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Table 5 Determining the contribution of gene weighting and moderated t-scores in PADOG when analyzing 229 KEGG metabolic and non-metabolic pathways

From: Down-weighting overlapping genes improves gene set analysis

  noM noW PADOG noMnoW
p geomean 0.0480 0.1330 0.0486 0.1225
p med 0.092 0.1695 0.091 0.1595
% p.value<0.05 33.3 16.7 33.3 16.7
% q.value<0.05 8.3 0 4.2 0
rank mean 20.52 22.33 18.95 22.48
rank med 14.38 15.71 13.05 16.81
p Wilcox. 0.0260 0.371 0.002 reference
p LME 0.0463 0.314 0.0030 reference
coef. LME -1.96 -0.15 -3.53 reference
  1. The table shows statistics computed from nominal and adjusted p-values, and ranks of the 24 target pathways only, including geometric mean, median and percentages of pathways significant at 0.05 level based on nominal and adjusted p-values (q-values). The results of comparing the ranks of each method against noMnoW method, using a paired Wilcoxon test and a linear mixed-effects model, are included. The best value for each criterion is shown in bold. PADOG is compared against simpler approaches that i) use gene weights but regular rather than moderated t-scores (noM), ii) use moderated t-scores but no gene weights (noW) and iii) use neither moderated t-scores nor gene weights (noMnoW).