Hi The confusion comes from the examples given in usersguide.pdf. Sections 7.3 and 8.2 both deal with two colour microarray data where a common reference has been used. Section 7.3 advocates the use of designMatrix() and makeContrasts(), where lmFit() is first used with the design matrix, and then contrasts.fit() is used with the contrasts matrix, and then eBayes() applied to the resulting linear model fit. Section 8.2 gives us the design matrix directly, and does not use a contrasts matrix at all. So my first question is this: with two colour cDNA microarrays which use a common reference, do we need both a design matrix and a contrasts matrix, or just a design matrix? (I'm assuming it depends on how many samples there are in addition to the reference, but I'm not sure). Looking at section 8.2, the ApoAI data, we have three samples - control mice, ApoAI mice and the reference sample. 8 control mice were compared to the reference and 8 ApoAI mice were compared to the reference, and in all cases the reference was Cy3. Therefore, a targets file to describe this experiment can reasonably be expected to look like this: SlideNumber Cy5 Cy3 1 c1 Control Ref 2 c2 Control Ref 3 c3 Control Ref 4 c4 Control Ref 5 c5 Control Ref 6 c6 Control Ref 7 c7 Control Ref 8 c8 Control Ref 9 k1 ApoAI Ref 10 k2 ApoAI Ref 11 k3 ApoAI Ref 12 k4 ApoAI Ref 13 k5 ApoAI Ref 14 k6 ApoAI Ref 15 k7 ApoAI Ref 16 k8 ApoAI Ref If we run modelMatrix() on this, we get this: ApoAI Control 1 0 1 2 0 1 3 0 1 4 0 1 5 0 1 6 0 1 7 0 1 8 0 1 9 1 0 10 1 0 11 1 0 12 1 0 13 1 0 14 1 0 15 1 0 16 1 0 If we then carry on the example in 7.3, and create a contrasts matrix, then I assume we are interested in the comparison of ApoAI knockout mice to Control mice, so I run: > makeContrasts(ApoAI-Control, levels=apoai.design) And get this ApoAI - Control ApoAI 1 Control -1 So, just to take a breath here, I am using the documentation from section 7.3 to run against the data in section 8.2. I now have a design matrix and a contrasts matrix for the ApoAI data. The only problem is that they look completely different to the example design matrix given in section 8.2. The design matrix there is: Control-Ref KO-Control c1 1 0 c2 1 0 c3 1 0 c4 1 0 c5 1 0 c6 1 0 c7 1 0 c8 1 0 k1 1 1 k2 1 1 k3 1 1 k4 1 1 k5 1 1 k6 1 1 k7 1 1 k8 1 1 And there is no contrasts matrix. So, my question 2: is the design matrix given in section 8.2 the equivalent of using the design and contrasts matrices that I calculated above? Question 3: does the fact that the ApoAI data only has one contrast of interest mean that I don't need a contrasts matrix, I only need a design matrix? (albeit a DIFFERENT design matrix to one that would be given by modelMatrix()). Question 4: can anyone recommend a good book which I can go and read and learn all about design and contrast matrices and their relation to linear models? Everything I have read so far just says something like "... The design matrix is therefore this... and the contrast matrix is therefore this..." and doesn't actually explain how exactly the structure of the matrices was arrived at... Thanks and sorry for the long mail! Mick