Dear all, As a complete newbie to microarrays, I am trying to analyze experiment with following design: Two samples (differentiated versus undifferentiated cells) were compared directly on two-color oligo array, with 3 biological replicates (different cell sources) and 4 technical replicates (arrays) per biological replicate (12 arrays altogether). In every set of technical replicates two arrays are dye-swap. I am not sure how to handle the technical and biological replication when trying to fit linear model. We are interested just in overall comparison differentiated versus undifferentiated cells. I have arrived to following setup: Targets file is: SlideNumber FileName Cy3 Cy5 1 1.gpr N1 D1 2 2.gpr N1 D1 3 3.gpr D1 N1 4 4.gpr D1 N1 5 5.gpr N2 D2 6 6.gpr N2 D2 7 7.gpr D2 N2 8 8.gpr D2 N2 9 9.gpr N3 D3 10 10.gpr N3 D3 11 11.gpr D3 N3 12 12.gpr D3 N3 Where N means undifferentiated and D differentiated cells and 1-3 are biological replicates. Is the following design correct one? Or is there a better way to obtain relevant information? Is this extensible for more/less biological replicates? design <- cbind(D1vsN1 = c(1,1,-1,-1,0,0,0,0,0,0,0,0), D2vsN2 = c(0,0,0,0,1,1,-1,-1,0,0,0,0), D3vsN3 = c(0,0,0,0,0,0,0,0,1,1,-1,-1)) fit <- lmFit(MA, design) cont.matrix <- makeContrasts(DvsN = (D1vsN1 + D2vsN2 + D3vsN3)/3, levels = design) fit2 <- contrasts.fit(fit, cont.matrix) fit2 <- eBayes(fit2) Sorry if I am asking something obvious and thank you in advance for your help. Best regards, Katerina --------------------------------------------------------------------- Katerina Kepkova Laboratory of developmental biology Department of Reproductive and Developmental Biology Institute of Animal Physiology and Genetics of the AS CR, v.v.i. Rumburska 89, Libechov 277 21 Czech Republic tel: +420 315 639 534 fax: +420 315 639 510 e-mail: kepkova at iapg.cas.cz

Hi Katerina, There is an example of how to deal with both biological and technical replicates in the limma vignette, section 8.2. There is even an example for dye-swaps, which I believe fits your design exactly. To get the limma vignette: > limmaUsersGuide() Good luck, Jenny At 10:06 AM 8/11/2008, =?iso-8859-2?Q?Kate=F8ina_Kepkov=E1?= wrote: >Dear all, >As a complete newbie to microarrays, I am trying to analyze experiment with >following design: Two samples (differentiated versus undifferentiated cells) >were compared directly on two-color oligo array, with 3 biological >replicates (different cell sources) and 4 technical replicates (arrays) per >biological replicate (12 arrays altogether). In every set of technical >replicates two arrays are dye-swap. I am not sure how to handle the >technical and biological replication when trying to fit linear model. We are >interested just in overall comparison differentiated versus undifferentiated >cells. >I have arrived to following setup: >Targets file is: >SlideNumber FileName Cy3 Cy5 >1 1.gpr N1 D1 >2 2.gpr N1 D1 >3 3.gpr D1 N1 >4 4.gpr D1 N1 >5 5.gpr N2 D2 >6 6.gpr N2 D2 >7 7.gpr D2 N2 >8 8.gpr D2 N2 >9 9.gpr N3 D3 >10 10.gpr N3 D3 >11 11.gpr D3 N3 >12 12.gpr D3 N3 > >Where N means undifferentiated and D differentiated cells and 1-3 are >biological replicates. > >Is the following design correct one? Or is there a better way to obtain >relevant information? >Is this extensible for more/less biological replicates? > >design <- cbind(D1vsN1 = c(1,1,-1,-1,0,0,0,0,0,0,0,0), D2vsN2 = >c(0,0,0,0,1,1,-1,-1,0,0,0,0), D3vsN3 = c(0,0,0,0,0,0,0,0,1,1,-1,-1)) >fit <- lmFit(MA, design) >cont.matrix <- makeContrasts(DvsN = (D1vsN1 + D2vsN2 + D3vsN3)/3, levels = >design) >fit2 <- contrasts.fit(fit, cont.matrix) >fit2 <- eBayes(fit2) > > >Sorry if I am asking something obvious and thank you in advance for your >help. > >Best regards, >Katerina > >--------------------------------------------------------------------- >Katerina Kepkova >Laboratory of developmental biology >Department of Reproductive and Developmental Biology >Institute of Animal Physiology and Genetics of the AS CR, v.v.i. >Rumburska 89, Libechov 277 21 >Czech Republic >tel: +420 315 639 534 >fax: +420 315 639 510 >e-mail: kepkova at iapg.cas.cz > >_______________________________________________ >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 Jenny Drnevich, Ph.D. Functional Genomics Bioinformatics Specialist W.M. Keck Center for Comparative and Functional Genomics Roy J. Carver Biotechnology Center University of Illinois, Urbana-Champaign 330 ERML 1201 W. Gregory Dr. Urbana, IL 61801 USA ph: 217-244-7355 fax: 217-265-5066 e-mail: drnevich at illinois.edu