Oh! sorry about the email, it displayed correctly when I sent it to you Maybe I need to know more about statistic and linear models, but thank you Bj?rn Usadel wrote: > 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, > bj?rn > > >> 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 >> >> > >