[BioC] Time course experiment in Limma

[Cornell, John E]

Dear Bioconductor:

 

We have a affymetrix time course experiment with repeated measurements
taken at 0 minutes, 30 minutes and 240 minutes following infusion of
insulin.  There are 10 arrays for each time point.  We used gcrma to
pre-process and normalize our expression data.

We want to use Limma to analyze differential expression in this time
course experiment.  We have limma 1.8.22  that we run on a Windows XP
system.  We have tried to follow the example on page 36 of the limma
user's guide, but we seem to have difficulty executing some of the
procedures.  For example the contrastMatrix( ) procedure does not exist,
so we used the makeContrasts( ) procedure.  Here is the code we use to
set the problem:

 

design <- model.matrix(~0+factor(rep(c(1,2,3),10)))

colnames(design) <- c("ic.0","ic.30","ic.240")

 

fit <- lmFit(i.clamp.gcrma, design)

 

cont.ic <- makeContrasts(ic.30-ic.0, ic.240-ic.30, levels=design)

 

fit2 <- contrasts.fit(fit, cont.ic)

 

Everything seems to work well up to this point.  Now, we tried the
p.adjust() procedure:

 

selected.ic <- p.adjust(fit2$F.p.value,method="fdr") < 0.05

 

The F.p.value does not exist in fit2.  Since we really wish to use the
empirical Bayes modified t tests, we also applied the ebayes(). However,
when we request the table of top genes we get the following error:

 

> topTable(fit2.eb, coef="ic.30-ic.0", n=20, adjust="fdr")

Error in array(x, c(length(x), 1), if (!is.null(names(x)))
list(names(x),  : 

        attempt to set an attribute on NULL

 

 

We have tried several variations on the code without success.  Since I
consider myself a novice limma user, I assume that I am making some
simple error that I just cannot see.  Any help or advice is very
welcome.

 

John E. Cornell, Ph.D.

Center for Epidemiology and Biostatistics

University of Texas Health Science Center, San Antonio

 


	[[alternative HTML version deleted]]