SAM siggenes number of permutations
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@olivier-armant-2622
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@james-w-macdonald-5106
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Hi Olivier, olivier armant wrote: > Dear all, > > I try to do SAM on my data using siggenes on R 2.4.1 (I am a beginner) > > The function I use is (after creating the vector) > sam.out<-sam(data.gcrma, sam.c1, B=100, var.equal=TRUE, Set med=TRUE) > > It seems to work well but I get allways the message: > number of effective permutations=20 > > Does it means that only 20 permutations were done, werheas I ask for 100 permutations with the function B=100?? Yes. A more correct statement would be that the number of combinations = 20. You evidently have 6 samples, with 3 in each class. There are only 20 ways you can make two groups of three, so it doesn't matter that you requested B=100. > > I read in the SAM excel package from standford that a precise FDR requires 1000 permutations!!!What do you think?? Ideally you want lots of combinations, as the null distribution with only 20 combinations will be very discrete. You can either assume that you are getting a reasonable null distribution with 20 combinations, or you can decide that isn't good enough and make the assumption that the genes all follow a Normal-ish distribution and use a parametric method (e.g., the limma package). Best, Jim > > Help would be welcome > > > Olivier ARMANT PhD. > > Institute of Toxicology and Genetics > Forschungszentrum Karlsruhe > Hermann-von-Helmholtz-Platz 1 > D-76344 Eggenstein-Leopoldshafen > Germany > > tel: +49-7247-82-2560 > fax: +49-7247-82-3354 > > [[alternative HTML version deleted]] > > _______________________________________________ > 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 -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623
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Just as a side note to Jim's comments: Besides using, e.g., limma to do a parametric test, you can also apply SAM to the genes assuming normality. For that, you have either to program your own test score or run Code Chunk 34 of the R vignette (which defines the function t.stat), and then use > sam(data, cl, method = t.stat) Best, Holger -------- Original-Nachricht -------- > Datum: Wed, 30 Jan 2008 10:31:17 -0500 > Von: "James W. MacDonald" <jmacdon at="" med.umich.edu=""> > An: olivier armant <olivier.armant at="" itg.fzk.de=""> > CC: bioconductor at stat.math.ethz.ch > Betreff: Re: [BioC] SAM siggenes number of permutations > Hi Olivier, > > olivier armant wrote: > > Dear all, > > > > I try to do SAM on my data using siggenes on R 2.4.1 (I am a beginner) > > > > The function I use is (after creating the vector) > > sam.out<-sam(data.gcrma, sam.c1, B=100, var.equal=TRUE, Set med=TRUE) > > > > It seems to work well but I get allways the message: > > number of effective permutations=20 > > > > Does it means that only 20 permutations were done, werheas I ask for 100 > permutations with the function B=100?? > > Yes. A more correct statement would be that the number of combinations = > 20. You evidently have 6 samples, with 3 in each class. There are only > 20 ways you can make two groups of three, so it doesn't matter that you > requested B=100. > > > > > I read in the SAM excel package from standford that a precise FDR > requires 1000 permutations!!!What do you think?? > > Ideally you want lots of combinations, as the null distribution with > only 20 combinations will be very discrete. You can either assume that > you are getting a reasonable null distribution with 20 combinations, or > you can decide that isn't good enough and make the assumption that the > genes all follow a Normal-ish distribution and use a parametric method > (e.g., the limma package). > > Best, > > Jim > > > > > > Help would be welcome > > > > > > Olivier ARMANT PhD. > > > > Institute of Toxicology and Genetics > > Forschungszentrum Karlsruhe > > Hermann-von-Helmholtz-Platz 1 > > D-76344 Eggenstein-Leopoldshafen > > Germany > > > > tel: +49-7247-82-2560 > > fax: +49-7247-82-3354 > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > 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 > > -- > James W. MacDonald, M.S. > Biostatistician > Affymetrix and cDNA Microarray Core > University of Michigan Cancer Center > 1500 E. Medical Center Drive > 7410 CCGC > Ann Arbor MI 48109 > 734-647-5623 > > _______________________________________________ > 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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Claus Mayer ▴ 340
