********************************************************************************************** ** ** ** SNPs&GO ** ** Predicting disease associated variation using GO terms ** ** ** ********************************************************************************************** Sequence File: SP.seq Mutation Prediction RI Probability Method G14W Neutral 1 0.451 PhD-SNP: F[G]=65% F[W]=0% Nali=19 G14W Unclassified NA NA PANTHER: F[G]=NA F[W]=NA G14W Neutral 8 0.095 SNPs&GO L41W Neutral 1 0.460 PhD-SNP: F[L]=78% F[W]=0% Nali=124 L41W Unclassified NA NA PANTHER: F[L]=NA F[W]=NA L41W Neutral 7 0.169 SNPs&GO N45H Neutral 8 0.101 PhD-SNP: F[N]=15% F[H]=0% Nali=129 N45H Unclassified NA NA PANTHER: F[N]=NA F[H]=NA N45H Neutral 9 0.030 SNPs&GO G64C Disease 5 0.744 PhD-SNP: F[G]=42% F[C]=0% Nali=145 G64C Unclassified NA NA PANTHER: F[G]=NA F[C]=NA G64C Neutral 2 0.382 SNPs&GO I69L Neutral 1 0.449 PhD-SNP: F[I]=47% F[L]=10% Nali=141 I69L Unclassified NA NA PANTHER: F[I]=NA F[L]=NA I69L Neutral 7 0.130 SNPs&GO E79V Neutral 2 0.412 PhD-SNP: F[E]=4% F[V]=0% Nali=50 E79V Unclassified NA NA PANTHER: F[E]=NA F[V]=NA E79V Neutral 6 0.188 SNPs&GO L99Q Disease 6 0.807 PhD-SNP: F[L]=58% F[Q]=0% Nali=188 L99Q Unclassified NA NA PANTHER: F[L]=NA F[Q]=NA L99Q Neutral 4 0.280 SNPs&GO Q156E Disease 2 0.618 PhD-SNP: F[Q]=16% F[E]=4% Nali=192 Q156E Unclassified NA NA PANTHER: F[Q]=NA F[E]=NA Q156E Neutral 2 0.387 SNPs&GO Y160C Disease 8 0.905 PhD-SNP: F[Y]=59% F[C]=0% Nali=191 Y160C Unclassified NA NA PANTHER: F[Y]=NA F[C]=NA Y160C Disease 2 0.584 SNPs&GO L162P Disease 7 0.867 PhD-SNP: F[L]=24% F[P]=0% Nali=192 L162P Unclassified NA NA PANTHER: F[L]=NA F[P]=NA L162P Disease 2 0.593 SNPs&GO T172M Disease 6 0.803 PhD-SNP: F[T]=76% F[M]=0% Nali=193 T172M Unclassified NA NA PANTHER: F[T]=NA F[M]=NA T172M Neutral 0 0.499 SNPs&GO S179L Neutral 1 0.474 PhD-SNP: F[S]=28% F[L]=2% Nali=194 S179L Unclassified NA NA PANTHER: F[S]=NA F[L]=NA S179L Neutral 7 0.166 SNPs&GO A180V Disease 3 0.644 PhD-SNP: F[A]=59% F[V]=0% Nali=194 A180V Unclassified NA NA PANTHER: F[A]=NA F[V]=NA A180V Neutral 5 0.257 SNPs&GO T187S Neutral 7 0.130 PhD-SNP: F[T]=19% F[S]=6% Nali=196 T187S Unclassified NA NA PANTHER: F[T]=NA F[S]=NA T187S Neutral 9 0.068 SNPs&GO M200V Neutral 1 0.469 PhD-SNP: F[M]=38% F[V]=2% Nali=179 M200V Unclassified NA NA PANTHER: F[M]=NA F[V]=NA M200V Neutral 6 0.224 SNPs&GO T201I Disease 0 0.513 PhD-SNP: F[T]=42% F[I]=5% Nali=170 T201I Unclassified NA NA PANTHER: F[T]=NA F[I]=NA T201I Neutral 5 0.232 SNPs&GO E203A Neutral 4 0.311 PhD-SNP: F[E]=34% F[A]=11% Nali=173 E203A Unclassified NA NA PANTHER: F[E]=NA F[A]=NA E203A Neutral 8 0.079 SNPs&GO V234I Neutral 8 0.112 PhD-SNP: F[V]=45% F[I]=7% Nali=111 V234I