wrote: >>>> >>>> Hi, >>>> I would like to use gcrma to do a within group normalization first (30 >>>> groups in total), then input all the normalised 30 groups to do another >>>> global gcrma. >>>> Is this possible? Does the gcrma accept the inputs from the first >>>> normalisation output? >>> >>> >>> The short answer is no. When you run gcrma(), you do background >>> correction, >>> normalization, and finally summarization of the probe-level data, >>> resulting >>> in probeset-level data. In other words, you are taking the PM probes and >>> summarizing them into a single value at the probeset level (after >>> background >>> correcting and normalizing). >>> >>> Since gcrma() expects you to be inputting an AffyBatch containing PM and >>> MM >>> probe data, it fails when you input an ExpressionSet containing >>> summarized >>> probeset level data. >>> >>> I assume you are trying to combine two groups that you think should not >>> be >>> normalized and summarized together. This leads to two questions - first, >>> why >>> don't you think these data can be combined prior to the gcrma() step, and >>> second, if the answer to the first question is because of a batch effect, >>> have you looked at e.g., sva or comBat? >>> >>> Best, >>> >>> Jim >>> >>> >>>> Many thanks. >>>> Jun >>>> >>>> -- output of sessionInfo(): >>>> >>>>> gcrma12<-gcrma(gcrma1,gcrma2) >>>> >>>> Error in function (classes, fdef, mtable) : >>>> unable to find an inherited method for function "indexProbes", for >>>> signature "ExpressionSet", "character" >>>> >>>> -- >>>> Sent via the guest posting facility at bioconductor.org. >>>> >>>> _______________________________________________ >>>> 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 >>> >>> _______________________________________________ >>> 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 > -- Xiaoling (Shirley) Zhang M.D., Ph.D. Boston University, Boston, MA Tel: (857) 233-9862 Email: zhangxl at bu.edu
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