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The strain effect is confounded with the batch effect. As a result, you cannot determine whether differences are due to strain or to batch. --Naomi At 10:27 PM 11/8/2007, Jason Pear wrote: >Hi Dear BioC >I have question about design matrix considering the batch effect >using limma. The experiment design is a factorial design. > Experiment (Affy chip) > Array Strain Treatment Replicate Batch > 1 A No 1 1 > 2 A No 2 1 > 3 A No 3 1 > 4 A Yes 1 1 > 5 A Yes 2 1 > 6 A Yes 3 1 > 7 B No 1 2 > 8 B No 2 2 > 9 B No 3 2 > 10 B Yes 1 2 > 11 B Yes 2 2 > 12 B Yes 3 2 > Here we want to konw which genes respond differently in treated > vs. untreated, and we also want to find out the > interaction. However, the cluster analysis showed that there is a > clear batch effect. So I designed the following design matrix to remove the >batch effect: >design > A_unTrt A_Trt B_unTrt B_Trt Batch > 1 1 0 0 0 0 > 2 1 0 0 0 0 > 3 1 0 0 0 0 > 4 0 1 0 0 0 > 5 0 1 0 0 0 > 6 0 1 0 0 0 > 7 0 0 1 0 1 > 8 0 0 1 0 1 > 9 0 0 1 0 1 > 10 0 0 0 1 1 > 11 0 0 0 1 1 > 12 0 0 0 1 1 > >contrast <- makeContrasts( > TrtvsUntrt=(A_Trt+B_trt)-(A_unTrt+B_unTrt), > interaction=(A_Trt-A_unTrt)-(B_Trt-B_unTrt), > levels=design) >However, when I tried to fit the data and the following happes > fit <- lmFit(myData, design) >Coefficients not estimable: Batch >I am using limma version 2.10.5 and R version 2.5.1 > >Any suggestions? > >Many thanks, > >Jason >_________________________________________________________________ >[[replacing trailing spam]] > > [[alternative HTML version deleted]] > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor >Search the archives: >http://news.gmane.org/gmane.science.biology.informatics.conductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111