Hi Simon,

On Tue, Mar 27, 2012 at 1:05 PM, Simon Anders <anders@embl.de> wrote:

>
> I was recently searching for a good review on this that can be recommended
> to non-statistician readers, but did not find anything suitable. Maybe
> somebody else on the list has a recommendation?
>
>
Stefanie Scheid's paper is admirably direct and to-the-point:
http://bioinformatics.oxfordjournals.org/content/21/12/2921.full.pdf
William Noble's paper in Nature Biotech touches on local FDR:
http://www.nature.com/nbt/journal/v27/n12/full/nbt1209-1135.html
Brad Efron's course at Stanford goes into much much much more depth:
http://www-stat.stanford.edu/~omkar/329/ (PDF of book is online)

Maybe some of these are somewhat useful?  I think that Noble's paper is
perhaps the most introductory, then Scheid's, and then Efron's course
probably has new insights to offer anyone who hasn't spent a lifetime
studying empirical Bayes methods.  So, um, the opposite of introductory.

Thanks for assembling a great package in DEXseq and also for your very
helpful remarks on the list,

--t



-- 
*A model is a lie that helps you see the truth.*
*
*
Howard Skipper<http://cancerres.aacrjournals.org/content/31/9/1173.full.pdf>

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