SAM and qvalue
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@nicolas-servant-1466
Last seen 22 months ago
France
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/
qvalue qvalue • 3.2k views
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@holger-schwender-344
Last seen 9.6 years ago
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/ > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor --
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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/ >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > -- > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > > . > > -- 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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Hi Nicolas, yes, the p-values in the summary are the raw p-values (in the latest versions of siggenes, they are also referred to as rawp and not p.value anymore). With SAM p-value in my last mail I have meant these raw p-values. There are no SAM adjusted p-values for individual genes. There is "only" the FDR as an error rate for a list of genes. Best, Holger -------- Original-Nachricht -------- Datum: Tue, 07 Nov 2006 18:47:12 +0100 Von: Nicolas Servant <nicolas.servant at="" curie.fr=""> An: Holger Schwender <holger.schw at="" gmx.de=""> Betreff: Re: [BioC] SAM and qvalue > 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/ > >> > >> _______________________________________________ > >> Bioconductor mailing list > >> Bioconductor at stat.math.ethz.ch > >> https://stat.ethz.ch/mailman/listinfo/bioconductor > >> Search the archives: > >> http://news.gmane.org/gmane.science.biology.informatics.conductor > >> > > > > -- > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor at stat.math.ethz.ch > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > . > > > > > > > -- > 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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