[BioC] classification method applied to microarrays (CMA package)

[Juan Carlos Oliveros Collazos]

Dear all,

I am starting using the CMA package for classification of microarray 
samples.

In particular, I want to know which genes are the main responsible for 
separating about 60 lists of expression values into 2 groups that are 
already known. I understand that SVM is a good method to find the 
hyperplane that best separate the two groups but what I need are the 
genes, not the hyperplane parameters.

My questions are:

To get a list of genes, should I use in some manner SVMs (or another 
classification method) or what I need is simply to identify the 
"informative" genes by using GeneSelection function of CMA package?

If so, the learning sets are needed? why?

Any recomendation for choosing a gene selection method?

Thanks in advance.

best,

Juan Carlos Oliveros
CNB-CSIC, Madrid, Spain