I'm trying to understand and analyse a microarray experiment performed by someone else, and I've been reading about experimental design in some books and have a few questions. The experiment involves groups of animals assigned to one of 3 time points (measured as the number of days since treatment) and administered with either A or B treatment. 2 out 3 tissue samples are taken from the groups at their designated time point. This is basically to identify expression differences over a time course in response to one of the two treatments. In addition a control group is used which received neither A or B treatment and sampled at a single time point. Am I correct in thinking I have an incomplete fractional factorial design since each group only has 2 of 3 possible tissue samples taken and it makes no sense to have control groups for ever time point and a control can not be treated with either A or B? E.g. as mentioned at the bottom of this page: http://www.socialresearchmethods.net/kb/expfact2.php I was thinking of the below as a possible design. '-' no group possible as it's a control group Tissue 1: days since treatment 0 3 7 21 C 8 - - - A - 4 4 4 B - 4 4 4 Tissue 2: days since treatment 0 3 7 21 C 4 - - - A - 4 4 4 B - 0 0 0 Tissue 3: days since treatment 0 3 7 21 C 4 - - - A - 0 0 0 B - 4 4 4 I'm wondering how best to approach the analysis in limma such that the following can be answered: 1) Identify genes that change in expression over the days since treatment. 2) Genes that show tissue specific responses 3) Genes that show the same response over tissues - I don't think this can be done since all three tissue samples were not taken for both treatments, only Tissue 1 was taken for both treatments. 4) Find genes in Tissue 1 that respond to both treatments. I think I'm getting confused with parameterising the experiment into an appropriate design matrix. Should I parameterise it using 3 factors (treatment, days since treatment and tissue) with 3 (control, A and B), 4 (0, 3, 7 and 21) and 3 (1, 2 and 3) levels respectively: Treatment: Control, A and B Days since treatment: 0, 3, 7 and 21 Tissue: 1, 2 and 3 Since it's only possible to have days since treatment for non-control groups, how do I best approach the analysis? Should I normalise the expression levels to that of the corresponding controls for that tissue and then proceed with the analysis using a fractional factorial design: Tissue 1: days since treatment 3 7 21 A 4 4 4 B 4 4 4 Tissue 2: days since treatment 3 7 21 A 4 4 4 B 0 0 0 Tissue 3: days since treatment 3 7 21 A 0 0 0 B 4 4 4 Thanks for any input! Nathan ------------------------------------------------------------- Dr. Nathan S. Watson-Haigh OCE Post Doctoral Fellow CSIRO Livestock Industries J M Rendel Laboratory Rockhampton QLD 4701 Tel: +61 (0)7 4923 8121 Australia Fax: +61 (0)7 4923 8222