2 color microarray and decidetests output
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@srikanth-manda-srinivas-4590
Last seen 9.7 years ago
Hi all, I am working with two color microrray data and have three different stages of cancer along with normal, all normalized with a universal Normal. I analyzed the data using Limma package in R.My workflow is as below: library(limma) targets<-readTargets(filename) RG<-read.maimages(targets, source="genepix") RG$genes<-readGAL() MA<-normalizeWithinArrays(RG,method="loess") plotMA(RG) plotMA(MA) MA<-normalizeBetweenArrays(MA,method="aquantile") design=modelMatrix(MA,ref="Control") fit<-lmfit(MA,design) fit2<-ebayes(fit) contrastmatrix<-makeContrasts("StageI-Normal","StageII-Normal ","StageIII-Normal","StageIII-StageI","StageII-StageI","StageIII- StageII",levels=design) fit3<-contrasts.fit(fit2,contrastsmatrix) fit3<-ebayes(fi3) results <- decideTests(fit3,method="global") vennDiagram(results[,1:3]) I want to print the common genes which are common in all three stages and also find common signature set of genes among different stages, please help on how I should proceed further. The target file is as below: SampleNumber FileName Cy3 Cy5 1 CN 310_N.gpr Control Normal 2 CN 314_N.gpr Control Normal 3 CN 318_N.gpr Control Normal 4 CN 321_N.gpr Control Normal 5 CN 322_N.gpr Control Normal 6 CT 1015_II.gpr Control StageII 7 CT1021_II.gpr Control StageII 8 CT 1063_II.gpr Control StageII 9 CT1077_II.gpr Control StageII 10 CT1099_III.gpr Control StageIII 11 CT 1131_III.gpr Control StageIII 12 CT 1138_I.gpr Control StageI 13 CT 1178_III.gpr Control StageIII 14 CT 1179_III.gpr Control StageIII 15 CT 1187_III.gpr Control StageIII 16 CT500_I.gpr Control StageI 17 CT503_II.gpr Control StageII 18 CT 510_I.gpr Control StageI 19 CT 513_I.gpr Control StageI 20 CT 514_I.gpr Control StageI 21 CT 515_I.gpr Control StageI 22 CT 800_II.gpr Control StageII 23 CT 805_II.gpr Control StageII 24 CT 809_III.gpr Control StageIII 25 CT 833_I.gpr Control StageI 26 CT 843_I.gpr Control StageI 27 CT 859_III.gpr Control StageIII 28 CT 871_II.gpr Control StageII 29 CT 905_III.gpr Control StageIII 30 CT 935_II.gpr Control StageII Regards, Srikanth -- Srinivas M. Srikanth Ph.D. Student Institute of Bioinformatics Discoverer, 7th Floor, International Technology Park, Bangalore, India Mob:+919019114878 [[alternative HTML version deleted]]
Cancer limma Cancer limma • 861 views
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@srikanth-manda-srinivas-4590
Last seen 9.7 years ago
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Hi Srinivas, On 1/24/2012 4:31 AM, Srinivas M. Srikanth wrote: > Hi all, > > I am working with two color microrray data and have three different stages > of cancer along with normal, all normalized with a universal Normal. I > analyzed the data using Limma package in R.My workflow is as below: > > library(limma) > targets<-readTargets(filename) > RG<-read.maimages(targets, > source="genepix") > RG$genes<-readGAL() > MA<-normalizeWithinArrays(RG,method="loess") > plotMA(RG) > plotMA(MA) > MA<-normalizeBetweenArrays(MA,method="aquantile") > design=modelMatrix(MA,ref="Control") > fit<-lmfit(MA,design) > fit2<-ebayes(fit) > contrastmatrix<-makeContrasts("StageI-Normal","StageII-Normal ","StageIII-Normal","StageIII-StageI","StageII-StageI","StageIII- StageII",levels=design) > fit3<-contrasts.fit(fit2,contrastsmatrix) > fit3<-ebayes(fi3) > results<- decideTests(fit3,method="global") > vennDiagram(results[,1:3]) > > I want to print the common genes which are common in all three stages and > also find common signature set of genes among different stages, please help > on how I should proceed further. There is a function vennSelect() in my affycoretools package that is designed to print out all the genes in each section of a Venn diagram. It is intended to annotate as well, so if you don't have an annotation package for your chip you will either need to make one, or you could debug() vennSelect() and grab the results before it gets to the point where it tries to annotate. I am not sure exactly what you mean by 'common signature set of genes'. Perhaps you should look at e.g., GSEABase, GOstats, Category, etc. All these packages have vignettes that you could read. Best, Jim > > > The