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

      Mutation     Prediction   RI  Probability   Method
         P216S        Neutral    2        0.378   PhD-SNP:  F[P]=82%  F[S]=0%   Nali=10
         P216S   Unclassified   NA           NA   PANTHER:  F[P]=NA   F[S]=NA
         P216S        Neutral    8        0.109   SNPs&GO

         S228A        Neutral    9        0.039   PhD-SNP:  F[S]=70%  F[A]=10%  Nali=9
         S228A   Unclassified   NA           NA   PANTHER:  F[S]=NA   F[A]=NA
         S228A        Neutral   10        0.009   SNPs&GO

         S231P        Neutral    9        0.055   PhD-SNP:  F[S]=67%  F[P]=22%  Nali=8
         S231P   Unclassified   NA           NA   PANTHER:  F[S]=NA   F[P]=NA
         S231P        Neutral   10        0.013   SNPs&GO

         T525S        Neutral    5        0.229   PhD-SNP:  F[T]=75%  F[S]=0%   Nali=7
         T525S   Unclassified   NA           NA   PANTHER:  F[T]=NA   F[S]=NA
         T525S        Neutral    9        0.060   SNPs&GO

         A533V        Neutral    7        0.151   PhD-SNP:  F[A]=38%  F[V]=0%   Nali=7
         A533V   Unclassified   NA           NA   PANTHER:  F[A]=NA   F[V]=NA
         A533V        Neutral    9        0.034   SNPs&GO

         P535A        Neutral    9        0.068   PhD-SNP:  F[P]=86%  F[A]=0%   Nali=6
         P535A   Unclassified   NA           NA   PANTHER:  F[P]=NA   F[A]=NA
         P535A        Neutral   10        0.011   SNPs&GO

         E711K        Neutral    1        0.436   PhD-SNP:  F[E]=53%  F[K]=2%   Nali=88
         E711K        Neutral    5        0.235   PANTHER:  F[E]=32%  F[K]=4%  
         E711K        Neutral    5        0.233   SNPs&GO

         Q714K        Neutral    6        0.178   PhD-SNP:  F[Q]=20%  F[K]=2%   Nali=124
         Q714K        Neutral    8        0.083   PANTHER:  F[Q]=12%  F[K]=7%  
         Q714K        Neutral    9        0.038   SNPs&GO

         E716Q        Neutral    8        0.095   PhD-SNP:  F[E]=36%  F[Q]=5%   Nali=141
         E716Q        Neutral    7        0.133   PANTHER:  F[E]=16%  F[Q]=5%  
         E716Q        Neutral   10        0.022   SNPs&GO

         Q977R        Neutral    3        0.352   PhD-SNP:  F[Q]=22%  F[R]=6%   Nali=893
         Q977R   Unclassified   NA           NA   PANTHER:  F[Q]=NA   F[R]=NA
         Q977R        Neutral    6        0.215   SNPs&GO

        G1271R        Neutral    9        0.066   PhD-SNP:  F[G]=60%  F[R]=20%  Nali=9
        G1271R   Unclassified   NA           NA   PANTHER:  F[G]=NA   F[R]=NA
        G1271R        Neutral   10        0.011   SNPs&GO

        P1277S        Neutral    6        0.184   PhD-SNP:  F[P]=78%  F[S]=0%   Nali=8
        P1277S   Unclassified   NA           NA   PANTHER:  F[P]=NA   F[S]=NA
        P1277S        Neutral   10        0.023   SNPs&GO

        L1281R        Neutral    3        0.351   PhD-SNP:  F[L]=90%  F[R]=0%   Nali=9
        L1281R   Unclassified   NA           NA   PANTHER:  F[L]=NA   F[R]=NA
        L1281R        Neutral    9        0.047   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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