[BioC] Limma and Block Effects

[Pie Muller]

Hi Bioconductors

I followed the example 10.2 in Limma's user guide which includes a 
coefficient for each mouse in the linear model to account for technical 
replication. I am somewhat puzzled because the example in the user's guide 
returns non-estimable coefficients and hence the contrast (mu1+mu2-wt2)/2 
as proposed in the guide cannot be computed... (I assume the function 
"designMatrix()" can be replaced by "modelMatrix()".) Since the given 
example returns an error, and I am not a statistician, I am struggling in 
finding the correct solution. As we have four  replicate spots on our 
arrays I cannot use the "duplicateCorrelation()" function here. How does 
the correct design matrix look like and which contrasts need to be computed?

Has anyone a solution either for the example given in the user guide or my 
own experiment listed below?

MANY THANKS!
Pie


I have 3 biological replicates and two technical replicates for each 
biological replicate, i.e.,

FileName Cy3 Cy5
File1    A1  B1
File2    B1  A1
File3    A2  B2
File4    B2  A2
File5    A3  B3
File6    B3  A3

and would like to estimate the effect between A and B including a 
coefficient to fit a separate effect for each individual.