[BioC] LIMMA and Clustering&In-Reply-To=

[Ron Ophir]

>Hi,
>I have a set of affymetrix data which includes three groups. I would
>like once to run supervised analysis by performing all three pairwise
>comarisons and once unsupersied by clustering samples. The question
is:
>Should I run the clustring on the normalized observed data (one that
>comaes out of RMA) or on coefficients after fitting in order that the
>input for the two type of analysis would be comparable?
>Having the following experimental design:
> A B C
>Array1 1 0 0
>Array2 1 0 0
>Array3 0 1 0
>Array4 0 1 0
>Array5 0 0 1
>Array6 0 0 1
>like in second design of chapter 13 "Two Groups: Affymetrix", is the
>coefficients after lmFit(data,design) are the same as the data
itself?

after running 
fit<-lmFit(data,design) 
fit$coefficients are actually the avrage values of (Array1,Array2)
(Array3,Array4) (Array5,Array6). Thus for each gene you'l get a vector
of size 3 which is exactly the averages of the groups you have been
described in the design matrix. Therefore, If you would like to cluster
the groups based on averages use fit$coeff matrix and if you want to
cluster  the sample based on the replicate values use the
exprs(AffyBatch) matrix.



>Thanks,
>Ron