However, this situation raises possible multiplicity issues, i.e. if both OS and PFS were to be tested in parallel, hence family-wise error rate adjustment to protect against type I error for multiple tests was carried out.
Genes with high variability within samples were selected by pair-wise comparison analyses performed by adjusting the type-I error for multiple tests (Step-down permutation (SDP) [ 10], and False Discovery Rate (FDR) [ 11]), and with no type-I error adjustment (Raw method).
In general, no error adjustment for multiple testing was conducted.
The scores were adjusted using the standard Bonferroni error correction for multiple testing.
The statistical advantage of permutation tests is the tighter control for type-I error, especially for multiple testing of correlated variables.
Only in cases in which analyses were based on a priori hypotheses derived from literature (e.g., [ 10, 41]), results are presented without correction of error probabilities for multiple testing (see also [ 41]).
And then we applied family-wise error (FWE) correction for multiple testing to avoid type I errors at the whole brain level.
