I'm reading through some papers that use PAM to create a classifier from
microarray data.
I would like to use these classifiers to classify my own samples with
microarray data.
These papers publish the output of 'pamr.listgenes()', and it's not clear
how to massage
that into a format that 'pamr.predict()' will accept.

The first argument to 'pamr.predict()' is "the result of a call to
pamr.train".  'pamr.train()'
operates on normalized microarray data and a vector of class labels.
Essentially, I'd
have to repeat the entire analysis, downloading every CEL file and
normalizing it,
in order to run 'pamr.train()' so I can run 'pamr.predict'.

That doesn't seem like the right way to do things, but I can't find any
other function
that would create the "pamrtrained" object that 'pamr.predict()' requires.
What's the
right way to do what I want to do here?

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