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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
