Hello, I gets the following table with siggenes package: Delta p0 False Called FDR 1 5 0,259 2,625 21 0,0323 2 12,4 0,259 2,125 17 0,0323 3 19,8 0,259 1,75 14 0,0323 4 27,2 0,259 0,875 7 0,0323 5 34,5 0,259 0,25 2 0,0323 6 41,9 0,259 0,25 2 0,0323 7 49,3 0,259 0,25 2 0,0323 8 56,6 0,259 0,25 2 0,0323 9 64 0,259 0,25 2 0,0323 10 71,4 0,259 0 0 0 I have the following questions: 1. can someone give me please detailed description over the parameters? (Delta p0 False Called FDR) 2. How is computed the parameters? 3. How can I interpret the results correct? 4. I found no suitable literature over it (except 2 articles by Robert Tibshirani and 1 by Holger Schwender ). How can I find more literature over it? Thanks in advance, Mohammad Esad-Djou Interdisziplin?res Zentrum f?r Bioinformatik (IZBI) Universit?t Leipzig H?rtelstr. 16 - 18 D-04107 Leipzig

Hi Mohammed, > --- Urspr?ngliche Nachricht --- > Von: Mohammad Esad-Djou <shahrgol at="" web.de=""> > An: bioconductor at stat.math.ethz.ch > Betreff: [BioC] SAM and siggenes: 4 questions > Datum: Sat, 25 Mar 2006 16:02:39 +0100 > > Hello, > I gets the following table with siggenes package: > > > Delta p0 False Called FDR > 1 5 0,259 2,625 21 0,0323 > 2 12,4 0,259 2,125 17 0,0323 > 3 19,8 0,259 1,75 14 0,0323 > 4 27,2 0,259 0,875 7 0,0323 > 5 34,5 0,259 0,25 2 0,0323 > 6 41,9 0,259 0,25 2 0,0323 > 7 49,3 0,259 0,25 2 0,0323 > 8 56,6 0,259 0,25 2 0,0323 > 9 64 0,259 0,25 2 0,0323 > 10 71,4 0,259 0 0 0 > > I have the following questions: > > 1. can someone give me please detailed description over the parameters? > (Delta p0 False Called FDR) > Delta are the Delta values mentioned in the Tibshirani papers and in my tech report. Delta is the distance between the two cut-off lines and the 45 degree line. p0 (actually pi_0) is the prior probability that a gene is not differentially expressed. False are the number of the so called falsely called genes if the specified threshold Delta is used. Called is the number of genes called differentially expressed if the corresponding value of Delta is used as threshold. FDR is the False Discovery Rate, i.e. the error rate, if the corresponding Delta is used as threshold, where FDR = p0 * False / Called. All these terms (not my sometimes cryptical abbreviations in the above table) are explained in the Tibshirani papers or my tech report. A more detailed description on the implementation of siggenes than the one in the tech report is available in my diploma thesis http://de.geocities.com/holgerschw/thesis.pdf > 2. How is computed the parameters? > Technical details on the siggenes implementation can be found in the tech report or in the diploma thesis. Some little things have changed since then. But they are rather unimportant for the SAM analysis itself. E.g., the way the group labels are permuted has been changed. Not so important, but if you are interested see ?sam.dstat for a short description of the new way of permuting. > 3. How can I interpret the results correct? > For example, choosing Delta as 27.2 leads in your analysis to 7 differentially expressed genes and a FDR of 0.0323 which loosely spoken means that about 3% of the 7 genes called differentially expressed are actually not really differentially expressed. Your task now is to find a Delta value that provides a good balance between the number of identified genes (Called in the above table) and the estimated FDR. A note: - By taking a look at the Delta values it seems that you are using the gene expression data on the original scale. It would be better to take the logarithm to the basis 2 of your data and put this log_2 transformed data into sam. > 4. I found no suitable literature over it (except 2 articles by Robert > Tibshirani and 1 by Holger Schwender ). How can I find more literature over > it? > The abovementioned diploma thesis. HTH, Holger > > Thanks in advance, > Mohammad Esad-Djou > > > Interdisziplin?res Zentrum f?r Bioinformatik (IZBI) > Universit?t Leipzig > H?rtelstr. 16 - 18 > D-04107 Leipzig > > _______________________________________________ > 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 > --