Dear List,
   
  Could you help me with another small issue?
  I usually write out the results of my analysis using the write.table function as follows:
   
  Assuming 30000 probes in the dataset:
  data <- ReadAffy()
  eset <- rma(data)
   
  design <- model.matrix(~ -1+factor(c(1,1,1,2,2,3,3,3)))
  colnames(design) <- c("group1", "group2", "group3")
  contrast.matrix <- makeContrasts(group2-group1, group3-group2, group3-group1, levels=design)
   
  fit <- lmFit(temp, design)
  fit2 <- contrasts.fit(fit, contrast.matrix)
  fit2 <- eBayes(fit2)
   
  C1<-topTable(fit2, coef=1, number=30000, adjust=”BH”)
  write.table(C1,file="comparison1.txt”,append=TRUE,quote=FALSE,sep="\t",row.names=TRUE,col.names=FALSE)
   
  C2<-topTable(fit2, coef=2, number=30000, adjust=”BH”)
  write.table(C2,file="comparison2.txt”,append=TRUE,quote=FALSE,sep="\t",row.names=TRUE,col.names=FALSE)
   
  C3<-topTable(fit2, coef=3, number=30000, adjust=”BH”)
  write.table(C3,file="comparison3.txt”,append=TRUE,quote=FALSE,sep="\t",row.names=TRUE,col.names=FALSE)
   
  I then use the written out txt files (comparison1.txt, comparison2.txt and comparison3.txt) to select significant probes on the basis of log2fold change and adjusted p values thresholds, using Excel.
  Would you say that this is a correct way to do this and could you please recommend me some other, may be more efficient way of writing the results of topTable for all 30000 probes out?
   
  With kind regards,
  Lev.

       
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