Steve, I have reread the paper and believe that the "genes of biological interest filter" about which I am asking, is qualitatively different than the numerical filters in the paper. I will follow Moshe and Kasper's advice and use the moderated t-statistic. Thanks and best wishes, Rich On May 17, 2012, at 11:54 AM, Steve Lianoglou wrote: > Hi Richard, > > It seems to me that this paper is highly relevant to the question you > are trying to answer: > > Independent filtering increases detection power for high-throughput > experiments > http://www.pnas.org/content/107/21/9546.full > > Perhaps you can see where your "filtering scheme" lands in the > landscape of filters described there. > > HTH, > -steve > > On Thu, May 17, 2012 at 9:25 AM, Richard Friedman > <friedman at="" cancercenter.columbia.edu=""> wrote: >> Moshe, >> >> Thank you for the clarification on the moderated t-statistic. >> If I am only interested in 10 genes is it better to calculate the >> moderated >> statistic and hence raw p-values based on all of the genes on the >> array >> or just thoe 10 genes? >> >> Best wishes, >> Rich >> >> >> On May 17, 2012, at 12:35 AM, Moshe Olshansky wrote: >> >>> Hi Rich, >>> >>> I think that Gordon Smyth (the author of limma) has explained at >>> this list >>> what moderated t-statistic is. >>> The brief explanation is that when there are few samples the >>> estimate of >>> the variance which is used in a standard t-test is quite noisy and >>> because >>> one must account for this noise the standard t-test has a low >>> statistical >>> power. The Empirical Bayes model used in the moderated t-tests >>> allows to >>> estimate the variance with more confidence and therefore has a >>> better >>> power. So it can be used even if you are interested in just a few >>> genes. >>> It has (almost) nothing to do with the multiple testing >>> adjustment. Well, >>> one may ask whether moderated p-values satisfy the assumptions of >>> multiple >>> testing adjustment procedures (in particular the BH), but this is >>> another >>> story. May be Gordon will comment on this. >>> >>> Best regards, >>> Moshe. >>> >>>> Moshe and List, >>>> >>>> Thanks for yoru reply. The method you describe retains >>>> the raw p-value based on the moderated t-statistic and adjusts >>>> it to give an adjusted p-value (usually a false discovery rate). >>>> However, as I understand it, the moderated >>>> t-statistic given by Limma based on >>>> all of the genes in the array, pools variance information >>>> to moderate the standard deviation to prevent fortuitously >>>> low p-values stemming from fortuitously low standard deviations >>>> encountered in thousands of multiple tests.I am wondering >>>> that if the experimentalist asks me to look up just 10 genes >>>> I should use the unmoderated frequentist t-statistic which >>>> will differ from the one in Limma and may imply significance >>>> where Limma does not. I guess another way to phrase it is >>>> "How many simulataneous tests does one need before one >>>> should prefer the moderated statistic to the empirical >>>> Bayesian one". Or should I fit just those 10 genes >>>> (~30 affy probes) with Limma? >>>> >>>> Best wishes, >>>> Rich >>>> >>>> >>>> >>>> On Thu, 17 May 2012, Moshe Olshansky wrote: >>>> >>>>> Hi Rich, >>>>> >>>>> Whether to use the moderated t-statistic or not does not depend on >>>>> whether >>>>> you are interested in the 10 particular genes or in all >>>>> differentially >>>>> expressed ones. This will affect your multiple testing adjustment. >>>>> The simplest way for you to proceed is to use limma as usual, >>>>> get the >>>>> topTable but then take the UNADJUSTED p-values for your 10 genes >>>>> of >>>>> interest and use the p.adjust function to adjust for multiple >>>>> testing if >>>>> you wish. In any case you should also look at (log)Fold Changes. >>>>> >>>>> Best regards, >>>>> Moshe. >>>>> >>>>> >>>>>> Dear Bioconductor List. >>>>>> >>>>>> I am using Limma to analyze differential expression >>>>>> between 2 >>>>>> conditions on an Affy chip. >>>>>> My experimental collaborator asks for the differential >>>>>> expression of >>>>>> 10 predefined genes. >>>>>> >>>>>> A, Should I correct for false discoveries based upon all of the >>>>>> genes >>>>>> on the chip? >>>>>> B. If not, should I correct for false discoveries just for the >>>>>> probeids for the 10 predefined >>>>>> genes? >>>>>> C. Should I use the moderated t-statistic or just use an >>>>>> unmoderated t- >>>>>> test for those 10 >>>>>> genes. >>>>>> >>>>>> Thanks and best wishes, >>>>>> Rich >>>>>> ------------------------------------------------------------ >>>>>> 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) >>>>>> 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://cancercenter.columbia.edu/~friedman/ >>>>>> >>>>>> "School is an evil plot to suppress my individuality" >>>>>> >>>>>> Rose Friedman, age15 >>>>>> >>>>>> _______________________________________________ >>>>>> 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 >>>> Herbert Irving Comprehensive Cancer Center >>>> Biomedical Informatics Shared Resource >>>> Lecturer >>>> Department of Biomedical Informatics >>>> Box 95, Room 130BB or P&S 1-420C >>>> Columbia University Medical Center >>>> 630 W. 168th St. >>>> New York, NY 10032 >>>> (212)305-6901 (5-6901) (voice) >>>> friedman at cancercenter.columbia.edu >>>> http://cancercenter.columbia.edu/~friedman/ >>>> >>>> "The last 250 pages of the last Harry Potter >>>> book took place in one day because alot >>>> happened in that day. All of Ulysses takes >>>> place in one day and nothing happened in that day." >>>> -Rose Friedman, age 11 >>>> >>>> >>> >>> >>> >>> ______________________________________________________________________ >>> The information in this email is confidential and inte...{{dropped: >>> 6}} >> >> >> _______________________________________________ >> 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 > > > > -- > Steve Lianoglou > Graduate Student: Computational Systems Biology > | Memorial Sloan-Kettering Cancer Center > | Weill Medical College of Cornell University > Contact Info: http://cbio.mskcc.org/~lianos/contact