Dear All I am working through the Apo1 example from the LIMMA users guide and adapting it to my data but am having some trouble with the design matrix and final data interpretation. I have the following experimental set up with my goal being to identify which genes are differentially expressed between test condition 1 and test condition 2. array#76?..test1(Cy3) vs reference(cy5) array#74?..test2(Cy3) vs reference(cy5) array#80?..reference(Cy3) vs test1(cy5) array#73?reference(Cy3) vs test2(Cy5) I have read in my four GenePix files and gal file and normalized using the print-tip lowess algorithm with no problems. I am using the following targets file: SlideNumber FileName Cy3 Cy5 76 slide76.gpr test1 reference 74 slide74.gpr test2 reference 80 slide80.gpr reference test1 73 slide73.gpr reference test2 The following design matrix has been generated using the above targets file and designMatrix() test1 test2 slide76 1 0 slide74 1 -1 slide80 -1 0 slide73 -1 -1 Is this design matrix appropriate if I am interested in comparing test1 to test2? If I was to use this design matrix (assuming I do not need a contrast matrix) and perform empirical bayes statistical analysis on the data to generate M values would negative M values that I get from toptable (coef =2) indicate genes that are down regulated in test condition 2 and positive Ms those that are up regulated? Thanks for your help Maria Kamarinos

> Date: Mon, 18 Oct 2004 15:46:38 +1000 > From: maria kamarinos <mariakamarinos@gmail.com> > Subject: [BioC] help with design matrix > To: bioconductor@stat.math.ethz.ch > > Dear All > > I am working through the Apo1 example from the LIMMA users guide and > adapting it to my data but am having some trouble with the design > matrix and final data interpretation. I have the following > experimental set up with my goal being to identify which genes are > differentially expressed between test condition 1 and test condition > 2. > > array#76???..test1(Cy3) vs reference(cy5) > array#74???..test2(Cy3) vs reference(cy5) > array#80???..reference(Cy3) vs test1(cy5) > array#73???reference(Cy3) vs test2(Cy5) > > I have read in my four GenePix files and gal file and normalized using > the print-tip lowess algorithm with no problems. I am using the > following targets file: > > SlideNumber FileName Cy3 Cy5 > 76 slide76.gpr test1 reference > 74 slide74.gpr test2 reference > 80 slide80.gpr reference test1 > 73 slide73.gpr reference test2 > > The following design matrix has been generated using the above targets > file and designMatrix() > > test1 test2 > slide76 1 0 > slide74 1 -1 > slide80 -1 0 > slide73 -1 -1 > > Is this design matrix appropriate if I am interested in comparing > test1 to test2? Yes, the 2nd coefficient estimates the test2-test1 comparison. It would be helpful to give the designMatrix() command that you used. I am guessing that you've used design <- designMatrix(targets, ref="test1") However the column headings are not right, so I'm guessing that you've reset them. > If I was to use this design matrix (assuming I do not need a contrast > matrix) and perform empirical bayes statistical analysis on the data > to generate M values would negative M values that I get from toptable > (coef =2) indicate genes that are down regulated in test condition 2 > and positive Ms those that are up regulated? Yes. You need fit <- eBayes(lmFit(MA, design)) topTable(fit, coef=2, adjust="fdr") Gordon > Thanks for your help > > Maria Kamarinos