[BioC] limma - design matrix for time series

[Naomi Altman]

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
>
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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