Question: limma design and contrast matrix for paired experiment
gravatar for David Westergaard
6.8 years ago by
David Westergaard280 wrote:
Hello, I am analysing microarray data performed on two cell cultures, in which the gene expression were measured before (C) and after treatment (T), so that the targets look like this: Cell-line Treatment Sample Cell 1 C 1 Cell 1 T 1 Cell 2 C 2 Cell 2 T 2 Cell 1 C 3 Cell 1 T 3 Cell 2 C 4 Cell 2 T 4 Cell 1 C 5 Cell 1 T 5 Cell 2 C 6 Cell 2 T 6 All experiments were performed on single-channel Agilent arrays, with 4 samples pr. slide. I am interested in determining the differentially expressed genes between Cell1 before and after treatment, as well as Cell2 before and after treatment. This is the preliminary code: # Load and normalize data RG <- read.maimages(targets$FileName,source="agilent.median", y=TRUE) # Assume there is a col called FileName in the targets section RG <- backgroundCorrect(RG, method="normexp", offset=16) RGNorm <- normalizeBetweenArrays(RG, method="quantile") RGNorm.ave <- avereps(RGNorm, ID=RGNorm$genes$ProbeName) # Create design Pairing <- paste(rep(c('C1-','C1-','C2-','C2-'),3),c(1,1,2,2,1,1,2,2,1 ,1,2,2),rep(c('C','T'),6),sep='') pair <- factor(Pairing,levels=unique(Pairing)) design <- model.matrix( ~ 0 + pair ) colnames(design) <- c('C1.C','C1.T','C2.C','C2.T') # Fit data fit <- lmFit(RGNorm.ave, design=design) cont.matrix <- makeContrasts(C1 = C1.T-C1.C, C2=C2.T-C2.C, levels=design) fit2 <-, cont.matrix) fit2 <- eBayes(fit2) For the experiment, is the design/contrast matrix a proper choice to answer the questions of 'Which genes are differentially expressed in Cell 1' and 'Which genes are differentially expressed in Cell 2'? Further, should I do any technical correction, such as duplicateCorrelation or similar? The reason I am asking is that even at p<=0.01 I am getting a very high number of differentially expressed probes (4500ish for Cell 1, and 7500ish for Cell 2, respectively), and I want to make sure this is biological significance, and not some technical aspect I have missed. Thanks in advance. Best, David > sessionInfo() R version 2.14.1 (2011-12-22) Platform: x86_64-unknown-linux-gnu (64-bit) locale: [1] C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] statmod_1.4.16 limma_3.10.3 loaded via a namespace (and not attached): [1] tcltk_2.14.1 tools_2.14.1
microarray • 692 views
ADD COMMENTlink written 6.8 years ago by David Westergaard280
Please log in to add an answer.


Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 297 users visited in the last hour