********************************************************************************************** ** ** ** SNPs&GO ** ** Predicting disease associated variation using GO terms ** ** ** ********************************************************************************************** Sequence File: LDLR_HUMAN.seq Mutation Prediction RI Probability Method W44R Disease 3 0.652 PhD-SNP: F[W]=44% F[R]=3% Nali=1535 W44R Disease 8 0.915 PANTHER: F[W]=45% F[R]=1% W44R Disease 8 0.881 SNPs&GO G98C Disease 7 0.852 PhD-SNP: F[G]=56% F[C]=0% Nali=1892 G98C Disease 10 0.981 PANTHER: F[G]=40% F[C]=0% G98C Disease 9 0.935 SNPs&GO G98R Disease 3 0.652 PhD-SNP: F[G]=56% F[R]=4% Nali=1892 G98R Disease 5 0.748 PANTHER: F[G]=40% F[R]=5% G98R Disease 7 0.847 SNPs&GO G98S Disease 3 0.632 PhD-SNP: F[G]=56% F[S]=4% Nali=1892 G98S Disease 6 0.787 PANTHER: F[G]=40% F[S]=4% G98S Disease 7 0.843 SNPs&GO T108M Neutral 8 0.110 PhD-SNP: F[T]=29% F[M]=0% Nali=1950 T108M Disease 9 0.943 PANTHER: F[T]=33% F[M]=0% T108M Disease 2 0.624 SNPs&GO D118G Disease 1 0.546 PhD-SNP: F[D]=21% F[G]=2% Nali=2140 D118G Disease 5 0.744 PANTHER: F[D]=20% F[G]=3% D118G Disease 5 0.762 SNPs&GO P144L Neutral 4 0.313 PhD-SNP: F[P]=31% F[L]=2% Nali=1901 P144L Disease 2 0.600 PANTHER: F[P]=16% F[L]=4% P144L Disease 1 0.571 SNPs&GO G207D Disease 5 0.747 PhD-SNP: F[G]=68% F[D]=2% Nali=2070 G207D Disease 8 0.902 PANTHER: F[G]=45% F[D]=1% G207D Disease 8 0.883 SNPs&GO R237H Neutral 5 0.234 PhD-SNP: F[R]=16% F[H]=2% Nali=1902 R237H Disease 6 0.825 PANTHER: F[R]=14% F[H]=1% R237H Disease 3 0.662 SNPs&GO G269S Neutral 4 0.303 PhD-SNP: F[G]=23% F[S]=7% Nali=1782 G269S Neutral 2 0.403 PANTHER: F[G]=10% F[S]=7% G269S Neutral 3 0.353 SNPs&GO P279H Disease 0 0.507 PhD-SNP: F[P]=48% F[H]=1% Nali=1379 P279H Disease 3 0.627 PANTHER: F[P]=27% F[H]=6% P279H Disease 2 0.594 SNPs&GO R303G Neutral 6 0.207 PhD-SNP: F[R]=9% F[G]=18% Nali=1603 R303G Neutral 3 0.369 PANTHER: F[R]=10% F[G]=14% R303G Neutral 4 0.317 SNPs&GO Y336D Disease 2 0.591 PhD-SNP: F[Y]=27% F[D]=1% Nali=815 Y336D Disease 7 0.842 PANTHER: F[Y]=13% F[D]=0% Y336D Disease 6 0.814 SNPs&GO E357G Neutral 0 0.500 PhD-SNP: F[E]=59% F[G]=1% Nali=895 E357G Disease 9 0.928 PANTHER: F[E]=52% F[G]=1% E357G Disease 8 0.907 SNPs&GO L371P Disease 2 0.592 PhD-SNP: F[L]=14% F[P]=1% Nali=1122 L371P Disease 6 0.804 PANTHER: F[L]=10% F[P]=0% L371P Disease 8 0.877 SNPs&GO G382R Disease 7 0.847 PhD-SNP: F[G]=82% F[R]=1% Nali=1160 G382R Disease 9 0.946 PANTHER: F[G]=66% F[R]=1% G382R Disease 9 0.946 SNPs&GO A394V Disease 4 0.676 PhD-SNP: