Entering edit mode
Erika Melissari
▴
250
@erika-melissari-2798
Last seen 10.1 years ago
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
[[alternative HTML version deleted]]