Stephen, I think this probably belongs on the bioconductor users list, rather than the development list. I am cross-posting to there. Sean On 6/1/06 5:28 PM, "Stephen Park" <stephen.park at="" ucd.ie=""> wrote: > Dear Bioconductor users, > > I'm looking to use linear modelling in Limma (all new to me) to identify > genes responding differently to infection in two different cattle breeds, > and would welcome advice on the correct model to use. > > Our experiment took eight animals from each of two genetically distinct > breeds of cattle varying in susceptibility to a parasite and infected them > with the parasite. RNA was isolated pre-infection and at five time- points > post-infection and hybridised to two-colour oligo arrays. A common reference > RNA obtained by pooling samples from both breeds and all timepoints was > labelled with the second dye and hybridised to each array. > > We're interested in seeing which genes respond differently to infection in > the different breeds. I believe the model we should be using is something > like > Gene expression level = intercept + (breed effect) + (time effect) + (time * > breed interaction effect) > > Assuming this is the appropriate model, I would like to correct for innate > pre-infection differences between breeds and effects due to infection that > are common to both breeds so that I can find those genes that respond > differently to infection between breeds, either at a given time- point or > across the entire timecourse. > > I'd like to know if I ought to set up a different design matrix from that > generated automatically using the modelMatrix function on my targets and > identifying the reference > > i.e. modelMatrix(targets,ref="Ref") > > which generates > > T0_B1 T0_B2 ... T0_B2 ... > T0_B1_A1 1 0 ... 0 ... > T0_B1_A2 1 0 ... 0 ... > ... > T1_B1_A1 0 1 ... 0 ... > ... > T0_B2_A9 0 0 ... 1 ... > .... > > where T=time, B=breed, A=animal > > > If this is OK, am I right in thinking that contrasts > (T1_B1 - T0_B1) - (T1_B2 - T0_B2) > will remove both the breed component of the model for each breed (within > brackets) and the component due to infection common to both breeds, leaving > me with the interaction component? > > Alternatively, should the design matrix contain additional coefficients to > account for time, breed and interaction components? > > I'd be very grateful for any advice you could offer. > > Thanks, > > Stephen > > ------------------------------------------------------ > Dr. Stephen Park > Animal Genomics Lab > School of Agriculture, Food Science & Vet. Medicine > University College Dublin > Dublin 4 > Ireland > > Tel: +353 (0)1 716 7767 > Fax: +353 (0)1 716 1103 > Mob: +353 (0)87 7666850 > E-mail: stephen.park at ucd.ie > Web: http://animalgenomics.ucd.ie/sdepark/ > > _______________________________________________ > Bioc-devel at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/bioc-devel