[BioC] loop design question

[Gordon K Smyth]

> Date: Mon, 8 Aug 2005 10:38:10 +0200
> From: Matja? Hren <Matjaz.Hren at nib.si>
> Subject: Re: [BioC] loop design question
> To: <smyth at wehi.edu.au>, <scholz at Ag.arizona.edu>
> Cc: bioconductor at stat.math.ethz.ch
>
> Hello,
>
> This short debate encouraged me to ask another question regarding direct microarray design and
> limma's design matrix.
>
> We compare response of plants to viral infection an several varieties of the sam plant species
> (potato). We don't use a common reference but we hybridise on each array infected (V) and healthy
> plant (M - mock infected) - for lets say 2 cultivars ( indexes "s", "i").  There are 3 biological
> repetitions including dyswaps - as seen in the targets file (below).
>
> My question is if the design matrix we created (down  below) is OK? In the "CD8 vs CD4 and DN vs
> CD4" case described in Limma User's Guide and discussed below the CD4 was used as a virtual common
> reference. Do you have any suggestions what could be used as a "virtual common reference" in our
> case or it doesn't matter what we choose for it?

Well, yes, you could analyse the experiment in principle with any choice of virtual common
reference.  But your experiment is hardly a "loop design".  Your experiment has a definite special
structure, which presumably arises from the fact that you are interested in the effect of
infection on each of the varieties.  A sensible analysis should reflect this structure and should
return quantities that are of interest to you.  There is no way for a program like limma to give
you canned analyses for every possible scientific situation.  The package is rather designed to
give you the flexibility to tailor the analysis to your experiment.

You experiment has been designed to estimate the effect of infection on each variety.  You should
design the analysis to do the same thing.  You could do this by

design <- cbind(I=c(-1,1,-1,0,0,0), S=c(0,0,0,-1,1,1))

In your linear model, the first coefficient will now be the effect of V over M or variety "i",
while  the second coefficient will be the effect of V over M for variety "s".  You could use a
contrast to test whether the two coefficients are different, i.e., to compare varieties.

This approach extends easily to any number of varieties.

Gordon

> Could we also include additional microarrays with the same experimental layout but done on two
> additional varietis of the plants (lets say indexes "c" and "n")in the experiment? And would then
> the logics of the design matrix construction still stay the same - see below (pick one virtual
> common reference)? Or would it be better if we used ANOVA to compare varieties?
>
>
>> targets<-readTargets("C:/Uporabniki/RRR/phenoDataIS.txt")
>> targets
>           fileName slide.number variety Cy5 Cy3
> 1 I_30m_1_1042.txt     12901042       I  Mi  Vi
> 2 I_30m_2_1109.txt     12901109       I  Vi  Mi
> 3 I_30m_3_1040.txt     12901040       I  Mi  Vi
> 4 S_30m_1_1103.txt     12901103       S  Ms  Vs
> 5 S_30m_2_1039.txt     12901039       S  Vs  Ms
> 6 S_30m_3_1106.txt     12901106       S  Vs  Ms
>
>> design <- modelMatrix(targets, ref="Mi")
> Found unique target names:
>  Mi Ms Vi Vs
>
>> design
>   Ms Vi Vs
> 1  0 -1  0
> 2  0  1  0
> 3  0 -1  0
> 4  1  0 -1
> 5 -1  0  1
> 6 -1  0  1
>
> And now for the four varieties (reference would be "Mi"):
>
> targets<-readTargets("C:/Uporabniki/RRR/phenoDataISCN.txt")
>
>> design <- modelMatrix(targets, ref="Mi")
> Found unique target names:
>  Mc Mi Mn Ms Vc Vi Vn Vs
>
>> design
>    Mc Mn Ms Vc Vi Vn Vs
> 1   0  0  0  0 -1  0  0
> 2   0  0  0  0  1  0  0
> 3   0  0  0  0 -1  0  0
> 4   0  0  1  0  0  0 -1
> 5   0  0 -1  0  0  0  1
> 6   0  0 -1  0  0  0  1
> 7   1  0  0 -1  0  0  0
> 8  -1  0  0  1  0  0  0
> 9   1  0  0 -1  0  0  0
> 10  0  1  0  0  0 -1  0
> 11  0 -1  0  0  0  1  0
> 12  0 -1  0  0  0  1  0
>
> Thank you for any replies,
>
> Matjaz
>
> P.S. I Use RGUI 2.1.1 on WindowsXP and limma package.
>
> --------------------------------------------------------------------------------
> Matjaz Hren
> National Institute of Biology
> Dept. of Plant Physiology and Biotechnology
> Vecna pot 111
> 1000 Ljubljana
> SLOVENIA
>
> www.nib.si
> phone: +386 1 423 33 88
> fax: +386 1 257 38 50
>
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