Skip to main content

Table 7 Calculated p-values for Wilcoxon signed rank sum tests (GDT)

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

 

0.14

3.59E-02

5.99E-03

1.09E-03

9.83E-06

3.88E-06

4.69E-08

1.37E-11

ProQ-MX

0.87

 

4.77E-02

7.52E-03

3.85E-05

3.58E-07

7.98E-07

3.24E-08

3.38E-12

ProQ-LG

0.96

0.95

 

0.07

3.48E-03

1.05E-04

2.99E-07

6.41E-08

2.06E-13

ProQ*

0.99

0.99

0.93

 

0.14

1.03E-02

3.40E-05

8.83E-06

2.91E-09

ModSSEA

1.00

1.00

1.00

0.86

 

0.06

5.80E-03

2.53E-03

7.13E-08

ModFOLD

1.00

1.00

1.00

0.99

0.94

 

4.64E-02

0.06

2.90E-06

Pcons*†

1.00

1.00

1.00

1.00

0.99

0.95

 

0.43

1.47E-03

LEE*†

1.00

1.00

1.00

1.00

1.00

0.94

0.57

 

1.01E-03

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 GDT 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.