[BioC] SAM and qvalue

[Nicolas Servant]

Thanks for your answer.
If the qvalues are computed as in the R package qvalue, I suppose that 
the "p.values" column of the results represents the raw pvalues.
So where can i found the pvalues adjusted by SAM ?
Best,

Nicolas

Holger Schwender wrote:
> Hi Nicolas,
>
> these differences are due to the differing calculation of the FDR and the q-value. The FDR is computed using the observed and expected d values that fall outside the interval (cutlow, cutup), whereas the q-values are computed as in the R package qvalue and based on the SAM p-value which uses symmetric thresholds, i.e., e.g., (-cutup, cutup). So it can and will happen that not all q-value estimates are smaller than the FDR value if, e.g., |cutup|>|cutlow|.
>
> Best,
> Holger
>
> -------- Original-Nachricht --------
> Datum: Mon, 06 Nov 2006 16:38:23 +0100
> Von: Nicolas Servant <Nicolas.Servant at curie.fr>
> An: Bioconductor <bioconductor at stat.math.ethz.ch>
> Betreff: [BioC] SAM and qvalue
>
>   
>> 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/
>>
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-- 
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/