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**                                                                                          **
**                                         SNPs&GO                                          **
**                  Predicting disease associated variation using GO terms                  **
**                                                                                          **
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WARNING: Incorrect mutation E355*
WARNING: Incorrect mutation Q276*
WARNING: Incorrect mutation R572*

      Sequence File: SP.seq

      Mutation     Prediction   RI  Probability   Method
         T240I        Disease    1        0.570   PhD-SNP:  F[T]=54%  F[I]=0%   Nali=36
         T240I        Neutral    3        0.359   PANTHER:  F[T]=36%  F[I]=2%  
         T240I        Neutral    6        0.215   SNPs&GO

         A452T        Neutral    8        0.108   PhD-SNP:  F[A]=50%  F[T]=3%   Nali=29
         A452T        Neutral    7        0.153   PANTHER:  F[A]=24%  F[T]=5%  
         A452T        Neutral   10        0.020   SNPs&GO

         E500A        Neutral    5        0.272   PhD-SNP:  F[E]=50%  F[A]=0%   Nali=39
         E500A        Neutral    3        0.334   PANTHER:  F[E]=52%  F[A]=3%  
         E500A        Neutral    8        0.079   SNPs&GO

         G523S        Neutral    5        0.269   PhD-SNP:  F[G]=63%  F[S]=12%  Nali=40
         G523S        Disease    4        0.695   PANTHER:  F[G]=83%  F[S]=2%  
         G523S        Neutral    5        0.264   SNPs&GO

         C542W        Disease    9        0.938   PhD-SNP:  F[C]=76%  F[W]=0%   Nali=40
         C542W        Disease    7        0.830   PANTHER:  F[C]=61%  F[W]=0%  
         C542W        Disease    6        0.819   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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