Unclassified NA NA PANTHER: F[V]=NA F[I]=NA V234I Neutral 9 0.027 SNPs&GO S236L Neutral 7 0.138 PhD-SNP: F[S]=28% F[L]=2% Nali=118 S236L Unclassified NA NA PANTHER: F[S]=NA F[L]=NA S236L Neutral 10 0.023 SNPs&GO T246I Neutral 8 0.090 PhD-SNP: F[T]=22% F[I]=5% Nali=115 T246I Unclassified NA NA PANTHER: F[T]=NA F[I]=NA T246I Neutral 9 0.035 SNPs&GO L256Q Disease 3 0.636 PhD-SNP: F[L]=40% F[Q]=2% Nali=171 L256Q Unclassified NA NA PANTHER: F[L]=NA F[Q]=NA L256Q Neutral 6 0.215 SNPs&GO Y284C Neutral 7 0.139 PhD-SNP: F[Y]=16% F[C]=2% Nali=172 Y284C Unclassified NA NA PANTHER: F[Y]=NA F[C]=NA Y284C Neutral 8 0.082 SNPs&GO Q287R Neutral 8 0.095 PhD-SNP: F[Q]=17% F[R]=5% Nali=186 Q287R Unclassified NA NA PANTHER: F[Q]=NA F[R]=NA Q287R Neutral 9 0.058 SNPs&GO S289C Neutral 6 0.205 PhD-SNP: F[S]=22% F[C]=1% Nali=181 S289C Unclassified NA NA PANTHER: F[S]=NA F[C]=NA S289C Neutral 8 0.093 SNPs&GO F295L Neutral 6 0.214 PhD-SNP: F[F]=31% F[L]=19% Nali=168 F295L Unclassified NA NA PANTHER: F[F]=NA F[L]=NA F295L Neutral 9 0.069 SNPs&GO L300M Neutral 6 0.191 PhD-SNP: F[L]=31% F[M]=10% Nali=177 L300M Unclassified NA NA PANTHER: F[L]=NA F[M]=NA L300M Neutral 9 0.064 SNPs&GO K309R Neutral 7 0.168 PhD-SNP: F[K]=23% F[R]=15% Nali=182 K309R Unclassified NA NA PANTHER: F[K]=NA F[R]=NA K309R Neutral 9 0.045 SNPs&GO A353T Neutral 0 0.491 PhD-SNP: F[A]=65% F[T]=4% Nali=180 A353T Unclassified NA NA PANTHER: F[A]=NA F[T]=NA A353T Neutral 8 0.100 SNPs&GO Q361R Neutral 1 0.468 PhD-SNP: F[Q]=30% F[R]=1% Nali=171 Q361R Unclassified NA NA PANTHER: F[Q]=NA F[R]=NA Q361R Neutral 6 0.187 SNPs&GO I385L Neutral 6 0.193 PhD-SNP: F[I]=39% F[L]=15% Nali=177 I385L Unclassified NA NA PANTHER: F[I]=NA F[L]=NA I385L Neutral 9 0.050 SNPs&GO V387M Neutral 7 0.127 PhD-SNP: F[V]=20% F[M]=2% Nali=174 V387M Unclassified NA NA PANTHER: F[V]=NA F[M]=NA V387M Neutral 9 0.050 SNPs&GO D424E Neutral 1 0.463 PhD-SNP: F[D]=82% F[E]=16% Nali=178 D424E Unclassified NA NA PANTHER: F[D]=NA F[E]=NA D424E Neutral 8 0.115 SNPs&GO D425N Neutral 2 0.387 PhD-SNP: F[D]=39% F[N]=3% Nali=165 D425N Unclassified NA NA PANTHER: F[D]=NA F[N]=NA D425N Neutral 8 0.087 SNPs&GO Q430R Neutral 4 0.316 PhD-SNP: F[Q]=11% F[R]=2% Nali=173 Q430R Unclassified NA NA PANTHER: F[Q]=NA F[R]=NA Q430R Neutral 8 0.101 SNPs&GO M485L Neutral 7 0.128 PhD-SNP: F[M]=13% F[L]=27% Nali=168 M485L Unclassified NA NA PANTHER: F[M]=NA F[L]=NA M485L Neutral 9 0.045 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 ********************************************************************************************** ** ** ** 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. ** ** ** **********************************************************************************************