[BioC] lmFit simple design or contrast

[Björn Usadel]

Hi Beatriz,

your mail is very hard to read. If you have a look at section 8.4 again 
where supposedly a similar design as yours was used
"For the first approach, the treatment-contrasts parametrization, the 
design matrix should be
as follows:
 > design
WT MUvsWT
Array1 1 0
Array2 1 0
Array3 1 1
Array4 1 1
Array5 1 1
Here the first coefficient estimates the mean log-expression for wild 
type mice and plays the
role of an intercept."

And you plotted the first coefficient. However, you were probably more 
interest in coeffient2
if you do type
 >fita
and then have a look at the slots, you can see that in coeffiecients 
there is a column labeled MUvsWT which is probably what you wanted to see:
you can access it with fita$coeff[,2] or fita$coeff[,"MUvsWT"]

also str(objects) can be one of your friends....

Cheers,
björn


>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
>
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