[BioC] how to 'bootstrap' expression data?

[James MacDonald]

Hi Alice,

I think what 'they' want is for you to estimate the null distribution by 
permuting the class labels for your samples. You can do this easily 
using the multtest package. The siggenes package will do this as well, 
and will also do some ad hoc shrinkage of the test denominator sort of 
like what limma does.

Best,

Jim



Johnstone, Alice wrote:
> Hi,
> I have a set of Affymetrix array data 3 groups  (two treatment one
> control) of 5 individuals in each.  I have analysed by fitting my model
> with a contrast of treatment-control, and treatment2-control to the
> linear model, using an eBayes correction, then listed the top genes
> using topTable.  I have been asked to 'bootstrap' my results to
> 'weed-out' false positives before QPCR validation.  
> Is this a necessary step?  And if so at what stage do I use it and how
> do I go about applying it to my expression data to find the
> differentially expressed genes?
> My background is definitely not in statistics so any discussion or
> pointers would be gratefully received!
> 
> Thank you
> 
> Alice
> 
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-- 
James W. MacDonald, MS
Biostatistician
UMCCC cDNA and Affymetrix Core
University of Michigan
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