Hi, everybody

I've read "limma: Linear Models for Microarray Data User's Guide" 
several times and I can't understood when you should use a simple design 
or a contrast matrix.

I have done my own experiments with the explanation of page 31 ("Two 
Groups: Affymetrix") and I can do it and obtain results but I don't 
understand why.

> My experiment is
>
> FileName
>
> 	
>
> Array
>
> 	
>
> Target
>
> File1
>
> 	
>
> 1
>
> 	
>
> Mu
>
> File2
>
> 	
>
> 1
>
> 	
>
> WT
>
> File3
>
> 	
>
> 2
>
> 	
>
> Mu
>
> File4
>
> 	
>
> 2
>
> 	
>
> WT
>
> File5
>
> 	
>
> 3
>
> 	
>
> Mu
>
> File6
>
> 	
>
> 4
>
> 	
>
> WT
>
>
> I have 2 questions:
>
> 1) When I design the design matrix with the instructions of this 
> user's guide, I obtain
>      WT MUvsWT
> [1,]  1   1
> [2,]  1   0
> [3,]  1   1
> [4,]  1   0
> [5,]  1   1
> [6,]  1   0 
>
> but I don't understand why you write 1s and 0s (I know column WT is 
> logIntensity and MUvsWT logRatio, but  I don't understand why you put 
> this number)
> do you consider that your WT intensity is always 10' (log10=1)?
> and MUvsWT is 10 or 1 (log10=1, log1=0)?
>
>
> 2) When I use a simple design and plot the results with plotMA(fita), 
> I can see a plot with M label in the Y-axe and A label in the X-axe 
> but the graphical representation is very similar to Intensity vs 
> Intensity plot (M are the log2ratio and A the average of control and 
> experiment intensity values)
>
>     --------------------------------------------------------------------------
>
>> design <- cbind(WT=1, MUvsWT=c(1,0,1,0,1,0))
>> design
>
>              WT MUvsWT
>         [1,]  1   1
>         [2,]  1   0
>         [3,]  1   1
>         [4,]  1   0
>         [5,]  1   1
>         [6,]  1   0
>
>> fita <- lmFit(eSet,design)
>> fita <- eBayes(fita)
>      
>     --------------------------------------------------------------------------
>
>
> When I use a contrast matrix and plot the results with plotMA(fit2), I 
> can see a plot with M label in the Y-axe and A label in the X-axe and 
> the graphical representation is a real MA plot
>
>     --------------------------------------------------------------------------
>
>> design2 <- cbind(MU=c(1,0,1,0,1,0),WT=c(0,1,0,1,0,1))
>> design2
>
>              MU WT
>         [1,]  1  0
>         [2,]  0  1
>         [3,]  1  0
>         [4,]  0  1
>         [5,]  1  0
>         [6,]  0  1
>
>> fit <- lmFit(eSet,design2)
>> contraste <- makeContrasts(MUvsWT=MU-WT, levels=design2)
>> contraste
>
>            MUvsWT
>         MU      1
>         WT     -1
>
>> fit2 <- contrasts.fit(fit,contraste)
>> fit2 <- eBayes(fit2)
>     --------------------------------------------------------------------------
>
>
> why you obtain diferent plots? is because of the design matrix?
>
> Thanks a lot for your help
>
> Beatriz
>

	[[alternative HTML version deleted]]

