Our goal is to measure the effects of a treatment on a specific cell line
using gene expression microarrays (agilent 2-color). There are two possible
experimental designs:

A) perform the entire experiment in one day: split cells into 6 groups,
treat 3 with compound and leave 3 untreated. This setup minimizes technical
variation, but the list of differentially expressed genes will include some
that are differentially expressed mainly due to the specific conditions on
the day of the experiment (humidty levels, temperature, oxygen levels,
etc).

B) perform the experiment on three separate occasions: each day, split
cells into two groups, treat only one with compound. An paired analyis
would be appropriate here. This setup introduces noise (technical noise
because of separate handling of the three pairs and noise from daily
variation of the environmental conditions) and so we lose some statistical
power. However, since the experiment is performed under slightly different
environmental conditions, some of the condition-specific genes will no
longer show up as differentially expressed and the list of genes would in
this sense be more robust/reproducible.

Does anyone have experience with both setups? I would like to know if the
amount of variance that is introduced in setup B can be expected to be low
enough to not lose too much power while producing a more robust set of
differentially expressed genes.

Cheers
/Ali

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