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Introduction
Results
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Methods
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Q2 |
P(D) |
Q(D) |
P(N) |
Q(N) |
MCC |
AUC |
|
M1 |
0. |
0. |
0. |
0. |
0. |
0. |
0. |
M2 |
0. |
0. |
0. |
0. |
0. |
0. |
0. |
M3 |
0. |
0. |
0. |
0. |
0. |
0. |
0. |
M4 |
0. |
0. |
0. |
0. |
0. |
0. |
0. |
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The overall accuracy Q2 is:
Q2=p/N
where p is the total number of correctly predicted residues and N is the total number of residues.
The correlation coefficient MCC is defined as:
C(s)=[p(s)n(s)-u(s)o(s)] / W
where W is the normalization factor
W=[(p(s)+u(s))(p(s)+o(s))(n(s)+u(s))(n(s)+o(s))]1/2
for each class s (D and N, for disease-related and neutral polymorphism, respectively); p(s) and n(s) are the total number of correct predictions and correctly rejected assignments, respectively, and u(s) and o(s) are the numbers of under and over predictions.
The coverage for each discriminated structure s is evaluated as:
Q(s)=p(s)/[p(s)+u(s)]
where p(s) and u(s) are as defined above. The probability of correct predictions P(s) (or accuracy for s) is computed as:
P(s)=p(s) / [p(s) + o(s)]
where p(s) and o(s) are defined above (ranging from 1 to 0).
References
[1]
[2]
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