********************************************************************************************** ** ** ** SNPs&GO ** ** Predicting disease associated variation using GO terms ** ** ** ********************************************************************************************** WARNING: Incorrect mutation T253A WARNING: Incorrect mutation R418 WARNING: Incorrect mutation N27T Sequence File: SP.seq Mutation Prediction RI Probability Method A36T Neutral 8 0.076 PhD-SNP: F[A]=3% F[T]=80% Nali=965 A36T Neutral 7 0.154 PANTHER: F[A]=16% F[T]=8% A36T Neutral 8 0.087 SNPs&GO R79Q Disease 7 0.852 PhD-SNP: F[R]=94% F[Q]=2% Nali=996 R79Q Disease 4 0.725 PANTHER: F[R]=77% F[Q]=1% R79Q Disease 6 0.815 SNPs&GO D133H Disease 7 0.872 PhD-SNP: F[D]=97% F[H]=0% Nali=983 D133H Disease 3 0.647 PANTHER: F[D]=49% F[H]=1% D133H Disease 5 0.735 SNPs&GO R200S Disease 5 0.749 PhD-SNP: F[R]=84% F[S]=2% Nali=63 R200S Unclassified NA NA PANTHER: F[R]=NA F[S]=NA R200S Disease 2 0.617 SNPs&GO R227Q Disease 1 0.571 PhD-SNP: F[R]=77% F[Q]=6% Nali=34 R227Q Unclassified NA NA PANTHER: F[R]=NA F[Q]=NA R227Q Neutral 3 0.338 SNPs&GO Q237E Neutral 8 0.082 PhD-SNP: F[Q]=34% F[E]=24% Nali=28 Q237E Unclassified NA NA PANTHER: F[Q]=NA F[E]=NA Q237E Neutral 9 0.045 SNPs&GO I265T Neutral 2 0.412 PhD-SNP: F[I]=41% F[T]=5% Nali=21 I265T Unclassified NA NA PANTHER: F[I]=NA F[T]=NA I265T Neutral 6 0.182 SNPs&GO N277K Neutral 8 0.105 PhD-SNP: F[N]=25% F[K]=15% Nali=19 N277K Unclassified NA NA PANTHER: F[N]=NA F[K]=NA N277K Neutral 9 0.059 SNPs&GO H291Q Disease 1 0.533 PhD-SNP: F[H]=53% F[Q]=0% Nali=16 H291Q Unclassified NA NA PANTHER: F[H]=NA F[Q]=NA H291Q Neutral 5 0.225 SNPs&GO E299A Neutral 3 0.331 PhD-SNP: F[E]=67% F[A]=11% Nali=17 E299A Unclassified NA NA PANTHER: F[E]=NA F[A]=NA E299A Neutral 8 0.095 SNPs&GO G315R Disease 4 0.690 PhD-SNP: F[G]=53% F[R]=6% Nali=16 G315R Unclassified NA NA PANTHER: F[G]=NA F[R]=NA G315R Neutral 1 0.461 SNPs&GO T348S Neutral 2 0.409 PhD-SNP: F[T]=58% F[S]=0% Nali=18 T348S Unclassified NA NA PANTHER: F[T]=NA F[S]=NA T348S Neutral 6 0.190 SNPs&GO K349E Disease 2 0.622 PhD-SNP: F[K]=84% F[E]=0% Nali=18 K349E Unclassified NA NA PANTHER: F[K]=NA F[E]=NA K349E Neutral 1 0.431 SNPs&GO P379L Neutral 9 0.049 PhD-SNP: F[P]=63% F[L]=26% Nali=18 P379L Unclassified NA NA PANTHER: F[P]=NA F[L]=NA P379L Neutral 10 0.014 SNPs&GO G384E Neutral 0 0.484 PhD-SNP: F[G]=63% F[E]=0% Nali=18 G384E Unclassified NA NA PANTHER: F[G]=NA F[E]=NA G384E Neutral 7 0.171 SNPs&GO P396A Disease 1 0.539 PhD-SNP: F[P]=88% F[A]=0% Nali=15 P396A Unclassified NA NA PANTHER: F[P]=NA F[A]=NA P396A Neutral 5 0.242 SNPs&GO S421G Neutral 9 0.044 PhD-SNP: F[S]=58% F[G]=32% Nali=18 S421G Unclassified NA NA PANTHER: F[S]=NA F[G]=NA S421G Neutral 10 0.019 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. ** ** ** **********************************************************************************************