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Table 3 Results of simulation S4

From: NEAT: an efficient network enrichment analysis test

Test p KS R 1 R 5 Sensitivity Specificity AUC
NEAT 0.399 1.33 1.14 69 % 94 % 0.920
NEA 0.001 0 0.87 68 % 96 % 0.918
LP 0 2.13 1.51 68 % 92 % 0.908
LA 0.255 1.60 1.17 60 % 94 % 0.897
LA+S 0.409 1.87 1.17 63 % 94 % 0.913
NP 0.037 1.24 1.28 58 % 94 % 0.884
  1. The best results for each indicator are in bold. p KS denotes the p-value of the Kolmogorov-Smirnov test for uniform distribution, AUC is an abbreviation for “area under the ROC curve”. The distribution of p-values under H 0 is evidently not uniform for NEA and LP. NEAT shows the highest values of sensitivity and AUC, and its specificity is close to the target value (95 %)