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Table 5 Calculated p-values for Wilcoxon signed rank sum tests (TM-score)

From: Benchmarking consensus model quality assessment for protein fold recognition

  Method x
Method y MODCHECK ProQ-MX ProQ-LG ProQ* ModSSEA ModFOLD Pcons*† LEE*† 3D-Jury†
MODCHECK   0.33 0.10 9.21E-03 9.25E-04 6.54E-05 2.85E-05 3.80E-08 1.89E-12
ProQ-MX 0.67   4.04E-02 3.34E-03 1.49E-06 1.14E-07 1.83E-07 3.49E-09 1.42E-12
ProQ-LG 0.91 0.96   2.35E-02 5.82E-05 1.54E-05 2.51E-07 5.88E-09 4.31E-13
ProQ* 0.99 1.00 0.98   4.29E-02 1.15E-02 3.43E-05 2.67E-06 8.17E-11
ModSSEA 1.00 1.00 1.00 0.96   0.26 2.53E-02 5.08E-03 1.32E-07
ModFOLD 1.00 1.00 1.00 0.99 0.75   0.05 2.76E-02 3.15E-07
Pcons*† 1.00 1.00 1.00 1.00 0.98 0.95   0.38 1.07E-04
LEE*† 1.00 1.00 1.00 1.00 1.00 0.97 0.63   5.02E-05
3D-Jury† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00  
  1. The different MQAP methods are compared in terms of the observed model quality of the top ranked models for each target. H0 = m x ≤ m y , H1 = m x > m y , where H0 is the null hypothesis; H1 is the alternative hypothesis; m x is the observed model quality of models selected by Method x and m y is the observed model quality of models selected by Method y according to the TM-score. * The MQAP scores for these methods were downloaded from CASP7 website; all other MQAP methods were run in house during the CASP7 experiment. † MQAP methods which rely on the comparison of multiple models or additional information from multiple servers; all other methods are capable of producing a single score based on a single model.
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BMC Bioinformatics

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