questions about Affy package from new user: onemore question
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Lizhe Xu ▴ 210
@lizhe-xu-666
Last seen 9.7 years ago
Hi, Jim Thank you very much for your help. But I still have a question, I have two groups, say disease vs control, each has three U133 set. I did rma on two group separately: (like what the affyDemo did on the Dilution data) > DIS<- expresso(Data[1:3], bgcorrect.method="rma", normalize.method="quantiles", pmcorrect.method="pmonly", summary.method="medianpolish") > CON<- expresso(Data[4:6], bgcorrect.method="rma", normalize.method="quantiles", pmcorrect.method="pmonly", summary.method="medianpolish") >NORMTOL<-merge(DIS, CON)* For me, it seems I still need to do sth to normalize data between two groups. Maybe, what I did was wrong, I should do rma on both group together. *Also, I can do exprs2excel on DIS and CON files but not on NORMTOL. What I should do to export NORMTOL? So far, I combined DIS and CON in Excel. Thanks. Lizhe -----Original Message----- From: James MacDonald [mailto:jmacdon@med.umich.edu] Sent: Monday, March 15, 2004 8:11 AM To: Lizhe Xu; bioconductor@stat.math.ethz.ch Subject: Re: [BioC] questions about Affy package from new user: onemore question AH. GS==GeneSpring. If you want to join them before importing to GeneSpring, you should do this after computing expression values. You can do something like: out <- rbind(exprs(exprSetA), exprs(exprSetB)) write.table(out, "Combined expression data.txt", sep="\t", quote=F, col.names=NA) HTH, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> "Lizhe Xu" <lxu@chnola-research.org> 03/14/04 06:20PM >>> Now, I tried to load the exported data from Bioconductor to GeneSpring and found another question. Since I used U133 chip set, I wonder if I can joint the U133A and B directly and import them to GS or I should do probeset level normalization first (if so, which package in bioconductor can do it) before joint them. Thanks. Lxu _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
Microarray Normalization Cancer affy GeneSpring Microarray Normalization Cancer affy • 915 views
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@james-w-macdonald-5106
Last seen 9 hours ago
United States
You misunderstood my post; you have to compute expression measures for the A and B chips separately, but this does not imply that you should do disease and control separately. Also note that what you did is exactly equal to simply running rma, but may not be as fast. You should do something like this: eset <- rma(Data) exprs2excel(eset) Best, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> "Lizhe Xu" <lxu@chnola-research.org> 03/15/04 12:25PM >>> Hi, Jim Thank you very much for your help. But I still have a question, I have two groups, say disease vs control, each has three U133 set. I did rma on two group separately: (like what the affyDemo did on the Dilution data) > DIS<- expresso(Data[1:3], bgcorrect.method="rma", normalize.method="quantiles", pmcorrect.method="pmonly", summary.method="medianpolish") > CON<- expresso(Data[4:6], bgcorrect.method="rma", normalize.method="quantiles", pmcorrect.method="pmonly", summary.method="medianpolish") >NORMTOL<-merge(DIS, CON)* For me, it seems I still need to do sth to normalize data between two groups. Maybe, what I did was wrong, I should do rma on both group together. *Also, I can do exprs2excel on DIS and CON files but not on NORMTOL. What I should do to export NORMTOL? So far, I combined DIS and CON in Excel. Thanks. Lizhe -----Original Message----- From: James MacDonald [mailto:jmacdon@med.umich.edu] Sent: Monday, March 15, 2004 8:11 AM To: Lizhe Xu; bioconductor@stat.math.ethz.ch Subject: Re: [BioC] questions about Affy package from new user: onemore question AH. GS==GeneSpring. If you want to join them before importing to GeneSpring, you should do this after computing expression values. You can do something like: out <- rbind(exprs(exprSetA), exprs(exprSetB)) write.table(out, "Combined expression data.txt", sep="\t", quote=F, col.names=NA) HTH, Jim James W. MacDonald Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 >>> "Lizhe Xu" <lxu@chnola-research.org> 03/14/04 06:20PM >>> Now, I tried to load the exported data from Bioconductor to GeneSpring and found another question. Since I used U133 chip set, I wonder if I can joint the U133A and B directly and import them to GS or I should do probeset level normalization first (if so, which package in bioconductor can do it) before joint them. Thanks. Lxu _______________________________________________ Bioconductor mailing list Bioconductor@stat.math.ethz.ch https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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