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On Mon, 1 Aug 2005, Stephen Montgomery-Smith wrote:
So I've read a bit more of the Watson book, so I can take a bit more
detail.
By the way, I always recommend Watson's "The Double Helix" for a
fascinating look into the history of a very important scientific advance.
Watson took a lot of crap for the book, and may have downplayed Rosalind
Franklin's role, but that's part of what makes the book so interesting.
I'm trying to get an idea of what kind of statistical problems you might run
into.
I'll just mention two kinds of statistical problems:
In microarray studies you have variation across a plate in the amount of
DNA and this can cause local variation in quantitative results, so a kind
of spatial analysis can help.
In both gene chip and microarray studies, many SNPs are analyzed, so the
dimensionality is very high. Imagine that you have 100,000 observations
on all of 100 cases (with some disease) and 100 controls (without the
disease and matched with cases on ethnicity, etc.). If you use a p-value
cutoff of .05, and there are no real effects in the data, you will have
5,000 false positives. So if you have 6,000 positives, you have about 17%
true and 83% false. And so it goes...
Mike
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