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**                                                                                          **
**                                         SNPs&GO                                          **
**                  Predicting disease associated variation using GO terms                  **
**                                                                                          **
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      Sequence File: C1TM_HUMAN.seq

      Mutation     Prediction   RI  Probability   Method
         G466E        Disease    8        0.877   PhD-SNP:  F[G]=96%  F[E]=0%   Nali=559
         G466E        Disease    7        0.825   PANTHER:  F[G]=73%  F[E]=1%  
         G466E        Disease    9        0.936   SNPs&GO

         Y519C        Disease    7        0.850   PhD-SNP:  F[Y]=64%  F[C]=0%   Nali=183
         Y519C   Unclassified   NA           NA   PANTHER:  F[Y]=NA   F[C]=NA
         Y519C        Disease    3        0.670   SNPs&GO

         T572M        Neutral    2        0.408   PhD-SNP:  F[T]=40%  F[M]=2%   Nali=788
         T572M        Neutral    0        0.498   PANTHER:  F[T]=24%  F[M]=2%  
         T572M        Neutral    2        0.380   SNPs&GO

         V702I        Neutral    2        0.417   PhD-SNP:  F[V]=16%  F[I]=1%   Nali=517
         V702I        Neutral    4        0.321   PANTHER:  F[V]=44%  F[I]=8%  
         V702I        Neutral    1        0.431   SNPs&GO

         T757K        Neutral    6        0.196   PhD-SNP:  F[T]=25%  F[K]=22%  Nali=266
         T757K   Unclassified   NA           NA   PANTHER:  F[T]=NA   F[K]=NA
         T757K        Neutral    8        0.098   SNPs&GO

         L762P        Disease    6        0.822   PhD-SNP:  F[L]=51%  F[P]=0%   Nali=427
         L762P   Unclassified   NA           NA   PANTHER:  F[L]=NA   F[P]=NA
         L762P        Disease    2        0.607   SNPs&GO

         D805N        Disease    8        0.875   PhD-SNP:  F[D]=100% F[N]=0%   Nali=761
         D805N        Disease    7        0.830   PANTHER:  F[D]=85%  F[N]=1%  
         D805N        Disease    7        0.873   SNPs&GO

         A873V        Disease    3        0.673   PhD-SNP:  F[A]=73%  F[V]=14%  Nali=760
         A873V        Neutral    3        0.356   PANTHER:  F[A]=56%  F[V]=10% 
         A873V        Disease    2        0.623   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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