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Hi all,
I have a question about SAM (siggenes) and its adjusted pvalues
(qvalues).
When i perform SAM on Golub data for a FDR threshold = 5%:
FDR=5/100
output<-sam(golub,golub.cl,rand=123,delta=seq(0.1,5,0.05))
res.sum<-summary(output)
sum.output <- res.sum at mat.fdr
delta<-sum.output[sum.output[,"FDR"]<=FDR,][1,"Delta"]
delta.sum<-summary(output,delta)
ds.mat.sig <- delta.sum at mat.sig
I found 894 significant genes.
Row d.value stdev p.value q.value R.fold
1 829 8.165222 0.29582512 0.000000e+00 0.000000e+00 7.2771792
2 2124 7.964784 0.17786969 0.000000e+00 0.000000e+00 3.3953035
3 2600 6.102371 0.19112194 0.000000e+00 0.000000e+00 2.6686992
....
892 142 -1.689638 0.11912464 3.305801e-02 5.393673e-02 0.8178807
893 864 -1.689047 0.08528524 3.312029e-02 5.393673e-02 0.8312349
894 686 -1.689045 0.20350807 3.312029e-02 5.393673e-02 0.7272737
For a FDR threshold, SAM use the Delta, the cutlow and the cutup
values
to find significant genes.
How can we explain that the last genes of my list have a qvalue bigger
than 5% (my FDR threshold) ?
I notice that their dstatistics are in the good range (cutlow-cutup),
It
certainly explains why these genes are significants.
Thanks for your help !
Best Regards,
Nicolas
--
Nicolas Servant
Equipe Bioinformatique
Institut Curie
26, rue d'Ulm - 75248 Paris Cedex 05 - FRANCE
Email: Nicolas.Servant at curie.fr
Tel: 01 53 10 70 55
http://bioinfo.curie.fr/