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Question: Limma and drug treatment
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gravatar for Nolwenn Le Meur
14.2 years ago by
Nolwenn Le Meur30 wrote:
Dear all, I would like to found out if there is an interaction between treatments (Amines and Betabloc) on gene expression. I would like to known if some genes are differentially expressed by one of the drugs(Betabloc,Amines) or their combination (Betabloc:Amines). Reading the Bioconductor FAQ I think that these questions can be answered by Limma but I am not sure of what I get for result with the following script. The design matrix only gives me the first topres (diffrentially expressed) genes for the clinical parameter "Betabloc". How can I get the data for the Betabloc:Amines relationship. Do I have to write a specific design matrix like design<-model.matrix(~Betabloc:Amines-1,data=pData(clinicFull)) ? Does the following contrast matrix give me the genes differentially expressed between patients taking "Betabloc" and the one taking "Amines" ? Thank you in advance,Best regards, Nolwenn Le Meur ##Code VD<-read.table("VD.txt",header=TRUE,sep="\t",row.names=1) clinicFull<-read.phenoData("clinic.txt",header=TRUE,sep="\t",row.name s=1) eset<-new("exprSet",exprs=VD1,phenoData= clinicFull) eset #Expression Set (exprSet) with # 571 genes # 94 samples # phenoData object with 18 variables and 94 cases # varLabels # SampleID: read from file # CODEBDD: read from file # PAT: read from file # SEXE: read from file # Tabac: read from file # Diabete: read from file # HTA: read from file # Ifam: read from file # Dyslipid: read from file # IEC: read from file # Betabloc: read from file # Amines: read from file # Inh: read from file # Antialdo: read from file # duir: read from file # statine: read from file # amio: read from file # digi: read from file ##Model Betabloc+Amines+Betabloc:Amines design<-model.matrix(~Betabloc*Amines-1,data=pData(clinicFull)) fit <- lmFit(eset, design) eb<-ebayes(fit) topres<-toptable(number=571,genelist=as.character(row.names(VD)),fit=f it,eb= eb,adjust="holm") length(which(topres$P.Value<0.01)) cont.matrix<-makeContrasts(Betabloc-Amines,levels=design) fit1<-contrasts.fit(fit,cont.matrix) eb1<-ebayes(fit1) topres1<-toptable(number=571,genelist=as.character(row.names(VD)),fit= fit1,e b=eb1,adjust="holm") length(which(topres1$P.Value<0.01)) ******************************************** Nolwenn Le Meur INSERM U533 Facult? de m?decine 1, rue Gaston Veil 44035 Nantes Cedex 1 France Tel: (+33)-2-40-41-29-86 (office) (+33)-2-40-41-28-44 (secretary) Fax: (+33)-2-40-41-29-50 mail: nolwenn.lemeur@nantes.inserm.fr
ADD COMMENTlink modified 14.2 years ago by huj@sciosinc.com20 • written 14.2 years ago by Nolwenn Le Meur30
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gravatar for Sean Davis
14.2 years ago by
Sean Davis21k
United States
Sean Davis21k wrote:
> > #Expression Set (exprSet) with > # 571 genes > # 94 samples > # phenoData object with 18 variables and 94 cases > # varLabels > > ##Model Betabloc+Amines+Betabloc:Amines > design<-model.matrix(~Betabloc*Amines-1,data=pData(clinicFull)) > fit <- lmFit(eset, design) > eb<-ebayes(fit) > topres<- > toptable(number=571,genelist=as.character(row.names(VD)),fit=fit,eb= > eb,adjust="holm") > length(which(topres$P.Value<0.01) My guess is that your eb contains information for each of the coefficients. You need to specify the coef parameter (1, 2, or 3) to get information about the other coefficients (the default coefficient is 1). Along the same lines, if you do: dim(eb$p.value) my guess is that you have 3 columns. Check to see if that is the case. See the documentation for topTable for using the coef parameter. > cont.matrix<-makeContrasts(Betabloc-Amines,levels=design) > fit1<-contrasts.fit(fit,cont.matrix) > eb1<-ebayes(fit1) > topres1<- > toptable(number=571,genelist=as.character(row.names(VD)),fit=fit1,e > b=eb1,adjust="holm") > length(which(topres1$P.Value<0.01)) > This looks right to me given what is above. Sean
ADD COMMENTlink written 14.2 years ago by Sean Davis21k
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gravatar for huj@sciosinc.com
14.2 years ago by
huj@sciosinc.com20 wrote:
Hi all, I would like to try LPE for cDNA microarray data analysis. Can anyone please tell me how to install this package? The package list for getBioC() does not seem to include this package. Also, since I am fairly new to this field, is this a good test for identifying significant differentially expressed genes in cDNA microarray experiments? what are the alternatives? Thank you very much in advance, Jeff [[alternative HTML version deleted]]
ADD COMMENTlink written 14.2 years ago by huj@sciosinc.com20
Jeff, I didn't try to getBioC for LPE recently (last few days), but it has generally been included. You can always get source from: http://www.bioconductor.org/repository/release1.4/package/html Other packages to consider are many but to name some (probably not complete): limma (my favorite), siggenes (includes SAM), multtest, ebarrays, factorial design, general anova and various statistical tests included with R, as well as the possibility of creating your own. Sean On Aug 23, 2004, at 5:20 PM, huj@sciosinc.com wrote: > Hi all, > > I would like to try LPE for cDNA microarray data analysis. Can anyone > please tell me how to install this package? The package list for > getBioC() does not seem to include this package. > > Also, since I am fairly new to this field, is this a good test for > identifying significant differentially expressed genes in cDNA > microarray > experiments? what are the alternatives? > > Thank you very much in advance, > > Jeff > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor
ADD REPLYlink written 14.2 years ago by Sean Davis21k
Sean, Thanks for your info. It seems LPE currently only supports oligo arrays. Has anybody used LPE for cDNA array? If not, what is the best alternative for cDNA array analyses with a few replicates (3-4)? Thank you very much. Jeff Sean Davis <sdavis2@mail.nih.gov> 08/24/2004 03:16 AM To huj@sciosinc.com cc <bioconductor@stat.math.ethz.ch> Subject Re: [BioC] How to get LPE package Jeff, I didn't try to getBioC for LPE recently (last few days), but it has generally been included. You can always get source from: http://www.bioconductor.org/repository/release1.4/package/html Other packages to consider are many but to name some (probably not complete): limma (my favorite), siggenes (includes SAM), multtest, ebarrays, factorial design, general anova and various statistical tests included with R, as well as the possibility of creating your own. Sean On Aug 23, 2004, at 5:20 PM, huj@sciosinc.com wrote: > Hi all, > > I would like to try LPE for cDNA microarray data analysis. Can anyone > please tell me how to install this package? The package list for > getBioC() does not seem to include this package. > > Also, since I am fairly new to this field, is this a good test for > identifying significant differentially expressed genes in cDNA > microarray > experiments? what are the alternatives? > > Thank you very much in advance, > > Jeff > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor [[alternative HTML version deleted]]
ADD REPLYlink written 14.2 years ago by huj@sciosinc.com20
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