limma - design matrix for time series
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@sebastian-mueller-2753
Last seen 9.6 years ago
dear members, I have a general question about the creation of design matrices for non-reference designs in limma. The set-up of the experiment I'm refering to looks like this: ------------------ 0h 1h 2h 4h 3 7 11 A > C > E > G ^ 1 ^ 5 ^ 9 ^ 13 v 2 v 6 v 10 v 14 B > D > F > H 4 8 12 ------------------ The experiment consists, as you hopefully can guess, of 14 arrays (each arrow is a two-color array which points from cyc5 to cyc3). Array 1 and 2 (5-6,9-10,13-14) correspond to a dye-swaps. Each letter (A-H) corresponds to another condition (however A and B should be the same condition) So, I'm interrested in the contrasts A-B, C-D, E-F, G-H for the time points 0h, 1h, 2h, 4h, respectively. The easiest way to do this (from the limma guide), would probably be to create a target-frame... targets <- as.data.frame(cbind( Cy3=c("B","A","A","B","D","C","C","D","F","E","E","F","H","G"), Cy5=c("A","B","C","D","C","D","E","F","E","F","G","H","G","H"))) rownames(targets) <- paste("Array",1:14) > targets Cy3 Cy5 Array 1 B A Array 2 A B Array 3 A C Array 4 B D Array 5 D C Array 6 C D Array 7 C E Array 8 D F Array 9 F E Array 10 E F Array 11 E G Array 12 F H Array 13 H G Array 14 G H ... and creating a design-matrix: > design=modelMatrix(targets,ref="A") Found unique target names: A B C D E F G H > design B C D E F G H Array 1 -1 0 0 0 0 0 0 Array 2 1 0 0 0 0 0 0 Array 3 0 1 0 0 0 0 0 Array 4 -1 0 1 0 0 0 0 Array 5 0 1 -1 0 0 0 0 Array 6 0 -1 1 0 0 0 0 Array 7 0 -1 0 1 0 0 0 Array 8 0 0 -1 0 1 0 0 Array 9 0 0 0 1 -1 0 0 Array 10 0 0 0 -1 1 0 0 Array 11 0 0 0 -1 0 1 0 Array 12 0 0 0 0 -1 0 1 Array 13 0 0 0 0 0 1 -1 Array 14 0 0 0 0 0 -1 1 cont=makeContrasts(C-D,E-F,G-H,levels=design) ... --------------------- As I actually don't have a reference design, I'm wondering if this is ok to do this. My problem is that I can't get the contrast A-B from this design. I already tried to append a colum A to this matrix by hand, but calling >lmFit(MA, design) gives me: Coefficients not estimable: A As I probably haven't really understood the concept of creating a design matrix (I have already looked trough the limma guide), I was wondering if someone knows a good tutorial or book (I was already looking for hours, but there is not such a thing for limma and time series analysis) I'm espacially wondering how I can solve this problem intuitively (as I was going to use limma for my future time-series experiments) and I also would like to know if my approch to tackle this problem is appropriate in general. Thanks a lot Sebastian Mueller ------ Max-Planck-Institute for Chemical Ecology Department of Biochemistry Hans-Knoell-Strasse 8 D-07745 Jena Germany
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Naomi Altman ★ 6.0k
@naomi-altman-380
Last seen 3.0 years ago
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I always use the single channel analysis (see the guide) for this type of analysis. It is simple to set up because you will do your contrasts directly on the treatment means not on differences and is actually more powerful than the 2-channel analysis. --Naomi At 07:45 AM 4/17/2008, Sebastian Mueller wrote: >dear members, > >I have a general question about the creation of design matrices for >non-reference designs in limma. > >The set-up of the experiment I'm refering to looks like this: >------------------ > 0h 1h 2h 4h > > 3 7 11 > A > C > E > G > ^ 1 ^ 5 ^ 9 ^ 13 > v 2 v 6 v 10 v 14 > B > D > F > H > 4 8 12 >------------------ >The experiment consists, as you hopefully can guess, of 14 arrays (each arrow >is a two-color array which points from cyc5 to cyc3). >Array 1 and 2 (5-6,9-10,13-14) correspond to a dye-swaps. >Each letter (A-H) corresponds to another condition (however A and B should be >the same condition) > >So, I'm interrested in the contrasts A-B, C-D, E-F, G-H for the time points >0h, 1h, 2h, 4h, respectively. > >The easiest way to do this (from the limma guide), would probably be >to create >a target-frame... > >targets <- as.data.frame(cbind( >Cy3=c("B","A","A","B","D","C","C","D","F","E","E","F","H","G"), >Cy5=c("A","B","C","D","C","D","E","F","E","F","G","H","G","H"))) >rownames(targets) <- paste("Array",1:14) > > targets > Cy3 Cy5 >Array 1 B A >Array 2 A B >Array 3 A C >Array 4 B D >Array 5 D C >Array 6 C D >Array 7 C E >Array 8 D F >Array 9 F E >Array 10 E F >Array 11 E G >Array 12 F H >Array 13 H G >Array 14 G H > >... and creating a design-matrix: > > > design=modelMatrix(targets,ref="A") >Found unique target names: > A B C D E F G H > > design > B C D E F G H >Array 1 -1 0 0 0 0 0 0 >Array 2 1 0 0 0 0 0 0 >Array 3 0 1 0 0 0 0 0 >Array 4 -1 0 1 0 0 0 0 >Array 5 0 1 -1 0 0 0 0 >Array 6 0 -1 1 0 0 0 0 >Array 7 0 -1 0 1 0 0 0 >Array 8 0 0 -1 0 1 0 0 >Array 9 0 0 0 1 -1 0 0 >Array 10 0 0 0 -1 1 0 0 >Array 11 0 0 0 -1 0 1 0 >Array 12 0 0 0 0 -1 0 1 >Array 13 0 0 0 0 0 1 -1 >Array 14 0 0 0 0 0 -1 1 > >cont=makeContrasts(C-D,E-F,G-H,levels=design) >... > >--------------------- >As I actually don't have a reference design, I'm wondering if this >is ok to do >this. >My problem is that I can't get the contrast A-B from this design. I already >tried to append a colum A to this matrix by hand, but calling > >lmFit(MA, design) >gives me: Coefficients not estimable: A > >As I probably haven't really understood the concept of creating a design >matrix (I have already looked trough the limma guide), I was wondering if >someone knows a good tutorial or book (I was already looking for hours, but >there is not such a thing for limma and time series analysis) > >I'm espacially wondering how I can solve this problem intuitively (as I was >going to use limma for my future time-series experiments) and I also would >like to know if my approch to tackle this problem is appropriate in general. > >Thanks a lot > >Sebastian Mueller > >------ >Max-Planck-Institute for Chemical Ecology >Department of Biochemistry >Hans-Knoell-Strasse 8 >D-07745 Jena >Germany > >_______________________________________________ >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 Naomi S. Altman 814-865-3791 (voice) Associate Professor Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111
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