@claus-mayer-1179
Last seen 10.2 years ago
European Union
Dear Oliver, my guess is that you have 2 groups with 3 samples each in which case there are only 20 different possible permutations and the software is clever enough to realise that. In that case the calculation is exact, but you will not find anything significant as the smallest possible p-value is 5% (1/20) for a one-sided and 10% (2/20) for a two-sided test. The problem of how large groupsizes must be in order to apply permutation tests was discussed on this list some time ago, have a look at https://stat.ethz.ch/pipermail/bioconductor/2007-November/020110.html. Hope that helps, Claus olivier armant wrote: > Dear all, > > I try to do SAM on my data using siggenes on R 2.4.1 (I am a beginner) > > The function I use is (after creating the vector) > sam.out<-sam(data.gcrma, sam.c1, B=100, var.equal=TRUE, Set med=TRUE) > > It seems to work well but I get allways the message: > number of effective permutations=20 > > Does it means that only 20 permutations were done, werheas I ask for 100 permutations with the function B=100?? > > I read in the SAM excel package from standford that a precise FDR requires 1000 permutations!!!What do you think?? > > Help would be welcome > > > Olivier ARMANT PhD. > > Institute of Toxicology and Genetics > Forschungszentrum Karlsruhe > Hermann-von-Helmholtz-Platz 1 > D-76344 Eggenstein-Leopoldshafen > Germany > > tel: +49-7247-82-2560 > fax: +49-7247-82-3354 > > [[alternative HTML version deleted]] > > _______________________________________________ > 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 > > > > > > > Click link below to report this email as spam. > https://www.mailcontrol.com/sr/3DY9iYaP4!7r39w1EFqnMqyXCXdO4FUjsVoyh 6aS5N4FEmP!1HRAPmogM3OjcxjD93Syur5W2CZtunTQgwTuP7V!!KZuwoZSVAucmrR2rgQ OGNiaVM6niaGOzmDM1kiNIGdfj1S974ZFrjONfMkOumM3VVLQBeUfyoE8wlh1VA3AcEiVY 62mDkUBARsCH4ulx40V!CB9C3v7YvmL6!0DaFxrVhykbxl2 > > > -- ********************************************************************** ************* Dr Claus-D. Mayer | http://www.bioss.ac.uk Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk Rowett Research Institute | Telephone: +44 (0) 1224 716652 Aberdeen AB21 9SB, Scotland, UK. | Fax: +44 (0) 1224 715349
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Hi Claus, this is not totally correct. If none of the permuted test scores is larger than the actual test score, then your p-value will be 0. Moreover, SAM uses not just the B permuted test scores of a particular gene to compute its p-values, but all mB permuted test scores of all m genes such that the p-value of a gene is given by i/mB instead of i/B, where i is the number of more extreme permuted test scores and B is the number of permutations. Best, Holger -------- Original-Nachricht -------- > Datum: Wed, 30 Jan 2008 15:27:25 +0000 > Von: Claus-Dieter Mayer <claus at="" bioss.ac.uk=""> > An: olivier armant <olivier.armant at="" itg.fzk.de=""> > CC: bioconductor at stat.math.ethz.ch > Betreff: Re: [BioC] SAM siggenes number of permutations > Dear Oliver, > > my guess is that you have 2 groups with 3 samples each in which case > there are only 20 different possible permutations and the software is > clever enough to realise that. In that case the calculation is exact, > but you will not find anything significant as the smallest possible > p-value is 5% (1/20) for a one-sided and 10% (2/20) for a two-sided > test. The problem of how large groupsizes must be in order to apply > permutation tests was discussed on this list some time ago, have a look > at https://stat.ethz.ch/pipermail/bioconductor/2007-November/020110.html. > > Hope that helps, > > Claus > > olivier armant wrote: > > Dear all, > > > > I try to do SAM on my data using siggenes on R 2.4.1 (I am a beginner) > > > > The function I use is (after creating the vector) > > sam.out<-sam(data.gcrma, sam.c1, B=100, var.equal=TRUE, Set med=TRUE) > > > > It seems to work well but I get allways the message: > > number of effective permutations=20 > > > > Does it means that only 20 permutations were done, werheas I ask for 100 > permutations with the function B=100?? > > > > I read in the SAM excel package from standford that a precise FDR > requires 1000 permutations!!!What do you think?? > > > > Help would be welcome > > > > > > Olivier ARMANT PhD. > > > > Institute of Toxicology and Genetics > > Forschungszentrum Karlsruhe > > Hermann-von-Helmholtz-Platz 1 > > D-76344 Eggenstein-Leopoldshafen > > Germany > > > > tel: +49-7247-82-2560 > > fax: +49-7247-82-3354 > > > > [[alternative HTML version deleted]] > > > > _______________________________________________ > > 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 > > > > > > > > > > > > > > Click link below to report this email as spam. > > > https://www.mailcontrol.com/sr/3DY9iYaP4!7r39w1EFqnMqyXCXdO4FUjsVoyh 6aS5N4FEmP!1HRAPmogM3OjcxjD93Syur5W2CZtunTQgwTuP7V!!KZuwoZSVAucmrR2rgQ OGNiaVM6niaGOzmDM1kiNIGdfj1S974ZFrjONfMkOumM3VVLQBeUfyoE8wlh1VA3AcEiVY 62mDkUBARsCH4ulx40V!CB9C3v7YvmL6!0DaFxrVhykbxl2 > > > > > > > > > -- > ******************************************************************** *************** > Dr Claus-D. Mayer | http://www.bioss.ac.uk > Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk > Rowett Research Institute | Telephone: +44 (0) 1224 716652 > Aberdeen AB21 9SB, Scotland, UK. | Fax: +44 (0) 1224 715349 > > _______________________________________________ > 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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Hi Holger, I am not a SAM-expert, so I accept the second point you mention. My comment rather referred to a standard permutation test. I am not sure whether I agree with your first point though. In my understanding a p-value is the probability of "obtaining a result at least as extreme as a given data point" (Wikipedia agrees with me on this), i.e it is the probability of being ">=" the observed value. So if there are only 20 possible ways to split the data up into the two groups, one of them will lead to the observed value, so the p-value will be 1/20 at least. Replacing the ">=" by a ">" in the calculation of the p-value will give the wrong result ( at least if the number of permutations is small). In general exact zeros should not occur for p-values in real-life situations (mathematically you can of course construct situations, where certain values are impossible to be obtained under the null hypothesis), the zeros you will find in output occasionally are just extremely small numbers, where the non-zero entry comes at decimal point that cannot be displayed. Best Wishes Claus Holger Schwender wrote: > Hi Claus, > > this is not totally correct. If none of the permuted test scores is larger than the actual test score, then your p-value will be 0. > > Moreover, SAM uses not just the B permuted test scores of a particular gene to compute its p-values, but all mB permuted test scores of all m genes such that the p-value of a gene is given by i/mB instead of i/B, where i is the number of more extreme permuted test scores and B is the number of permutations. > > Best, > Holger > > > -------- Original-Nachricht -------- > >> Datum: Wed, 30 Jan 2008 15:27:25 +0000 >> Von: Claus-Dieter Mayer <claus at="" bioss.ac.uk=""> >> An: olivier armant <olivier.armant at="" itg.fzk.de=""> >> CC: bioconductor at stat.math.ethz.ch >> Betreff: Re: [BioC] SAM siggenes number of permutations >> > > >> Dear Oliver, >> >> my guess is that you have 2 groups with 3 samples each in which case >> there are only 20 different possible permutations and the software is >> clever enough to realise that. In that case the calculation is exact, >> but you will not find anything significant as the smallest possible >> p-value is 5% (1/20) for a one-sided and 10% (2/20) for a two- sided >> test. The problem of how large groupsizes must be in order to apply >> permutation tests was discussed on this list some time ago, have a look >> at https://stat.ethz.ch/pipermail/bioconductor/2007-November/020110.html. >> >> Hope that helps, >> >> Claus >> >> olivier armant wrote: >> >>> Dear all, >>> >>> I try to do SAM on my data using siggenes on R 2.4.1 (I am a beginner) >>> >>> The function I use is (after creating the vector) >>> sam.out<-sam(data.gcrma, sam.c1, B=100, var.equal=TRUE, Set med=TRUE) >>> >>> It seems to work well but I get allways the message: >>> number of effective permutations=20 >>> >>> Does it means that only 20 permutations were done, werheas I ask for 100 >>> >> permutations with the function B=100?? >> >>> I read in the SAM excel package from standford that a precise FDR >>> >> requires 1000 permutations!!!What do you think?? >> >>> Help would be welcome >>> >>> >>> Olivier ARMANT PhD. >>> >>> Institute of Toxicology and Genetics >>> Forschungszentrum Karlsruhe >>> Hermann-von-Helmholtz-Platz 1 >>> D-76344 Eggenstein-Leopoldshafen >>> Germany >>> >>> tel: +49-7247-82-2560 >>> fax: +49-7247-82-3354 >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> 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 >> >>> >>> >>> >>> >>> Click link below to report this email as spam. >>> >>> >> https://www.mailcontrol.com/sr/3DY9iYaP4!7r39w1EFqnMqyXCXdO4FUjsVoy h6aS5N4FEmP!1HRAPmogM3OjcxjD93Syur5W2CZtunTQgwTuP7V!!KZuwoZSVAucmrR2rg QOGNiaVM6niaGOzmDM1kiNIGdfj1S974ZFrjONfMkOumM3VVLQBeUfyoE8wlh1VA3AcEiV Y62mDkUBARsCH4ulx40V!CB9C3v7YvmL6!0DaFxrVhykbxl2 >> >> >>> >>> >> -- >> ******************************************************************* **************** >> Dr Claus-D. Mayer | http://www.bioss.ac.uk >> Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk >> Rowett Research Institute | Telephone: +44 (0) 1224 716652 >> Aberdeen AB21 9SB, Scotland, UK. | Fax: +44 (0) 1224 715349 >> >> _______________________________________________ >> 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 >> > > -- ********************************************************************** ************* Dr Claus-D. Mayer | http://www.bioss.ac.uk Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk Rowett Research Institute | Telephone: +44 (0) 1224 716652 Aberdeen AB21 9SB, Scotland, UK. | Fax: +44 (0) 1224 715349
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Hi Claus, yes, you are correct (and not only since wikipedia says so). Didn't pay attention to the fact that the vector of the actual class labels is one of the permutations of it if you do complete permutations. Sorry for that Holger -------- Original-Nachricht -------- > Datum: Thu, 31 Jan 2008 11:52:41 +0000 > Von: Claus-Dieter Mayer <claus at="" bioss.ac.uk=""> > An: Holger Schwender <holger.schw at="" gmx.de=""> > CC: olivier.armant at itg.fzk.de, bioconductor at stat.math.ethz.ch > Betreff: Re: [BioC] SAM siggenes number of permutations > Hi Holger, > > I am not a SAM-expert, so I accept the second point you mention. My > comment rather referred to a standard permutation test. I am not sure > whether I agree with your first point though. In my understanding a > p-value is the probability of "obtaining a result at least as extreme > as a given data point" (Wikipedia agrees with me on this), i.e it is the > probability of being ">=" the observed value. So if there are only 20 > possible ways to split the data up into the two groups, one of them will > lead to the observed value, so the p-value will be 1/20 at least. > Replacing the ">=" by a ">" in the calculation of the p-value will give > the wrong result ( at least if the number of permutations is small). > In general exact zeros should not occur for p-values in real-life > situations (mathematically you can of course construct situations, where > certain values are impossible to be obtained under the null hypothesis), > the zeros you will find in output occasionally are just extremely small > numbers, where the non-zero entry comes at decimal point that cannot be > displayed. > > Best Wishes > > Claus > > Holger Schwender wrote: > > Hi Claus, > > > > this is not totally correct. If none of the permuted test scores is > larger than the actual test score, then your p-value will be 0. > > > > Moreover, SAM uses not just the B permuted test scores of a particular > gene to compute its p-values, but all mB permuted test scores of all m genes > such that the p-value of a gene is given by i/mB instead of i/B, where i > is the number of more extreme permuted test scores and B is the number of > permutations. > > > > Best, > > Holger > > > > > > -------- Original-Nachricht -------- > > > >> Datum: Wed, 30 Jan 2008 15:27:25 +0000 > >> Von: Claus-Dieter Mayer <claus at="" bioss.ac.uk=""> > >> An: olivier armant <olivier.armant at="" itg.fzk.de=""> > >> CC: bioconductor at stat.math.ethz.ch > >> Betreff: Re: [BioC] SAM siggenes number of permutations > >> > > > > > >> Dear Oliver, > >> > >> my guess is that you have 2 groups with 3 samples each in which case > >> there are only 20 different possible permutations and the software is > >> clever enough to realise that. In that case the calculation is exact, > >> but you will not find anything significant as the smallest possible > >> p-value is 5% (1/20) for a one-sided and 10% (2/20) for a two- sided > >> test. The problem of how large groupsizes must be in order to apply > >> permutation tests was discussed on this list some time ago, have a look > >> at > https://stat.ethz.ch/pipermail/bioconductor/2007-November/020110.html. > >> > >> Hope that helps, > >> > >> Claus > >> > >> olivier armant wrote: > >> > >>> Dear all, > >>> > >>> I try to