[BioC] dye swap vs. control channel

[A.J. Rossini]

These are actually unresolved issues (at least here, I know of one
statistician doing design that has changed their mind on this).

I think it boils down to whether you are interested in a direct
head-to-head comparison (then dye swapping is essential), or in more
general, less direct statements about groups of samples, with the
possibility of generalizing past the experiment (then choice of
reference sample is critical).

Now the REAL hard past is figuring out which you are really interested
in, given the associated costs.  Right now, if you have a good
reference or reference prototype for your situation, and can afford
biological replications,  I'd probably do reference comparisons.
(note that those "if"'s are very serious questions to answer --
flippant answers result in flippant studies :-).

So all of a sudden, we've moved beyond statistical design, to
cost-function based decision theory and risk analysis.

Sorry, no easy answers this morning.

I'd be interested in hearing others opinions on the topic as well.

best,
-tony





Isaac Mehl <imehl at ucsd.edu> writes:

> this design brings up a question i always have.  is it "better" to do
> all experiments in one channel (Cy5) and compare every sample to a
> standard (cy3)?  this way you can use less arrays or do more biological
> replicates.  IMHO getting repeated measurements of biological variation
> is more important than dye swap.
>
> very interested to hear what people think about this topic since it is
> integral to experimental design.
>
> -isaac
>
>
>
> DIF1,2 and 3 are different but similar drugs...............
>>>
>>> Slides 1-6 are treatment 1 (DIF1) Vs No treatment
>>> Slide1 Cy5/Cy3 (DIF1/no treatment)
>>> Slide2 Cy3/Cy5 (DIF1/no treatment)
>>> Slide3 Cy5/Cy3 (DIF1/no treatment)
>>> Slide4 Cy3/Cy5 (DIF1/no treatment)
>>> Slide5 Cy3/Cy5 (DIF1/no treatment)
>>> Slide6 Cy5/Cy3 (DIF1/no treatment)
>>>
>>> Slides 7-12 are treatment 2 (DIF2) Vs No treatment
>>> Slide7 Cy5/Cy3 (DIF2/no treatment)
>>> Slide8 Cy3/Cy5 (DIF2/no treatment)
>>> Slide9 Cy5/Cy3 (DIF2/no treatment)
>>> Slide10 Cy3/Cy5 (DIF2/no treatment)
>>> Slide11 Cy3/Cy5 (DIF2/no treatment)
>>> Slide12 Cy5/Cy3 (DIF2/no treatment)
>>>
>>> Slides 13-18 are treatment 3(DIF3) Vs No treatment
>>> Slide13 Cy5/Cy3 (DIF3/no treatment)
>>> Slide14 Cy3/Cy5 (DIF3/no treatment)
>>> Slide15 Cy5/Cy3 (DIF3/no treatment)
>>> Slide16 Cy3/Cy5 (DIF3/no treatment)
>>> Slide17 Cy3/Cy5 (DIF3/no treatment)
>>> Slide18 Cy5/Cy3 (DIF3/no treatment)
>>>
>>> I'd obviously like to compare across the different treatments DIF1,2
>>> and 3
> -- 
> -isaac mehl
> gene expression lab (gele)
> salk institute
> 10010 n. torrey pines rd.
> la jolla ca. 92037
> http://genex.salk.edu
>
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-- 
rossini at u.washington.edu            http://www.analytics.washington.edu/ 
Biomedical and Health Informatics   University of Washington
Biostatistics, SCHARP/HVTN          Fred Hutchinson Cancer Research Center
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