I have data for gene mutations (binary values) and gene expression level (continuous values) for several patients. (Theseare shown in two tables in the first row of the pic.)
To decide whether a gene mutation truly affects function.
I need to combine it with its expression level.
So I divided people into two groups based on gene mutation.
Then do a test on their gene expression levels.
This test result in a P-value.
My question is, what is the right way to convert P-values to q-values in this case, in
Should I pool all P-values across groups or within a group together to calculate individual q-values?
It is actually the method used in 'Emerging landscape of oncogenic signatures across human cancers', which I intend to imitate.
see Method-Testing for concordant mRNA and copy number changes.