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Only 60 CpGs revealed significant association upon adjustment for multiple testing (adjusted P < 0.05; Fig. 1b).
For drug screen data, probesets were selected for further analysis if the fold change was greater than 2 and multiple testing adjusted p-value using Benjamini and Hochberg procedure (BH-adjusted p-value) was less than 0.05 [37].
Multiple testing adjusted significant thresholds to the 5%-level were determined by Bonferroni-adjustment or by permutation test (50 000 permutations, to account for correlations between cognitive phenotypes).
Probes were selected for further analysis if the fold-induction was greater than 2 and multiple testing adjusted the p-value to less than 0.05 using Benjamini and Hochberg procedure (BH-adjusted p-value) [28].
This excess is not significant when corrected for multiple testing (adjusted P = 0.21).
In our examples, we use the commonly accepted multiple testing adjusted significance threshold of p < 5 × 10−8[ 15].
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The multiple testing adjusting method for P-values is the Benjamini and Hochberg algorithm.
These tests were not considered significant after applying Bonferroni corrections for multiple tests (adjusted significance level: α' = 0.009).
Additionally, we probed for canonical pathways enrichment using the Ingenuity Pathway Analysis (IPA) tools and calculated the multiple test adjusted P-value for each pathway according to the fit of user's data to IPA database.
The raw P-values (hypergeometric test) and the multiple test- adjusted P-values are listed for each pathway.
The Kruskal-Wallis test revealed statistically significant differences among groups (p = 0.029), also confirmed by a multiple test adjusting procedure based on the rank-means paired differences (p = 0.018) (Table 2). Figure 1 Cephalalgiaphobia and frequency of migraine.
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