Entering edit mode
3.9 years ago
doniaprof
•
0
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!
The approach will depend on what you're interested in. Define what is relevant to your use case. Also if by significance you mean statistical significance, remember that it doesn't automatically mean biological relevance.