How to choose a gene selection approach?
Hello guys,
I want to conduct an analysis to select the most relevant or significant genes from multi omics datasets says gene expression , DNA methylation , copy number variation and mutation data. these data contain a list of genes and samples .
Which approach i have to better choose , DEG or machine learning algorithms or rCNA( recurrent copy number alterations) algorithms with annotation or any others? Are all these approaches have good peformance?
Please suggest me to better understand these things.
I highly appreciate any help!
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doniaprof •
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I don't think there's anyway to answer this question as written. It's much too vague - the "best" approach will depend on things you haven't mentioned - what is the experiment? What is the system? What are the questions you are trying to answer? And what does rCNA stand for? (I doubt it's the Royal College of Nursing in Australia).
@seidel Ok Thank you i wil update the queston and make it clear. rCNA means recurrent copy number alteration , sorry for that
@seidel, i have provide the details is it ok now? appreciate your help and suggestion