do SAM on my data using siggenes on R 2.4.1 (I am a beginner) > >>> > >>> The function I use is (after creating the vector) > >>> sam.out<-sam(data.gcrma, sam.c1, B=100, var.equal=TRUE, Set med=TRUE) > >>> > >>> It seems to work well but I get allways the message: > >>> number of effective permutations=20 > >>> > >>> Does it means that only 20 permutations were done, werheas I ask for > 100 > >>> > >> permutations with the function B=100?? > >> > >>> I read in the SAM excel package from standford that a precise FDR > >>> > >> requires 1000 permutations!!!What do you think?? > >> > >>> Help would be welcome > >>> > >>> > >>> Olivier ARMANT PhD. > >>> > >>> Institute of Toxicology and Genetics > >>> Forschungszentrum Karlsruhe > >>> Hermann-von-Helmholtz-Platz 1 > >>> D-76344 Eggenstein-Leopoldshafen > >>> Germany > >>> > >>> tel: +49-7247-82-2560 > >>> fax: +49-7247-82-3354 > >>> > >>> [[alternative HTML version deleted]] > >>> > >>> _______________________________________________ > >>> 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 > >> > >>> > >>> > >>> > >>> > >>> Click link below to report this email as spam. > >>> > >>> > >> > https://www.mailcontrol.com/sr/3DY9iYaP4!7r39w1EFqnMqyXCXdO4FUjsVoyh 6aS5N4FEmP!1HRAPmogM3OjcxjD93Syur5W2CZtunTQgwTuP7V!!KZuwoZSVAucmrR2rgQ OGNiaVM6niaGOzmDM1kiNIGdfj1S974ZFrjONfMkOumM3VVLQBeUfyoE8wlh1VA3AcEiVY 62mDkUBARsCH4ulx40V!CB9C3v7YvmL6!0DaFxrVhykbxl2 > >> > >> > >>> > >>> > >> -- > >> > ******************************************************************** *************** > >> Dr Claus-D. Mayer | http://www.bioss.ac.uk > >> Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk > >> Rowett Research Institute | Telephone: +44 (0) 1224 716652 > >> Aberdeen AB21 9SB, Scotland, UK. | Fax: +44 (0) 1224 715349 > >> > >> _______________________________________________ > >> 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 > >> > > > > > > -- > ******************************************************************** *************** > Dr Claus-D. Mayer | http://www.bioss.ac.uk > Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk > Rowett Research Institute | Telephone: +44 (0) 1224 716652 > Aberdeen AB21 9SB, Scotland, UK. | Fax: +44 (0) 1224 715349 > ******************************************************************** *************** > --
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@stefano-calza-2107
Last seen 10.2 years ago
How many samples do you have in each group? You can't get 100 different permutations, with 3 vs 3 comparison (for example) On Wed, Jan 30, 2008 at 03:56:15PM +0100, olivier armant wrote: <olivier>Dear all, <olivier> <olivier>I try to do SAM on my data using siggenes on R 2.4.1 (I am a beginner) <olivier> <olivier>The function I use is (after creating the vector) <olivier>sam.out<-sam(data.gcrma, sam.c1, B=100, var.equal=TRUE, Set med=TRUE) <olivier> <olivier>It seems to work well but I get allways the message: <olivier> number of effective permutations=20 <olivier> <olivier>Does it means that only 20 permutations were done, werheas I ask for 100 permutations with the function B=100?? <olivier> <olivier>I read in the SAM excel package from standford that a precise FDR requires 1000 permutations!!!What do you think?? <olivier> <olivier>Help would be welcome <olivier> <olivier> <olivier>Olivier ARMANT PhD. <olivier> <olivier>Institute of Toxicology and Genetics <olivier>Forschungszentrum Karlsruhe <olivier>Hermann-von-Helmholtz-Platz 1 <olivier>D-76344 Eggenstein-Leopoldshafen <olivier>Germany <olivier> <olivier> tel: +49-7247-82-2560 <olivier> fax: +49-7247-82-3354 <olivier> <olivier> [[alternative HTML version deleted]] <olivier> <olivier>_______________________________________________ <olivier>Bioconductor mailing list <olivier>Bioconductor at stat.math.ethz.ch <olivier>https://stat.ethz.ch/mailman/listinfo/bioconductor <olivier>Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Stefano Calza, PhD Researcher - Biostatistician *Sezione di Statistica Medica e Biometria Dipartimento di Scienze Biomediche e Biotecnologie Universit? degli Studi di Brescia - Italy Viale Europa, 11 25123 Brescia email: calza at med.unibs.it Phone: +390303717653 Fax: +390303717488
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@olivier-armant-2622
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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]] > > _______________________________________________ > 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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