Hi, I am analysing Illumina Beadchips (HumanWG6) for 42 SAMPLES. Experimental design: (factorial) time course, samples grown on 4 media; have zero control sampled at onset only[ one way multigroup analysis]; 2-3 reps per treatment. I used the lumi script by Pan Du et al (2009) for preprocessing and normalisation . This part was okay. The samples were subsetted and are R objects. SAMPLE 1 REFERENCE SAMPLE DAY 0 (triplicate) SAMPLE 2 MEDIA A DAY 7 (triplicate) SAMPLE 3 MEDIA A DAY 14 (triplicate) SAMPLE 4 MEDIA A Day 30 (triplicate) SAMPLE 5 MEDIA A DAY60 (single) SAMPLE 6 MEDIA A DAY90 (REPLICATES) SAMPLE 7 MEDIA B DAY 7 (triplicate) SAMPLE 8 MEDIA B DAY 14 (triplicate) SAMPLE 9 MEDIA B DAY 30 (triplicate) SAMPLE 10 MEDIA B DAY60 (SINGLE) SAMPLE 11 MEDIA B DAY 90 (TRIPLICATE) SAMPLE 12 MEDIA C DAY 7 (REPLICATES) SAMPLE 13 MEDIA C DAY 14 (REPLICATES) SAMPLE 14 MEDIA C DAY 30 (REPLICATES) SAMPLE 15 MEDIA D DAY 7 (REPLICATES) SAMPLE 16 MEDIA D DAY 14 (REPLCATES) SAMPLE 17 MEDIA D DAY 30 (REPLICATES) SAMPLE 18 MEDIA D (DAY 90 (REPLICATES I am new to R and would like to use limma for identifying differentially expressed genes. I have read the limma users guide (Gordon Smyth), LAB4 limma 2005, James MacDonald's BioC 2009. I am afraid my linear algebra is not good. I tried the lumi script using the modified limma (PanDu et al 2009) but met no success as I do not know how to construct the design matrix and contrast matrix for this experimental design. This is a differentiation experiment. The contrasts (comparisons) I am looking for: differential gene expression of each sample WITH the reference early differentiation genes as affected by media, time and both late differentiation genes as affected by media or both. Help towards this end will be warmly welcomed and appreciated. Sincerely, Maria