[BioC] SAM siggenes number of permutations
Holger Schwender
holger.schw at gmx.de
Thu Jan 31 10:31:57 CET 2008
Hi Olivier,
for Delta=2.5 you do not have 9 false positives, you have -- what Tusher et al. call -- 9 falsely called genes. The expected number of false positives is given by pi0 * False. So you have an expected number of false positives of 0.78 * 9. I know that this is pretty confusing and I will add a more detailed description on this to the siggenes vignette.
Moreover, the FDR is computed by pi0 * False / Called which is here 0.0209. So your estimated FDR is 2.1%.
Best,
Holger
-------- Original-Nachricht --------
> Datum: Wed, 30 Jan 2008 19:03:47 +0100
> Von: "olivier armant" <olivier.armant at itg.fzk.de>
> An: bioconductor at stat.math.ethz.ch
> Betreff: Re: [BioC] SAM siggenes number of permutations
> Dear all,
>
> Thank you for your feedback!
> Everyone can guess that I am not a statistician....
> :)
>
> Here is the results I get with my samples running SAM.
> > sam.out<-sam(normalized, sam.c1, B=100,var.equal=TRUE, med=TRUE)
>
> SAM Analysis for the Two-Class Unpaired Case Assuming Equal Variances
>
> Delta p0 False Called FDR
> 1 0.1 0.78 16417 26195 0.4887
> 2 1.3 0.78 78 751 0.0810
> 3 2.5 0.78 9 335 0.0209
> 4 3.7 0.78 3 146 0.0160
> 5 4.9 0.78 1 71 0.0110
> 6 6.1 0.78 0 21 0
> 7 7.3 0.78 0 6 0
> 8 8.5 0.78 0 4 0
> 9 9.8 0.78 0 3 0
> 10 11.0 0.78 0 0 0
>
> For me having 335 genes with only 9 false positve is already satisfactory.
> Even 20% FDR would be ok as I will have to confirm the microarray data by
> other methods...
> Do you think I can use those data as a first way to select candidate
> genes? I would say yes, but I would like advise from the specialists to see if I
> am not doing something wrong!!
> Is it better to use the limma package that you suggested??
>
> Cheers
>
> Olivier
>
> [[alternative HTML version deleted]]
>
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