[BioC] lmFit simple design or contrast
Björn Usadel
usadel at mpimp-golm.mpg.de
Fri Nov 18 18:08:57 CET 2005
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
>
>_______________________________________________
>Bioconductor mailing list
>Bioconductor at stat.math.ethz.ch
>https://stat.ethz.ch/mailman/listinfo/bioconductor
>
>
More information about the Bioconductor
mailing list