On Feb 21, 2012, at 22:44 , array chip wrote:

> Hi, I have a microarray dataset from Agilent chips. The data were really log 
> ratio between test samples and a universal reference RNA. Because of the 
> nature of log ratios, coefficient of variation (CV) doesn't really apply to 
> this kind of data due to the fact that mean of log ratio is very close to 0. 
> What kind of measurements would people use to measure the dispersion so that 
> I can compare across genes on the chip to find stably expressed genes? 
> something similar to CV would be easily interpreted?

What's wrong with the SD of log(X)?? That's pretty much equivalent to CV at 
least for CV's less than 50%:

> x <- rlnorm(1000,5,.5)
> sd(x)/mean(x)
[1] 0.5252718
> sd(log(x))
[1] 0.5037995

Looking for a relative measure of precision _after_ taking log strikes me as 
very odd. If you scale your original observations by a constant factor, this 
will be _added_ to the log transformed data, without affecting their variation 
at all.


-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk  Priv: pda...@gmail.com

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