F[A]=44% F[V]=6% Nali=1113 A394V Disease 2 0.606 PANTHER: F[A]=37% F[V]=10% A394V Disease 7 0.845 SNPs&GO P424L Neutral 2 0.405 PhD-SNP: F[P]=31% F[L]=4% Nali=1266 P424L Disease 6 0.806 PANTHER: F[P]=15% F[L]=1% P424L Disease 3 0.655 SNPs&GO L456F Neutral 1 0.451 PhD-SNP: F[L]=30% F[F]=4% Nali=1247 L456F Disease 6 0.818 PANTHER: F[L]=33% F[F]=2% L456F Disease 7 0.825 SNPs&GO T467N Neutral 4 0.310 PhD-SNP: F[T]=22% F[N]=4% Nali=1247 T467N Disease 3 0.655 PANTHER: F[T]=10% F[N]=2% T467N Disease 2 0.625 SNPs&GO D477N Disease 0 0.525 PhD-SNP: F[D]=25% F[N]=3% Nali=1305 D477N Disease 5 0.728 PANTHER: F[D]=16% F[N]=2% D477N Disease 6 0.803 SNPs&GO S499C Disease 0 0.514 PhD-SNP: F[S]=14% F[C]=1% Nali=1362 S499C Disease 9 0.953 PANTHER: F[S]=17% F[C]=0% S499C Disease 6 0.778 SNPs&GO V500A Neutral 1 0.446 PhD-SNP: F[V]=72% F[A]=6% Nali=1363 V500A Disease 9 0.965 PANTHER: F[V]=77% F[A]=0% V500A Disease 6 0.810 SNPs&GO T510M Neutral 2 0.398 PhD-SNP: F[T]=27% F[M]=2% Nali=1363 T510M Disease 8 0.878 PANTHER: F[T]=31% F[M]=1% T510M Disease 6 0.800 SNPs&GO I522S Disease 8 0.893 PhD-SNP: F[I]=66% F[S]=0% Nali=1368 I522S Disease 10 0.991 PANTHER: F[I]=64% F[S]=0% I522S Disease 9 0.955 SNPs&GO Y532C Disease 8 0.900 PhD-SNP: F[Y]=52% F[C]=1% Nali=1368 Y532C Disease 10 0.989 PANTHER: F[Y]=31% F[C]=0% Y532C Disease 8 0.913 SNPs&GO V613F Disease 7 0.833 PhD-SNP: F[V]=40% F[F]=2% Nali=1337 V613F Disease 8 0.915 PANTHER: F[V]=33% F[F]=1% V613F Disease 9 0.943 SNPs&GO E650K Neutral 4 0.296 PhD-SNP: F[E]=5% F[K]=6% Nali=1208 E650K Disease 3 0.638 PANTHER: F[E]=6% F[K]=1% E650K Disease 4 0.694 SNPs&GO P661L Disease 4 0.695 PhD-SNP: F[P]=61% F[L]=4% Nali=1101 P661L Disease 10 0.981 PANTHER: F[P]=74% F[L]=0% P661L Disease 8 0.879 SNPs&GO Q678H Neutral 4 0.301 PhD-SNP: F[Q]=9% F[H]=2% Nali=1178 Q678H Disease 5 0.754 PANTHER: F[Q]=9% F[H]=1% Q678H Disease 4 0.691 SNPs&GO P683L Neutral 5 0.227 PhD-SNP: F[P]=36% F[L]=23% Nali=923 P683L Neutral 3 0.337 PANTHER: F[P]=32% F[L]=30% P683L Neutral 3 0.351 SNPs&GO R709G Disease 3 0.659 PhD-SNP: F[R]=30% F[G]=2% Nali=906 R709G Disease 4 0.702 PANTHER: F[R]=25% F[G]=4% R709G Disease 8 0.900 SNPs&GO I792F Disease 0 0.521 PhD-SNP: F[I]=43% F[F]=1% Nali=154 I792F Disease 5 0.733 PANTHER: F[I]=12% F[F]=1% I792F Disease 6 0.806 SNPs&GO H837R Disease 4 0.695 PhD-SNP: F[H]=60% F[R]=0% Nali=120 H837R Disease 1 0.551 PANTHER: F[H]=8% F[R]=2% H837R Disease 7 0.830 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. ** ** ** **********************************************************************************************