Question: Latest Regression techniques for Microarray data
gravatar for sjorsvanheuveln
4.5 years ago by
sjorsvanheuveln50 wrote:

I'm currently studying which models would best work in predicting age (continuous variable) from DNA-methylation microarrays. As, nowadays there are many extensions/variations becoming available based on (penalized) regression techniques, I was wondering which techniques are now out there that can be used. I've extensively looked for proper articles online, but I can't seem to find a good review of the latest techniques for applying regression to microarray data.

So if you know or if you are currently using a technique you favor, please post it here, so I can help create an overview of the contemporary methods. Thanks a lot.

P.S.: I know this topic resembles this post a lot Microarray Class Prediction - For Continuous Data? , but in this post only the obvious techniques are being mentioned and I try to do a deeper inquiry on the latest variations/extensions of the main regression techniques.

ADD COMMENTlink written 4.5 years ago by sjorsvanheuveln50

How about random survival forests?

ADD REPLYlink written 4.5 years ago by russhh5.5k

Yeah nice idea. Seems to be an interesting candidate. And it has also got an R-package, so that's awesome too.

ADD REPLYlink written 4.5 years ago by sjorsvanheuveln50

Actually, isn't a random survival forest only just suited for predicting time of survival of a population. Can it be transferred to age prediction, which seems to be something else?

ADD REPLYlink written 4.5 years ago by sjorsvanheuveln50
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