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**                                                                                          **
**                                         SNPs&GO                                          **
**                  Predicting disease associated variation using GO terms                  **
**                                                                                          **
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      Sequence File: IL23R_HUMAN.seq

      Mutation     Prediction   RI  Probability   Method
          W35C        Disease    2        0.599   PhD-SNP:  F[W]=43%  F[C]=0%   Nali=27
          W35C   Unclassified   NA           NA   PANTHER:  F[W]=NA   F[C]=NA
          W35C        Neutral    5        0.230   SNPs&GO

          S49Y        Disease    0        0.502   PhD-SNP:  F[S]=47%  F[Y]=0%   Nali=35
          S49Y   Unclassified   NA           NA   PANTHER:  F[S]=NA   F[Y]=NA
          S49Y        Neutral    7        0.173   SNPs&GO

          C52F        Disease    7        0.864   PhD-SNP:  F[C]=100% F[F]=0%   Nali=35
          C52F   Unclassified   NA           NA   PANTHER:  F[C]=NA   F[F]=NA
          C52F        Disease    2        0.613   SNPs&GO

          C59R        Disease    5        0.764   PhD-SNP:  F[C]=67%  F[R]=6%   Nali=35
          C59R   Unclassified   NA           NA   PANTHER:  F[C]=NA   F[R]=NA
          C59R        Neutral    1        0.444   SNPs&GO

          L64P        Disease    4        0.701   PhD-SNP:  F[L]=53%  F[P]=0%   Nali=33
          L64P   Unclassified   NA           NA   PANTHER:  F[L]=NA   F[P]=NA
          L64P        Neutral    4        0.313   SNPs&GO

         P220S        Disease    4        0.685   PhD-SNP:  F[P]=93%  F[S]=0%   Nali=43
         P220S        Neutral    3        0.360   PANTHER:  F[P]=62%  F[S]=3%  
         P220S        Neutral    2        0.398   SNPs&GO

         P220T        Disease    3        0.632   PhD-SNP:  F[P]=93%  F[T]=0%   Nali=43
         P220T        Neutral    2        0.421   PANTHER:  F[P]=62%  F[T]=2%  
         P220T        Neutral    3        0.337   SNPs&GO

         W242C        Disease    5        0.760   PhD-SNP:  F[W]=88%  F[C]=0%   Nali=39
         W242C        Disease    5        0.727   PANTHER:  F[W]=61%  F[C]=0%  
         W242C        Disease    3        0.647   SNPs&GO

         C253R        Disease    0        0.516   PhD-SNP:  F[C]=49%  F[R]=0%   Nali=42
         C253R        Disease    1        0.539   PANTHER:  F[C]=58%  F[R]=1%  
         C253R        Neutral    2        0.392   SNPs&GO

         L284W        Disease    5        0.739   PhD-SNP:  F[L]=100% F[W]=0%   Nali=44
         L284W        Disease    6        0.808   PANTHER:  F[L]=60%  F[W]=0%  
         L284W        Disease    0        0.515   SNPs&GO

         C296R        Disease    8        0.881   PhD-SNP:  F[C]=73%  F[R]=0%   Nali=44
         C296R        Disease    3        0.673   PANTHER:  F[C]=66%  F[R]=1%  
         C296R        Disease    6        0.814   SNPs&GO

         W307G        Disease    5        0.770   PhD-SNP:  F[W]=100% F[G]=0%   Nali=43
         W307G        Disease    3        0.637   PANTHER:  F[W]=69%  F[G]=1%  
         W307G        Disease    3        0.654   SNPs&GO

         W395R        Disease    6        0.818   PhD-SNP:  F[W]=100% F[R]=0%   Nali=16
         W395R        Disease    3        0.663   PANTHER:  F[W]=69%  F[R]=1%  
         W395R        Disease    4        0.700   SNPs&GO

         P401S        Disease    3        0.656   PhD-SNP:  F[P]=100% F[S]=0%   Nali=16
         P401S        Neutral    0        0.495   PANTHER:  F[P]=71%  F[S]=2%  
         P401S        Disease    1        0.563   SNPs&GO


      Mutation: WT+POS+NEW
      WT:  Residue in wild-type protein
      POS: Residue position
      NEW: New residue after mutation
      Prediction:
             Neutral: Neutral variation
             Disease: Disease associated variation
      RI: Reliability Index
      Probability: Disease probability (if >0.5 mutation is predicted Disease)
      Method: SVM type and data
             PANTHER: Output of the PANTHER algorithm
             PhD-SNP:  SVM input is the sequence and profile at the mutated position
             SNPs&GO:  SVM input is all the input in PhD-SNP, PANTHER  and GO term features
      F[X]: Frequency of residue X in the sequence profile
      Nali: Number of aligned sequences in the mutated site

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**                                                                                          **
**     Calabrese R, Capriotti E, Fariselli P, Martelli PL, Casadio R. (2009). Functional    **
**     annotations improve the predictive score of human disease-related mutations in       **
**     proteins. Human Mutation. 30:1237-1244.                                              **
**                                                                                          **
**     Capriotti E, Altman RB. (2011). Improving the prediction of disease-related vari-    **
**     ants using protein three-dimensional structure. BMC Bioinformatics. 12 (Sup.4) S3.   **
**                                                                                          **
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