[BioC] limma and blocks

[Thibaud-Nissen, Francoise]

Hi,

 

I am analyzing an experiment using 32 Arabidopsis Affymetrix chips. It is basically a 2x2x4 design repeated twice using different biological replicates (the third replicate will be provided later). The plants within each biological replicate were grown at the same time, and in that sense are related and form a block. There are no technical replicates within each block. 

 

I am using limma. In the model I calculate separate coefficients for each of the 16 conditions. I then use contrasts matrices to evaluate contrasts of interest.

 

I now would like to incorporate the block effect in my model in order to account for random variation in the growth conditions between the two biological replicates.

 

I tried two models that give different results, but I am not sure any of them is correct:

 

If the first biological replicate appears first in my design, and "design" is my design matrix for the 16 coefficients:

 

Model 1:

biorep <- c(rep(1,16),rep(2,16))

fit <- lmFit(mydata, design, block= biorep)

fit <- eBayes(fit)

...

 

Model 2:

blockdiff <- c(rep(1,16),rep(-1,16)) 

blockdesign <- cbind(design, Block=blockdiff)

fitblock <-lmFit(mydata, blockdesign)

fitblock <- eBayes(fitblock)

...

 

I would appreciate any tip that could put me in the right track!

 

Thanks,

 

Françoise

 

 

 


	[[alternative HTML version deleted]]