Hello all,

I am planning the experimental design for a new microarray experiment. We are interested in studying the effect of a new drug on treated mice respect to untreated mice.
In order to obtain an efficient experiment, we would like to use a balanced block design, that is to balance the samples respect to the dyes, as the following:

        Red Green 
      array_1 treated_mice _1 untreated_mice_1 
      array_2 untreated_mice_2 treated_mice _2 
      array_3 treated_mice _3 untreated_mice_3 
      array_4 untreated_mice_4 treated_mice _4 
      array_5 treated_mice _5 untreated_mice_5 
      array_6 untreated_mice_6 treated_mice _6 
      array_7 treated_mice _7 untreated_mice_7 
      array_8 untreated_mice_8 treated_mice _8 
      array_9 treated_mice _9 untreated_mice_9 
      array_10 untreated_mice_10 treated_mice _10 


Usually I use LIMMA package to perform statistical analysis but I looked LIMMA userguide up not finding anything...
Does someone knows if LIMMA supports this experimental design?
How do I have to consider (biological replicates, etc.) the arrays?...I think they are indipendent? Is it right?
Do I have to calculate duplicate correlation among spot replicates on different arrays (I use arrays with only one spot per gene)?
How can I correct for the dye bias if I do not have any pair of arrays with the same pair of samples dye-swapped?

Any suggestions are appeciated.

Best Regards

Erika
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