********************************************************************************************** ** ** ** SNPs&GO ** ** Predicting disease associated variation using GO terms ** ** ** ********************************************************************************************** Sequence File: MMP9_HUMAN.seq Mutation Prediction RI Probability Method G84C Disease 6 0.801 PhD-SNP: F[G]=97% F[C]=0% Nali=524 G84C Disease 10 0.987 PANTHER: F[G]=96% F[C]=0% G84C Disease 8 0.877 SNPs&GO G84S Disease 5 0.741 PhD-SNP: F[G]=97% F[S]=0% Nali=524 G84S Disease 9 0.964 PANTHER: F[G]=96% F[S]=0% G84S Disease 7 0.844 SNPs&GO T90M Disease 4 0.683 PhD-SNP: F[T]=95% F[M]=1% Nali=531 T90M Disease 8 0.909 PANTHER: F[T]=75% F[M]=0% T90M Disease 6 0.819 SNPs&GO R98L Disease 9 0.925 PhD-SNP: F[R]=98% F[L]=0% Nali=558 R98L Disease 9 0.973 PANTHER: F[R]=93% F[L]=0% R98L Disease 9 0.927 SNPs&GO R98W Disease 8 0.904 PhD-SNP: F[R]=98% F[W]=0% Nali=558 R98W Disease 10 0.992 PANTHER: F[R]=93% F[W]=0% R98W Disease 8 0.904 SNPs&GO G100W Disease 8 0.888 PhD-SNP: F[G]=90% F[W]=0% Nali=561 G100W Disease 10 0.995 PANTHER: F[G]=96% F[W]=0% G100W Disease 8 0.890 SNPs&GO P233R Disease 8 0.918 PhD-SNP: F[P]=96% F[R]=0% Nali=247 P233R Unclassified NA NA PANTHER: F[P]=NA F[R]=NA P233R Disease 6 0.812 SNPs&GO F234C Disease 8 0.886 PhD-SNP: F[F]=87% F[C]=0% Nali=241 F234C Unclassified NA NA PANTHER: F[F]=NA F[C]=NA F234C Disease 5 0.735 SNPs&GO C256F Disease 8 0.885 PhD-SNP: F[C]=86% F[F]=0% Nali=256 C256F Unclassified NA NA PANTHER: F[C]=NA F[F]=NA C256F Disease 4 0.701 SNPs&GO C256Y Disease 7 0.874 PhD-SNP: F[C]=86% F[Y]=0% Nali=256 C256Y Unclassified NA NA PANTHER: F[C]=NA F[Y]=NA C256Y Disease 5 0.732 SNPs&GO C271S Disease 6 0.791 PhD-SNP: F[C]=83% F[S]=8% Nali=257 C271S Unclassified NA NA PANTHER: F[C]=NA F[S]=NA C271S Disease 5 0.734 SNPs&GO C271Y Disease 8 0.923 PhD-SNP: F[C]=83% F[Y]=0% Nali=257 C271Y Unclassified NA NA PANTHER: F[C]=NA F[Y]=NA C271Y Disease 7 0.870 SNPs&GO C288Y Disease 9 0.946 PhD-SNP: F[C]=95% F[Y]=0% Nali=272 C288Y Unclassified NA NA PANTHER: F[C]=NA F[Y]=NA C288Y Disease 8 0.922 SNPs&GO F292C Disease 8 0.888 PhD-SNP: F[F]=91% F[C]=0% Nali=273 F292C Unclassified NA NA PANTHER: F[F]=NA F[C]=NA F292C Disease 4 0.724 SNPs&GO C314G Disease 7 0.866 PhD-SNP: F[C]=93% F[G]=0% Nali=276 C314G Unclassified NA NA PANTHER: F[C]=NA F[G]=NA C314G Disease 7 0.843 SNPs&GO C314Y Disease 8 0.890 PhD-SNP: F[C]=93% F[Y]=0% Nali=276 C314Y Unclassified NA NA PANTHER: F[C]=NA F[Y]=NA C314Y Disease 7 0.826 SNPs&GO C347Y Disease 9 0.952 PhD-SNP: F[C]=93% F[Y]=0% Nali=236 C347Y Unclassified NA NA PANTHER: F[C]=NA F[Y]=NA C347Y Disease 9 0.938 SNPs&GO Y358C Disease 7 0.867 PhD-SNP: F[Y]=59% F[C]=0% Nali=265 Y358C Unclassified NA NA PANTHER: F[Y]=NA F[C]=NA Y358C Disease 3 0.653 SNPs&GO W372G Disease 7 0.851 PhD-SNP: F[W]=78% F[G]=0% Nali=250 W372G Unclassified NA NA PANTHER: F[W]=NA F[G]=NA W372G Disease 1 0.564 SNPs&GO W372L Disease 5 0.736 PhD-SNP: F[W]=78% F[L]=4% Nali=250 W372L Unclassified NA NA PANTHER: F[W]=NA F[L]=NA W372L Neutral 3 0.346 SNPs&GO P598L Disease 8 0.881 PhD-SNP: F[P]=93% F[L]=0% Nali=348 P598L Disease 10 0.981 PANTHER: F[P]=96% F[L]=0% P598L Disease 8 0.897 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. ** ** ** **********************************************************************************************