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Nadia Messerschmidt
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10
@nadia-messerschmidt-1913
Last seen 10.5 years ago
Hi,
I'm am currently a postgraduate bioinformatics student at the
University
of Pretoria, South Africa.
My background is from computer science, and I'm trying to create
software that would enable biologists to get a better feel for what
the
statistics behind the experiments are. And how different experimental
designs (loop or reference) would influence the statistics.
I thought I would start with time course experiments since they are
used
quite a lot at our lab. I will need a generic approach that enables
all
time point comparisons and the profiles of genes across all time
points.
If you for instance do a small pilot study (would the design matter
here?) and find that the population coefficient of variability is 30 %
for argument's sake, you can enter that value into the power.t.test
and
get a feel for the different possibilities (changing sig level, power
ect).
But now, for the large-scale study, the question is, would a loop or a
reference design be better? Would it be possible to adapt the
power.t.test parameters somehow so that is would reflect the different
designs, or would you have to do two pilots studies, one loop and one
reference, get the var of each and put those into the power.t.test? Or
is there some way that you can take the variance from the pilot study,
say using a loop design, and adjust that to reflect a ref design?
Is what I'm trying to achieve feasible at all? Because I read another
paper saying that the effectiveness of the loop design becomes less if
you have more than 10 time points - something that surely can't be
accounted for in the power.t.test params?
Any help would be greatly appreciated.
Regards,
Nadia Messerschmidt
ACGT Bioinformatics and Computational Biology Unit
University of Pretoria
South Africa