Yes. Or in the devel version dge <- estimateDisp(dge, design ...) is an alternative route to NB dispersion estimation, and could subsitute for the two disp calls below. Gordon On Mon, 18 Mar 2013, Ryan C. Thompson wrote: > Ok, so the proper calling sequence would, in general, be something like this? > > dge <- DGEList(...) > dge <- calcNormFactors(dge) > dge <- estimateGLMCommonDisp(dge, design) > dge <- estimateGLMTrendedDisp(dge, design) > qlft <- glmQLFTest(dge, design, coef=...) > > > > > On 03/18/2013 07:42 PM, Gordon K Smyth wrote: >> Dear Ryan, >> >> Yes, glmQLFTest() can be substituted for glmLRT() in an edgeR analysis >> pipeline, but it assumes that trended not tagwise dispersion has been >> estimated. This is explained in the published paper Lund et al (2012). >> >> There has been no detailed description of the usage of glmQLFTest() in the >> edgeR document so far, but there will be before the next release in a few >> weeks' time. >> >> Yes, glmQLFtest() does its own tagwise dispersion moderation. This is the >> reason for the function. glmQLFTest() actually does its own trending as >> well, so that it is quite robust to the NB dispersions that it gets as >> input. The help page says: >> >> "[glmQLFTest] calls the limma function squeezeVar to conduct empirical >> Bayes smoothing of the genewise multiplicative dispersions." >> >> I don't think that you will get meaningfull results from inputing tagwise >> dispersions into glmQLTest(), i.e., it doesn't make sense to re- shrink >> values that are already shrunk. >> >> Because of the possible misunderstanding, glmQLFTest() now has a new >> calling sequence, so that it can stand alone from glmFit(). This permits >> the function to ensure that it gets the correct NB dispersion estimates. >> >> Best wishes >> Gordon >> >> --------------------------------------------- >> Professor Gordon K Smyth, >> Bioinformatics Division, >> Walter and Eliza Hall Institute of Medical Research, >> 1G Royal Parade, Parkville, Vic 3052, Australia. >> http://www.statsci.org/smyth >> >> On Mon, 18 Mar 2013, Ryan C. Thompson wrote: >> >>> Hi Gordon, >>> >>> I was looking in the devel code for edgeR and I noticed this new check >>> in glmQLFTest: >>> >>>> if(!is.null(disptype)) if(disptype=="tagwise") stop("glmfit should be >>> computed using trended dispersions, not tagwise") >>> >>> which refuses to run the quasi-likelihood F-test on a fit for tagwise >>> dispersion. Could you elaborate on this? Does glmQLFTest implement its >>> own different kind of tagwise behavior that is different from that of >>> estimateGLMTagwiseDisp? >>> >>> What would happen if I ran glmQLFTest after estimateGLMTagwiseDisp >>> (using the release version, which does not disallow it)? Would the >>> results be statistically meaningful? I have been doing this sometimes >>> because I assumed that glmQLFTest was supposed to be a "drop-in" >>> replacement for glmLRT, using all the same dispersions and such, due >>> to this quote from the glmQLFTest help text in the current release of >>> edgeR: >>> >>>> [glmQLFTest] behaves the same as ?glmLRT? except that it replaces >>> likelihood ratio tests with quasi-likelihood F-tests for coefficients >>> in the linear model. >>> >>> So, what is the correct usage of glmQLFTest with the estimate*Disp >>> family, and has this changed between the current release and devel >>> versions of edgeR? >>> >>> Thanks, >>> -Ryan Thompson ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:5}}