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Table 3 Uni-variate Cox proportional hazards analysis results for right Markov clustering modules

From: A network module-based method for identifying cancer prognostic signatures

   Nejm GSE4922 GSE3143 GSE18229 GSE1456
Module Size Hazard ratio P-value Hazard ratio P-value Hazard ratio P-value Hazard ratio P-value Hazard ratio P-value
2 31 1.30E+00 1.75E-10 1.84E+00 5.84E-05 1.55E+01 6.70E-06 1.12E+00 1.64E-04 2.46E+00 8.76E-05
18 9 9.44E-01 3.99E-09 1.35E+00 1.86E-04 2.61E+00 1.42E-01 7.23E-01 2.59E-03 2.19E+00 1.10E-04
4 17 1.14E+00 1.35E-08 2.46E+00 2.95E-04 2.18E-01 9.23E-01 1.08E+00 3.81E-03 3.38E+00 8.42E-04
13 11 1.02E+00 7.49E-07 1.84E+00 2.02E-04 6.20E-01 3.28E-01 8.66E-01 3.31E-04 2.51E+00 2.37E-04
21 8 1.75E+00 5.21E-05 2.08E+00 6.61E-02 -2.14E+00 2.48E-01 1.31E+00 3.44E-02 3.06E+00 2.93E-02
12 11 -6.59E-01 3.59E-04 -7.18E-01 3.40E-01 3.07E+00 8.43E-02 -8.81E-01 1.26E-02 -3.32E+00 1.55E-02
29 8 7.90E-01 9.21E-04 1.80E+00 5.03E-02 -1.08E-01 4.89E-01 1.25E+00 2.41E-03 3.84E+00 2.58E-03
1 70 -6.68E-01 2.05E-03 2.96E+00 2.95E-02 -1.41E-01 2.62E-01 -1.75E-01 6.38E-01 -2.04E+00 2.76E-01
  1. The eight MCL modules were selected by the trained superpc model when the Nejm data set was used as the training data set. Modules are sorted based on P-values. The sole module that is significant across five breast cancer data sets is in bold.