target file is as below: > SampleNumber FileName Cy3 Cy5 > 1 CN 310_N.gpr Control Normal > 2 CN 314_N.gpr Control Normal > 3 CN 318_N.gpr Control Normal > 4 CN 321_N.gpr Control Normal > 5 CN 322_N.gpr Control Normal > 6 CT 1015_II.gpr Control StageII > 7 CT1021_II.gpr Control StageII > 8 CT 1063_II.gpr Control StageII > 9 CT1077_II.gpr Control StageII > 10 CT1099_III.gpr Control StageIII > 11 CT 1131_III.gpr Control StageIII > 12 CT 1138_I.gpr Control StageI > 13 CT 1178_III.gpr Control StageIII > 14 CT 1179_III.gpr Control StageIII > 15 CT 1187_III.gpr Control StageIII > 16 CT500_I.gpr Control StageI > 17 CT503_II.gpr Control StageII > 18 CT 510_I.gpr Control StageI > 19 CT 513_I.gpr Control StageI > 20 CT 514_I.gpr Control StageI > 21 CT 515_I.gpr Control StageI > 22 CT 800_II.gpr Control StageII > 23 CT 805_II.gpr Control StageII > 24 CT 809_III.gpr Control StageIII > 25 CT 833_I.gpr Control StageI > 26 CT 843_I.gpr Control StageI > 27 CT 859_III.gpr Control StageIII > 28 CT 871_II.gpr Control StageII > 29 CT 905_III.gpr Control StageIII > 30 CT 935_II.gpr Control StageII > > > Regards, > Srikanth > > -- 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 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues
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Hi Srinivas, On 1/24/2012 4:31 AM, Srinivas M. Srikanth wrote: > Hi all, > > I am working with two color microrray data and have three different stages > of cancer along with normal, all normalized with a universal Normal. I > analyzed the data using Limma package in R.My workflow is as below: > > library(limma) > targets<-readTargets(filename) > RG<-read.maimages(targets, > source="genepix") > RG$genes<-readGAL() > MA<-normalizeWithinArrays(RG,method="loess") > plotMA(RG) > plotMA(MA) > MA<-normalizeBetweenArrays(MA,method="aquantile") > design=modelMatrix(MA,ref="Control") > fit<-lmfit(MA,design) > fit2<-ebayes(fit) > contrastmatrix<-makeContrasts("StageI-Normal","StageII-Normal ","StageIII-Normal","StageIII-StageI","StageII-StageI","StageIII- StageII",levels=design) > fit3<-contrasts.fit(fit2,contrastsmatrix) > fit3<-ebayes(fi3) > results<- decideTests(fit3,method="global") > vennDiagram(results[,1:3]) > > I want to print the common genes which are common in all three stages and > also find common signature set of genes among different stages, please help > on how I should proceed further. There is a function vennSelect() in my affycoretools package that is designed to print out all the genes in each section of a Venn diagram. It is intended to annotate as well, so if you don't have an annotation package for your chip you will either need to make one, or you could debug() vennSelect() and grab the results before it gets to the point where it tries to annotate. I am not sure exactly what you mean by 'common signature set of genes'. Perhaps you should look at e.g., GSEABase, GOstats, Category, etc. All these packages have vignettes that you could read. Best, Jim > > > The target file is as below: > SampleNumber FileName Cy3 Cy5 > 1 CN 310_N.gpr Control Normal > 2 CN 314_N.gpr Control Normal > 3 CN 318_N.gpr Control Normal > 4 CN 321_N.gpr Control Normal > 5 CN 322_N.gpr Control Normal > 6 CT 1015_II.gpr Control StageII > 7 CT1021_II.gpr Control StageII > 8 CT 1063_II.gpr Control StageII > 9 CT1077_II.gpr Control StageII > 10 CT1099_III.gpr Control StageIII > 11 CT 1131_III.gpr Control StageIII > 12 CT 1138_I.gpr Control StageI > 13 CT 1178_III.gpr Control StageIII > 14 CT 1179_III.gpr Control StageIII > 15 CT 1187_III.gpr Control StageIII > 16 CT500_I.gpr Control StageI > 17 CT503_II.gpr Control StageII > 18 CT 510_I.gpr Control StageI > 19 CT 513_I.gpr Control StageI > 20 CT 514_I.gpr Control StageI > 21 CT 515_I.gpr Control StageI > 22 CT 800_II.gpr Control StageII > 23 CT 805_II.gpr Control StageII > 24 CT 809_III.gpr Control StageIII > 25 CT 833_I.gpr Control StageI > 26 CT 843_I.gpr Control StageI > 27 CT 859_III.gpr Control StageIII > 28 CT 871_II.gpr Control StageII > 29 CT 905_III.gpr Control StageIII > 30 CT 935_II.gpr Control StageII > > > Regards, > Srikanth > > -- 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 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues
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