Hi Mike, That's what I would do. Best, Jim Michael Walter wrote: > Hi Jim, > > I perfectly agree with you that I must not block the patients when I > want to compare MSA vs Controls. For these comparisons I fitted a > model without the patients and this worked fine. What we also want to > see is the difference between the different regions in the different > diseases, e.g. Cerebellum vs Cortex in the patients having MSA. Here > I'd like to match the samples according to the donor. Can I > alternatively try to fit three independent models for each disease > instead of putting all together in one model? > > Best Regards, > > Mike > > >> Hi Mike, >> >> Michael Walter wrote: >>> Dear List, >>> >>> This one of the hundreds of "how do I create a design matrix in >>> limma question". However, I have difficulties in setting up a >>> paired design, with some error messages I really do not >>> understand. The experiment consists of 27 U133A arrays from 9 >>> patients with 3 different conditions (2 diseases plus healthy >>> controls). From each patient we have 3 different brain regions. I >>> want to compare the difference between the brain regions in the >>> different diseases. therefore I want to match the samples from >>> the individual patients. I attached the code below. When I try to >>> fit the model with lmFit I get following error message: >>> >>>> fit <- lmFit(data.norm, design) >>> Coefficients not estimable: sample_881 sample_936 Warning >>> message: In lmFit(data.norm, design) : Some coefficients not >>> estimable: coefficient interpretation may vary. >>> >>> What I dont understand is why can I calculate the coefficients >>> for all but 2 samples? I allready doublechecked my target file >>> and design matrix and can't find any clue what might be wrong >>> with these two samples, so any hint is highly appreciated. >> There is nothing wrong with these samples per se. The problem >> arises from the fact that you are trying to compute estimates for >> too many parameters, so lmFit() is informing you of this problem. >> >> When you are fitting a linear model, in essence what you are doing >> is solving equations for multiple unknown quantities. Algebraically >> you need one equation (or set of data) per unknown quantity. So for >> instance, you can solve for x with one equation, but you can't >> solve for x and y with one equation, you need two. >> >> However, you can solve for some combination of x and y with just >> one equation: >> >> x - y + 4 = 25 => x - y = 21 >> >> So what is happening is that one or more of your coefficients may >> be the difference between two parameter estimates, rather than the >> estimate of a single parameter. Which is what the 'coefficient >> interpretation may vary' is hinting at. >> >> I don't think you want to block these data on patient anyway. It >> seems to me that you have patients with various diseases from whom >> you have sampled brain tissue from various regions of the brain. So >> if you want to e.g., compare the expression of genes in the >> cerebellum of people with MSA to Co, then there is no blocking to >> be done because people either have MSA or Co, but nobody has both. >> >> Best, >> >> Jim >> >>> Best Regards, >>> >>> Mike >>> >>> >>> >>> Here is the code I used: >>> >>>> target >>> File disease patient region 1 "Cbm 628 U133A.CEL" PD 628 >>> Cerebellum 2 "Cbm 631 U133A.CEL" MSA 631 Cerebellum 3 "Cbm 650 >>> U133A.CEL" PD 650 Cerebellum 4 "Cbm 755 U133A.CEL" PD 755 >>> Cerebellum 5 "Cbm 758 U133A.CEL" Co 758 Cerebellum 6 "Cbm 769 >>> U133A.CEL" MSA 769 Cerebellum 7 "Cbm 776 U133A.CEL" MSA 776 >>> Cerebellum 8 "Cbm 881 U133A.CEL" MSA 881 Cerebellum 9 "Cbm 936 >>> U133A.CEL" Co 936 Cerebellum 10 "E4R_042a12b.CEL" Co 936 Cortex >>> 11 "I4R_012a1.CEL" PD 628 Cortex 12 "I4R_012a11.CEL" MSA 881 >>> Cortex 13 "I4R_012a2.CEL" MSA 631 Cortex 14 "I4R_012a3.CEL" PD >>> 650 Cortex 15 "I4R_012a6.CEL" PD 755 Cortex 16 "I4R_012a7.CEL" Co >>> 758 Cortex 17 "I4R_012a8.CEL" MSA 769 Cortex 18 "I4R_012a9.CEL" >>> MSA 776 Cortex 19 "pn0628_133a.CEL" PD 628 Putamen 20 >>> "pn0631_133a.CEL" MSA 631 Putamen 21 "pn0650_133a.CEL" PD 650 >>> Putamen 22 "pn0755_133a.CEL" PD 755 Putamen 23 "pn0758_133a.CEL" >>> Co 758 Putamen 24 "pn0769_133a.CEL" MSA 769 Putamen 25 >>> "pn0776_133a.CEL" MSA 776 Putamen 26 "pn0881_133a.CEL" MSA 881 >>> Putamen 27 "pn0936_133a.CEL" Co 936 Putamen >>> >>>> condition <- as.factor(paste(disease, rep(c("Cbm", "Cor", >>>> "Ptm"), each=9), sep=".")) sample <- as.factor(paste("_", >>>> patient, sep="")) >>>> >>>> >>>> design <- model.matrix(~0+condition+sample) >>>> colnames(design)[1:9] <- sort(as.character(unique(condition))) >>>> fit <- lmFit(data.norm, design) >>> Coefficients not estimable: sample_881 sample_936 Warning >>> message: In lmFit(data.norm, design) : Some coefficients not >>> estimable: coefficient interpretation may vary. >>>> sessionInfo() >>> R version 2.7.0 (2008-04-22) i386-pc-mingw32 >>> >>> locale: >>> LC_COLLATE=German_Germany.1252;LC_CTYPE=German_Germany.1252;LC_MON ETARY=German_Germany.1252;LC_NUMERIC=C;LC_TIME=German_Germany.1252 >>> >>> >>> >>> attached base packages: [1] tools stats graphics grDevices utils >>> datasets methods [8] base >>> >>> other attached packages: [1] affy_1.18.2 preprocessCore_1.2.0 >>> affyio_1.8.0 [4] Biobase_2.0.1 limma_2.14.5 >>> >>> loaded via a namespace (and not attached): [1] >>> scatterplot3d_0.3-27 >>> >>> >>> >>> ------------------------------------------------------------------ ------ >>> >>> >>> >>> _______________________________________________ Bioconductor >>> mailing list Bioconductor at stat.math.ethz.ch >>> https://stat.ethz.ch/mailman/listinfo/bioconductor Search the >>> archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >> -- James W. MacDonald, M.S. Biostatistician Hildebrandt Lab 8220D >> MSRB III 1150 W. Medical Center Drive Ann Arbor MI 48109-0646 >> 734-936-8662 >> >> _______________________________________________ Bioconductor >> mailing list Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor Search the >> archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > -- Dr. Michael Walter > > The Microarray Facility University of Tuebingen Calwerstr. 7 72076 > T?bingen/GERMANY > > Tel.: +49 (0) 7071 29 83210 Fax. + 49 (0) 7071 29 5228 > > Confidentiality Note: This message is intended only for the use of > the named recipient(s) and may contain confidential and/or > proprietary information. If you are not the intended recipient, > please contact the sender and delete the message. Any unauthorized > use of the information contained in this message is prohibited -- James W. MacDonald, M.S. Biostatistician Hildebrandt Lab 8220D MSRB III 1150 W. Medical Center Drive Ann Arbor MI 48109-0646 734-936-8662