********************************************************************************************** ** ** ** SNPs&GO ** ** Predicting disease associated variation using GO terms ** ** ** ********************************************************************************************** Sequence File: fileseq.seq Mutation Prediction RI Probability Method A14V Neutral 7 0.137 PhD-SNP: F[A]=17% F[V]=22% Nali=366 A14V Neutral 8 0.076 PANTHER: F[A]=11% F[V]=13% A14V Neutral 9 0.026 SNPs&GO S56C Disease 3 0.637 PhD-SNP: F[S]=36% F[C]=3% Nali=815 S56C Disease 4 0.714 PANTHER: F[S]=59% F[C]=1% S56C Neutral 0 0.496 SNPs&GO G73D Disease 8 0.905 PhD-SNP: F[G]=85% F[D]=0% Nali=901 G73D Disease 10 0.983 PANTHER: F[G]=96% F[D]=0% G73D Disease 6 0.796 SNPs&GO D111A Disease 1 0.567 PhD-SNP: F[D]=18% F[A]=2% Nali=879 D111A Neutral 4 0.306 PANTHER: F[D]=32% F[A]=4% D111A Neutral 4 0.306 SNPs&GO D124N Neutral 1 0.440 PhD-SNP: F[D]=7% F[N]=1% Nali=936 D124N Neutral 0 0.494 PANTHER: F[D]=67% F[N]=3% D124N Disease 1 0.564 SNPs&GO S129F Disease 4 0.688 PhD-SNP: F[S]=27% F[F]=2% Nali=943 S129F Disease 5 0.732 PANTHER: F[S]=59% F[F]=0% S129F Disease 5 0.742 SNPs&GO D167N Disease 0 0.514 PhD-SNP: F[D]=66% F[N]=16% Nali=957 D167N Disease 6 0.791 PANTHER: F[D]=83% F[N]=1% D167N Disease 3 0.659 SNPs&GO I180V Disease 1 0.562 PhD-SNP: F[I]=83% F[V]=6% Nali=969 I180V Neutral 1 0.452 PANTHER: F[I]=72% F[V]=9% I180V Neutral 2 0.420 SNPs&GO A181V Disease 2 0.591 PhD-SNP: F[A]=7% F[V]=3% Nali=969 A181V Neutral 3 0.357 PANTHER: F[A]=33% F[V]=3% A181V Neutral 3 0.370 SNPs&GO K195T Neutral 5 0.241 PhD-SNP: F[K]=13% F[T]=11% Nali=970 K195T Neutral 9 0.071 PANTHER: F[K]=21% F[T]=23% K195T Neutral 10 0.019 SNPs&GO M200I Neutral 3 0.331 PhD-SNP: F[M]=16% F[I]=15% Nali=962 M200I Neutral 6 0.217 PANTHER: F[M]=21% F[I]=4% M200I Neutral 7 0.167 SNPs&GO Y227C Disease 5 0.742 PhD-SNP: F[Y]=34% F[C]=1% Nali=892 Y227C Disease 7 0.847 PANTHER: F[Y]=66% F[C]=0% Y227C Disease 4 0.720 SNPs&GO L228V Neutral 3 0.342 PhD-SNP: F[L]=51% F[V]=11% Nali=928 L228V Neutral 3 0.369 PANTHER: F[L]=65% F[V]=5% L228V Neutral 4 0.301 SNPs&GO E244V Neutral 6 0.189 PhD-SNP: F[E]=12% F[V]=2% Nali=952 E244V Neutral 4 0.291 PANTHER: F[E]=15% F[V]=2% E244V Neutral 9 0.046 SNPs&GO V250M Neutral 4 0.280 PhD-SNP: F[V]=36% F[M]=2% Nali=962 V250M Disease 0 0.503 PANTHER: F[V]=43% F[M]=2% V250M Neutral 6 0.186 SNPs&GO P262H Disease 2 0.583 PhD-SNP: F[P]=56% F[H]=0% Nali=954 P262H Disease 2 0.594 PANTHER: F[P]=35% F[H]=1% P262H Neutral 4 0.294 SNPs&GO T266S Neutral 4 0.309 PhD-SNP: F[T]=17% F[S]=2% Nali=970 T266S Neutral 4 0.303 PANTHER: F[T]=39% F[S]=4% T266S Neutral 7 0.140 SNPs&GO R282H Neutral 5 0.275 PhD-SNP: F[R]=4% F[H]=1% Nali=884 R282H Unclassified NA NA PANTHER: F[R]=NA F[H]=NA R282H Neutral 7 0.132 SNPs&GO D287N Disease 0 0.505 PhD-SNP: F[D]=20% F[N]=2% Nali=964 D287N Neutral 4 0.283 PANTHER: F[D]=40% F[N]=5% D287N Neutral 5 0.255 SNPs&GO G300R Disease 6 0.804 PhD-SNP: F[G]=96% F[R]=0% Nali=979 G300R Disease 10 0.993 PANTHER: F[G]=97% F[R]=0% G300R Disease 5 0.758 SNPs&GO S305I Disease 6 0.815 PhD-SNP: F[S]=55% F[I]=2% Nali=982 S305I Disease 3 0.660 PANTHER: F[S]=59% F[I]=1% S305I Disease 3 0.650 SNPs&GO E346Q Neutral 8 0.094 PhD-SNP: F[E]=3% F[Q]=19% Nali=983 E346Q Neutral 5 0.227 PANTHER: F[E]=26% F[Q]=5% E346Q Neutral 9 0.054 SNPs&GO L382R Disease 2 0.580 PhD-SNP: F[L]=16% F[R]=5% Nali=981 L382R Disease 1 0.535 PANTHER: F[L]=19% F[R]=0% L382R Neutral 0 0.475 SNPs&GO V388I Neutral 9 0.072 PhD-SNP: F[V]=12% F[I]=8% Nali=971 V388I Neutral 6 0.224 PANTHER: F[V]=57% F[I]=11% V388I Neutral 9 0.051 SNPs&GO V390M Neutral 7 0.168 PhD-SNP: F[V]=7% F[M]=8% Nali=973 V390M Neutral 2 0.408 PANTHER: F[V]=34% F[M]=2% V390M Neutral 7 0.141 SNPs&GO L463V Neutral 7 0.137 PhD-SNP: F[L]=20% F[V]=11% Nali=645 L463V Unclassified NA NA PANTHER: F[L]=NA F[V]=NA L463V Neutral 9 0.044 SNPs&GO I476V Neutral 8 0.090 PhD-SNP: F[I]=10% F[V]=13% Nali=650 I476V Unclassified NA NA PANTHER: F[I]=NA F[V]=NA I476V Neutral 9 0.054 SNPs&GO R484H Neutral 5 0.256 PhD-SNP: F[R]=5% F[H]=1% Nali=662 R484H Unclassified NA NA PANTHER: F[R]=NA F[H]=NA R484H Neutral 7 0.161 SNPs&GO R492C Neutral 1 0.433 PhD-SNP: F[R]=97% F[C]=0% Nali=542 R492C Unclassified NA NA PANTHER: F[R]=NA F[C]=NA R492C Neutral 2 0.380 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. ** ** ** **********************************************************************************************