So, I use voom/limma workflow to analyse my RNA-seq data. Now, I want to do further analysis, like measuring genes correlation and try some machine learning method (regression, random forest, etc.). My question is, is the output of voom step can be used for this kind of analysis? The voom step I mean is like below:
vRnaSeq <- voom(dgeList,designVoom,plot=TRUE)
exprs <- vRnaSeq$E
From the code above, what I understand is the exprs variable is a matrix of genes x sample for the log of gene expression. Is this data good for further analysis or I need to use raw read count? What kind of analysis is good and not good to be applied for this data? Maybe you can give some criteria for analysis type which good and not good based on log of gene expression data. Also, if you know some papers about machine learning analysis for gene expression data, maybe you can tell me which to read. Thank you.