This has been called the multiple testing problem or the problem of multiplicity [ 8].
Due to the high number of tested hypotheses (number of molecular features, 5,891), the multiple testing problem was addressed.
To control for the multiple testing problem we performed a false discovery rate correction [41].
The foreseen expansion of the multiple testing problem merits appropriate attention.
In addition, analyzing multiple phenotypes jointly can also alleviate multiple testing problem caused by testing different traits separately.
Such an approach is not applicable to deal with the discovery of multiple causal variants, since we then have to consider the impact of multiple testing problem.
To address the multiple testing problem, we selected SNPs considering a 25% level for the FDR which is the expected proportion of false discoveries among all discoveries[12].
The multiple testing problem does not apply to the strong genetic interaction we found between SNPs in TLR4, TOLLIP, and IRAK1.
Furthermore, carrying out numerous subgroup comparisons leads to the multiple testing problem.
The multiple testing problem was considered using the two different Bonferroni corrections.
Because of the multiple testing problem, the P-values of all nodes have to be adjusted.
