Hi Sir, I have a simple question regarding cut-off parameter to be used for filtering out DEGs from the topT object obtained using LIMMA. Which statistics is preferred more and why? 1) filter of adj.p.value and log2FC. 2) filter of B.value and log2FC. I mean both give similar ranking of genes but usually I have seen people using an adj.p.value cut-off of 0.01. What is the minimum cut- off value for B.value?(Is it 4?) It is a technical question so I do not have any output to be put in the next sessionInfo() field. Thank you for your input Sir. Regards. Deb. -- output of sessionInfo(): topT<- topTable(fit3, coef=1, adjust="BH", sort.by="B",number=nrow(data)) -- Sent via the guest posting facility at bioconductor.org.

Dear Deb, I used adjusted.p.value (with fdr) <0.05 because it takes multiple tests into account in computing the signficance. If I have fewer than (say) 50 genes I make the fdr more lenient. If more that 1K genes, I filter by the absolute value of log2FC as well. with hopes that the above helps, Rich On Dec 2, 2013, at 1:15 PM, deb [guest] wrote: > > Hi Sir, > I have a simple question regarding cut-off parameter to be used for filtering out DEGs from the topT object obtained using LIMMA. > Which statistics is preferred more and why? > 1) filter of adj.p.value and log2FC. > 2) filter of B.value and log2FC. > I mean both give similar ranking of genes but usually I have seen people using an adj.p.value cut-off of 0.01. What is the minimum cut- off value for B.value?(Is it 4?) > It is a technical question so I do not have any output to be put in the next sessionInfo() field. > Thank you for your input Sir. > Regards. > Deb. > > > > -- output of sessionInfo(): > > topT<- topTable(fit3, coef=1, adjust="BH", sort.by="B",number=nrow(data)) > > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor Richard A. Friedman, PhD Associate Research Scientist, Biomedical Informatics Shared Resource Herbert Irving Comprehensive Cancer Center (HICCC) Lecturer, Department of Biomedical Informatics (DBMI) Educational Coordinator, Center for Computational Biology and Bioinformatics (C2B2)/ National Center for Multiscale Analysis of Genomic Networks (MAGNet)/ Columbia Department of Systems Biology Room 824 Irving Cancer Research Center Columbia University 1130 St. Nicholas Ave New York, NY 10032 (212)851-4765 (voice) friedman at cancercenter.columbia.edu http://friedman.c2b2.columbia.edu/ In memoriam, Frederik Pohl

Dear Deb, Well, this is not really a simple question at all. The way that you prioritise your discoveries is not just a matter of statistics, but also depends on the context and aims of your study. That is why limma offers different options. If you want to know what the limma developers do, have a look at the case studies in the limma User's Guide. We do not actually recommend either of the options that you mention. The most common analysis would be to simply choose genes by FDR. But please don't ask me what cutoff you should use for FDR. It is quite common to use 0.05 or 0.1, but there is no correct value and this is for you to decide on the basis of the science of your own study. If you want to give even more priority to larger fold changes, then we recommend that you use treat(). This is better than just cutting on estimated logFC value. There is no B.value cutoff. The B-statistic is for ranking, not for absolute cutoff. I do not know where you might have got the cutoff value "4" from. I have not seen anyone suggest this. To use the B-statistic for absolute cutoff would require estimating the overall proportion of DE genes, which limma can do by propTrueNull but doesn't do by default. Best wishes Gordon > Date: Mon, 2 Dec 2013 10:15:53 -0800 (PST) > From: "deb [guest]" <guest at="" bioconductor.org=""> > To: bioconductor at r-project.org, devbt15 at gmail.com > Subject: [BioC] (adj.p.value & log2FC) or (B.value & log2FC) > > > Hi Sir, > I have a simple question regarding cut-off parameter to be used for filtering out DEGs from the topT object obtained using LIMMA. > Which statistics is preferred more and why? > 1) filter of adj.p.value and log2FC. > 2) filter of B.value and log2FC. > I mean both give similar ranking of genes but usually I have seen people using an adj.p.value cut-off of 0.01. What is the minimum cut- off value for B.value?(Is it 4?) > It is a technical question so I do not have any output to be put in the next sessionInfo() field. > Thank you for your input Sir. > Regards. > Deb. > > > > -- output of sessionInfo(): > > topT<- topTable(fit3, coef=1, adjust="BH", sort.by="B",number=nrow(data)) ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}