Dear All,

I have been using single colour 8X60K Version 3 Sure Print Agilent single colour slide for my experiments and i am presently studying Limma package

My data contains two groups and three time points with NO replicates. One is an experimental group and the other is a control group

I visualise to run the experimental group data individually and then the control group data individually and later n look at the genes that are differentially regulated in both the groups

With the present code given in the "corn oil study experiment", i will be able to compare the baseline to other two time points. Is it possible to see the differential gene expression in all the three time points between both the groups?

Please can you recommend me a solution

As there are no replicates, please suggest if i have to normalise the data between the arrays. Is the below code correct in my case

#please suggest if this step is correct

isexpr <- rowSums(X$E > cutoff) >= 1

levels <- c("Baseline_Expt","Post1_Expt","Post2_Expt","Baseline_Ctrl", "Post1_Ctrl", "Post2_Ctrl")

Treatment <- factor(Treatment,levels=levels)

Thanks in advance

Best Regards,

Ragavendrasamy

Microarray data always has to be normalized, regardless of whether you have replicates or not. (Why would you think you might not have to do that?)

However you can't test for differential expression using limma if you don't have replicates. All you can is to compute log-fold-changes.