Hi All, a question about the interpretation of the logFC in limma. I have a microarray experiment with a common reference (Cy5) design. I have generated the two matrices in the following manner design.contrast <- modelMatrix(targets, ref="REF") contrast.matrix <- makeContrasts (BPCa0-BPCa20, BPCa0-BPCa40, BPCa0-BPCa60, levels=design.contrast) and fitted the linear model. No problems there. The contrast matrix looks like the following: > contrast.matrix [1:4,1:3] Contrasts Levels BPCa0 - BPCa20 BPCa0 - BPCa40 BPCa0 - BPCa60 BPCa0 1 1 1 BPCa20 -1 0 0 BPCa40 0 -1 0 BPCa60 0 0 -1 And the fitted coefficients for those contrasts: > fit.contrast$coefficients[1:3,1:3] Contrasts BPCa0 - BPCa20 BPCa0 - BPCa40 BPCa0 - BPCa60 [1,] -0.07923765 -0.06255957 -0.14165962 [2,] -0.18658108 0.10286377 -0.06617045 [3,] -0.02428776 0.04029805 0.09705064 For no reasons, i assumed that the output value would represent the log expression of the first group vs the second as in log(BPCa0/BPCa20) and therefore a negative value would mean downregulation in the first group compared with the second. I have evidence, however, to believe that this might not be the case (by checking the M values)... Could someone please clarify how do i correctly interpret this fold change as it is not straight forward for me to extract this information from the matrix. Thanks in advance, Christian -- The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*. 94% of our 2012 graduates were in work and/or further study within six months of graduation. *The Telegraph The University of Stirling is a charity registered in Scotland, number SC 011159.

Dear Christian, You can type the function write.fit(), which will write a file that has all the statistics for the contrasts and fold changes. Fold changes are in the Coef. columns. just type write.fit(fit, file="xxx.txt") Best Regards, Pekka 2013/11/12 Christian De Santis <christian.desantis at="" stir.ac.uk="">: > > Hi All, > > a question about the interpretation of the logFC in limma. I have a microarray experiment with a common reference (Cy5) design. > > I have generated the two matrices in the following manner > > design.contrast <- modelMatrix(targets, ref="REF") > contrast.matrix <- makeContrasts (BPCa0-BPCa20, BPCa0-BPCa40, BPCa0-BPCa60, levels=design.contrast) > > and fitted the linear model. No problems there. > > The contrast matrix looks like the following: >> contrast.matrix [1:4,1:3] > Contrasts > Levels BPCa0 - BPCa20 BPCa0 - BPCa40 BPCa0 - BPCa60 > BPCa0 1 1 1 > BPCa20 -1 0 0 > BPCa40 0 -1 0 > BPCa60 0 0 -1 > > And the fitted coefficients for those contrasts: >> fit.contrast$coefficients[1:3,1:3] > Contrasts > BPCa0 - BPCa20 BPCa0 - BPCa40 BPCa0 - BPCa60 > [1,] -0.07923765 -0.06255957 -0.14165962 > [2,] -0.18658108 0.10286377 -0.06617045 > [3,] -0.02428776 0.04029805 0.09705064 > > For no reasons, i assumed that the output value would represent the log expression of the first group vs the second as in log(BPCa0/BPCa20) and therefore a negative value would mean downregulation in the first group compared with the second. I have evidence, however, to believe that this might not be the case (by checking the M values)... > > Could someone please clarify how do i correctly interpret this fold change as it is not straight forward for me to extract this information from the matrix. > > Thanks in advance, > Christian > > > -- > The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*. > 94% of our 2012 graduates were in work and/or further study within six months of graduation. > *The Telegraph > The University of Stirling is a charity registered in Scotland, number SC 011159. > > _______________________________________________ > 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