Have you tried reading some of the material from the BioConductor
workshop http://bioconductor.org/workshops/ ?
Here is a simplistic way of proceeding:
## Calculate pvalues from t-test
p <- apply( mat, function(x) t.test( x ~ cl )$p.value )
## Subset
mat.sub <- mat[ p, ]
## Cluster
heatmap(m)
Regards, Adai
Abhilash Venu wrote:
Hi all,
I am working on a single color expression data using limma. I would like to
perform a cluster analysis after selecting the differentially genes based on
the P value (say 0.001). As far as my knowledge is concerned I have to do
the sub setting of these selected genes on the normalized data (MA), to
retrieve the distribution across the samples.
But I am wondering whether I can perform using the R script?
I would appreciate any help.
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