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**                                                                                          **
**                                         SNPs&GO                                          **
**                  Predicting disease associated variation using GO terms                  **
**                                                                                          **
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      Sequence File: FA5_HUMAN.seq

      Mutation     Prediction   RI  Probability   Method
         D107H        Neutral    4        0.323   PhD-SNP:  F[D]=12%  F[H]=1%   Nali=300
         D107H        Neutral    5        0.240   PANTHER:  F[D]=28%  F[H]=5%  
         D107H        Neutral    4        0.312   SNPs&GO

         I387T        Disease    7        0.852   PhD-SNP:  F[I]=72%  F[T]=2%   Nali=253
         I387T        Neutral    4        0.296   PANTHER:  F[I]=25%  F[T]=3%  
         I387T        Disease    7        0.835   SNPs&GO

         C613R        Disease    3        0.658   PhD-SNP:  F[C]=5%   F[R]=0%   Nali=266
         C613R        Disease    0        0.510   PANTHER:  F[C]=32%  F[R]=1%  
         C613R        Disease    8        0.895   SNPs&GO

         K858R        Neutral    8        0.119   PhD-SNP:  F[K]=40%  F[R]=27%  Nali=14
         K858R   Unclassified   NA           NA   PANTHER:  F[K]=NA   F[R]=NA
         K858R        Neutral    9        0.068   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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