Hi Gordon, I seem to learn something new about edgeR everytime I use it.
Thanks for the help! Best, Sean On Fri, Sep 16, 2011 at 5:47 PM, Gordon K Smyth <sm...@wehi.edu.au> wrote: > Dear Sean, > > The dispersion estimation functions in edgeR have a lower limit for the > dispersions that they will estimate. For estimateCommonDisp(), the lower > limit is just above 0.0001. For estimateTagwiseDisp() the lower limit is > just above 0.001. For your data, the ideal dispersion estimate appears to > be zero, so the functions are simply returning to you the pre-set lower > limits. > > I agree that was a bit sloppy of us (the edgeR authors) for the lower > limits to be inconsistent between the functions. The reason for > estimateTagwiseDisp() having a higher limit is that it does a grid search, > so we wanted to limit the number of grid points for computational > efficiency. > > The new glm functions in edgeR, estimateGLMCommonDisp() etc have somewhat > less restrictive lower limits than the classic functions that you are using. > > The bottom line is that with technical data such as the yeast data, we do > not view the differences between dispersion estimates of 1e-3 or 1e-4 as > scientifically meaningful. We would simply observe that the dispersion > appears to be at the lower boundary, showing that the data has essentially > no biological variability. We would set the dispersions to be zero. > > Best wishes > Gordon > > Date: Thu, 15 Sep 2011 18:03:28 -0700 >> From: Sean Ruddy <srudd...@gmail.com> >> To: bioc-sig-sequencing@r-project.**org<bioc-sig-sequencing@r-project.org> >> Subject: [Bioc-sig-seq] edgeR tagwise estimates not converging to >> common estimate with large prior.n value >> >> Hi, >> >> Thanks in advance for any help. I have the latest R software (2.13.1) and >> edgeR software (2.8.4). I'm running into a problem where I estimate a >> common >> dispersion parameter of 0.0001 and when I subsequently estimate tagwise >> dispersions using the default prior.n = 10, the summary statistics are >> >> Min. 1st Qu. Median Mean 3rd Qu. Max. >> 0.001 0.001 0.001 0.001 0.001 0.022 >> >> ie, all estimates are 10 times larger than the common dispersion estimate. >> Since the method is supposed to shrink toward the common value this seems >> a >> little surprising. When I increase prior.n to a large number I expect the >> tagwise estimates to all converge to the common dispersion, but as you >> might >> guess from the table above it converges to 0.001 = 10*common. >> >> The data comes from the bioconductor package "yeastRNASeq" and it appears >> from the description of the data that the two samples in each group are >> actually from sequencing the same extraction of mRNA, ie not biological >> and >> not even really technical replicates. So the common dispersion should be >> zero as the counts should follow the poisson. >> >> I cannot explain the behavior of the estimates but I'm afraid it might be >> something in the code so I'll include that below. >> >> library(yeastRNASeq) >> data( geneLevelData ) >> d <- DGEList( geneLevelData , group = c( rep( "Mutant" , 2 ) , rep( "Wild" >> , >> 2 ) ) ) >> d <- calcNormFactors( d ) >> d <- d[rowSums(d$counts) >= 5, ] >> d <- estimateCommonDisp( d ) >> >> d$common.dispersion >> [1] 0.000101 >> >> d <- estimateTagwiseDisp( d , prior.n = 10 ) >> >> summary( d$tagwise.dispersion ) >> Min. 1st Qu. Median Mean 3rd Qu. Max. >> 0.001 0.001 0.001 0.001 0.001 0.022 >> >> d <- estimateTagwiseDisp( d , prior.n = 1000 ) >> >> summary( d$tagwise.dispersion ) >> Min. 1st Qu. Median Mean 3rd Qu. Max. >> 0.001 0.001 0.001 0.001 0.001 0.001 >> >> >> It could just be an oddity of the data set itself but I don't have enough >> experience using edgeR across different RNA-Seq experiments to know how >> these methods should behave. >> >> >> Thanks, >> Sean >> > > ______________________________**______________________________**__________ > The information in this email is confidential and inte...{{dropped:10}} _______________________________________________ Bioc-sig-sequencing mailing list Bioc-sig-sequencing@r-project.org https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing