Hi! I would like to use Limma to compare gene expression between two treatment groups (PO vs C). In this analysis I need to adjust for differences in a quantitative covariate (age) between samples. Is the following setup appropriate for this analysis? Do I accurately adjust for age in the final analysis? Ingrid -- output of sessionInfo(): eset<-readExpressionSet("eset.txt","target.txt",header=TRUE) GROUP <- factor(target$GROUP, levels=c("C","PO")) AGE <- factor(target$AGE) design <- model.matrix(~0+GROUP+AGE) colnames(design) <- c("C","PO") fit <- lmFit(eset,design) cont.matrix <- makeContrasts(CvsPO=C-PO,levels=design) fit2 <- contrasts.fit(fit, cont.matrix) fit2 <- eBayes(fit2) topTable(fit2, n=100, coef="CvsPO", adjust="BH") -- Sent via the guest posting facility at bioconductor.org.

Hi Ingrid, On Monday, December 02, 2013 4:12:20 AM, Ingrid Dahlman [guest] wrote: > > Hi! > I would like to use Limma to compare gene expression between two treatment groups (PO vs C). In this analysis I need to adjust for differences in a quantitative covariate (age) between samples. Is the following setup appropriate for this analysis? Do I accurately adjust for age in the final analysis? > Ingrid > > -- output of sessionInfo(): > > eset<-readExpressionSet("eset.txt","target.txt",header=TRUE) > GROUP <- factor(target$GROUP, levels=c("C","PO")) > AGE <- factor(target$AGE) I don't think this is what you want to do. A factor is by definition something that is unordered and not quantitative. I would think instead you want to fit age as a continuous covariate. Something like design <- model.matrix(~ 0 + GROUP + AGE, target) colnames(design) <- gsub("target", "", colnames(design)) Should get you what you want. Best, Jim > design <- model.matrix(~0+GROUP+AGE) > colnames(design) <- c("C","PO") > fit <- lmFit(eset,design) > cont.matrix <- makeContrasts(CvsPO=C-PO,levels=design) > fit2 <- contrasts.fit(fit, cont.matrix) > fit2 <- eBayes(fit2) > topTable(fit2, n=100, coef="CvsPO", adjust="BH") > > -- > 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