Dear Yang, On Tue, 30 Apr 2013, Yang Liu wrote: > Dear Prof. Smyth, > > Thanks for your reply. Great to hear back from you. I see your points, but > it still confuses me. > > First, thank you for confirming that my interpretation of the intercept is > correct. To me, it also cancels out in any contrast, as you may find the > 1st coefficient of my contrast is also zero. > > Also, I agree that we are fitting an additive model (patient + treatment) > within each disease group, that is why there is no interaction between > patient and treatment. > > However, the case is that we are estimating the patient's effect nested in > each disease as a fixed effect (not a random effect). Then, the patients in > Healthy group are different from the patients in Disease1 group, hence > patient's nested effects could not cancel out in the contrast. You are not fully understanding how a paired analysis works. Treatments are compared only within patients. The between-patient error strata is not used at all in the analysis. > Generally, based on the design (see the attached figure), if we are > trying to find genes that respond differently to the hormone in disease1 > vs healthy patients, we should average observation 8, 10 and 12 (the > average log-fold-change after hormone treatment for patients in disease > group 1), then subtract the average of observation 2, 4 and 6 (the > average log-fold-change after hormone treatment for healthy patients). No, this is in incorrect. You have failed to adjust for the baseline expression level for each individual patient when treatment="none". If this is still unclear, your PhD advisor or professors might be able to help. Best wishes Gordon > And it ends up with my contrast showed in my previous thread (i.e. *lrt > <- glmLRT(fit, contrast = c(0, 1, 0, -1/3, 1/3, 0, -1/3, 1/3, 0, -1, 1, > 0))*) > > Also, we can find in the design, the observation 1 (first row in the > design, healthy patient 1 without treatment) has only coefficient on > Intercept, which is consistent with the concept that the intercept > (baseline) represents the combined effect from Healthy, Patient 1, and None > Treatment. Meanwhile, besides intercept, the observation 2 (second row in > the design, healthy patient 1 with treatment) has another coefficient on > "DiseaseHealthy:TreatmentHormone". Hence, we could say that the coefficient > "DiseaseHealthy:TreatmentHormone" only represents the difference of > log-fold-change between "with and without hormone treatment" for healthy > patient 1. We can also check other observations. Especially, for the > observation 4 (healthy patient 2 with treatment), it has coefficients on > intercept, "DiseaseHealthy:Patient2", and > "DiseaseHealthy:TreatmentHormone". > > Hence, I still insist that my contrast would be more appropriate. Hope my > points make sense to you. If not, please feel free to correct me. Thanks > for your time and helps. > > Sincerely, > > Yang > > > > On Mon, Apr 29, 2013 at 4:17 AM, Gordon K Smyth <smyth at="" wehi.edu.au=""> wrote: > >> Dear Yang Liu, >> >> I believe that the documentation is correct as it stands. >> >> The coefficient "DiseaseHealthy:**TreatmentHormone" represents the >> average log-fold-change after hormone treatment for healthy patients. The >> coefficient "DiseaseDisease1:**TreatmentHormone" represents the average >> log-fold-change after hormone treatment for patients in disease group 1. So >> taking the difference of these two coefficients represents the contrast as >> described in the documentation. >> >> The linear model here is equivalent to three paired t-tests, one for each >> disease group. In effect we are fitting an additive model >> (patient+treatment) within each disease group. >> >> You are correct in your interpretation of the intercept term, but this is >> not relevant because it cancels out of any contrast. >> >> Best wishes >> Gordon >> >> ---------------- original message ---------------- >> >> [BioC] Possible Bugs in Contrasts Design of edgeR >> Yang Liu [guest] guest at bioconductor.org >> Thu Apr 25 17:59:21 CEST 2013 >> >> Hi, >> >> I am a PhD student from Dept. Statistics of Penn State University. I have >> been using edgeR for my RNA-seq data recently. As I moved forward with >> edgeR, I found there are probably some bugs in the latest documentation. >> >> My experimental design is exactly the same as the design (Comparisons Both >> Between and Within Subject) on page 32 in the latest documentation (last >> revised on 31 March 2013). From page 32 to 34, everything looks fine to me >> except for the contrasts defined at the end. >> >> If I understand it properly, with the procedure showed on those pages, I >> can estimate each effect in the design, which can be showed with >> colnames(design). Then, all contrasts should be based on those estimated >> effects. For the first contrast on page 34, it is trying to find genes that >> respond differently to the hormone in disease1 vs healthy patients. The >> contrast looks as follows: >> >> lrt <- glmLRT(fit, contrast = c(0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 1, 0)) >> >> However, it looks not right to me, and it only put weights on the 10th and >> 11th effects ("-1" and "1"), which are corresponding to "DiseaseHealthy:**TreatmentHormone" >> and "DiseaseDisease1:**TreatmentHormone". As I see, the intercept >> (baseline) represents the combined effect from Healthy, Patient 1, and None >> Treatment. In order to find genes that respond differently to the hormone >> in disease1 vs healthy patients (regardless which patient it is), you could >> not leave the weights for all 4th to 9th effects as zeros. Also, as the >> contrast compares disease1 to healthy, the weight in the contrast for the >> 2nd effect should not be zero as well. I think the right contrast should be >> as follows: >> >> lrt <- glmLRT(fit, contrast = c(0, 1, 0, -1/3, 1/3, 0, -1/3, 1/3, 0, -1, >> 1, 0)) >> >> Please feel free to correct me if I am wrong. >> >> Thanks, >> >> Yang Liu >> >> -- output of sessionInfo(): >> >> R version 2.15.2 (2012-10-26) >> Platform: x86_64-apple-darwin9.8.0/x86_**64 (64-bit) >> >> locale: >> [1] en_US.UTF-8/en_US.UTF-8/en_US.**UTF-8/C/en_US.UTF-8/en_US.UTF-**8 >> >> attached base packages: >> [1] stats graphics grDevices utils datasets methods base >> >> other attached packages: >> [1] edgeR_3.0.8 limma_3.14.4 >> ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}