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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).