--------------------------------------------------------------- hg19.trackDb.html : Differences exist between hgwbeta and hgw2 (RR fields taken from public MySql server, not individual machine) 2888,2889c2888 < bayesDel |

BayesDel is a deleteriousness meta-score for coding and < bayesDel | non-coding variants, single nucleotide --- > bayesDel |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 2915c2914 < bayesDel | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > bayesDel | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 2935c2934 < bayesDel | MutScore --- > bayesDel | MutScore 2947,2980d2945 < bayesDel |

PrimateAI-3D - hg38/hg19

< bayesDel |

< bayesDel | Interpretation: Scores range from 0 to 1, with higher values indicating greater < bayesDel | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < bayesDel | pathogenic from benign missense variants. 75% of all possible missense variants are classified < bayesDel | as benign, 25% as pathogenic. < bayesDel |

< bayesDel |

< bayesDel | PrimateAI-3D < bayesDel | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < bayesDel | 4.5 million benign missense variants from 233 primate species and common human variants. < bayesDel | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < bayesDel | homology models) combined with multiple sequence alignments from 592 species. The track < bayesDel | contains pre-computed scores for all 70.7 million possible single nucleotide missense < bayesDel | variants. < bayesDel | Pathogenic variants are shown in red, < bayesDel | benign in blue. < bayesDel | Items can be filtered by prediction and by percentile score. < bayesDel |

< bayesDel | < bayesDel |

PromoterAI - hg38

< bayesDel |

< bayesDel | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < bayesDel | disruption of promoter function, negative scores indicate the variant is tolerated. < bayesDel |

< bayesDel |

< bayesDel | PromoterAI < bayesDel | predicts the impact of single nucleotide variants in gene < bayesDel | promoter regions, scoring all possible substitutions within 500 bp of annotated < bayesDel | transcription start sites. The track contains four bigWig subtracks (one per alternate < bayesDel | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < bayesDel | where overlapping transcripts produce different scores. < bayesDel |

< bayesDel | 3107,3126d3071 < bayesDel | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < bayesDel | Fiziev PP, Kuderna LFK et al. < bayesDel | < bayesDel | The landscape of tolerated genetic variation in humans and primates. < bayesDel | Science. 2023 Jun 2;380(6648):eabn8197. < bayesDel | PMID: 37262156; PMC: PMC10187174 < bayesDel |

< bayesDel | < bayesDel |

< bayesDel | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < bayesDel | Dutta A, Shon J et al. < bayesDel | < bayesDel | Predicting the clinical impact of human mutation with deep neural networks. < bayesDel | Nat Genet. 2018 Aug;50(8):1161-1170. < bayesDel | PMID: 30038395; PMC: PMC6237276 < bayesDel |

< bayesDel | < bayesDel |

29455c29400 < humanMethylationAtlasSignals |

Replicate tracks display the methylation signal for each individual sample and are --- > humanMethylationAtlasSignals |

Replicate tracks display the methylation signal for each individual sample and are 34981,34982c34926 < maxAFmutA |

BayesDel is a deleteriousness meta-score for coding and < maxAFmutA | non-coding variants, single nucleotide --- > maxAFmutA |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 35008c34952 < maxAFmutA | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > maxAFmutA | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 35028c34972 < maxAFmutA | MutScore --- > maxAFmutA | MutScore 35040,35073d34983 < maxAFmutA |

PrimateAI-3D - hg38/hg19

< maxAFmutA |

< maxAFmutA | Interpretation: Scores range from 0 to 1, with higher values indicating greater < maxAFmutA | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < maxAFmutA | pathogenic from benign missense variants. 75% of all possible missense variants are classified < maxAFmutA | as benign, 25% as pathogenic. < maxAFmutA |

< maxAFmutA |

< maxAFmutA | PrimateAI-3D < maxAFmutA | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < maxAFmutA | 4.5 million benign missense variants from 233 primate species and common human variants. < maxAFmutA | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < maxAFmutA | homology models) combined with multiple sequence alignments from 592 species. The track < maxAFmutA | contains pre-computed scores for all 70.7 million possible single nucleotide missense < maxAFmutA | variants. < maxAFmutA | Pathogenic variants are shown in red, < maxAFmutA | benign in blue. < maxAFmutA | Items can be filtered by prediction and by percentile score. < maxAFmutA |

< maxAFmutA | < maxAFmutA |

PromoterAI - hg38

< maxAFmutA |

< maxAFmutA | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < maxAFmutA | disruption of promoter function, negative scores indicate the variant is tolerated. < maxAFmutA |

< maxAFmutA |

< maxAFmutA | PromoterAI < maxAFmutA | predicts the impact of single nucleotide variants in gene < maxAFmutA | promoter regions, scoring all possible substitutions within 500 bp of annotated < maxAFmutA | transcription start sites. The track contains four bigWig subtracks (one per alternate < maxAFmutA | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < maxAFmutA | where overlapping transcripts produce different scores. < maxAFmutA |

< maxAFmutA | 35200,35219d35109 < maxAFmutA | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < maxAFmutA | Fiziev PP, Kuderna LFK et al. < maxAFmutA | < maxAFmutA | The landscape of tolerated genetic variation in humans and primates. < maxAFmutA | Science. 2023 Jun 2;380(6648):eabn8197. < maxAFmutA | PMID: 37262156; PMC: PMC10187174 < maxAFmutA |

< maxAFmutA | < maxAFmutA |

< maxAFmutA | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < maxAFmutA | Dutta A, Shon J et al. < maxAFmutA | < maxAFmutA | Predicting the clinical impact of human mutation with deep neural networks. < maxAFmutA | Nat Genet. 2018 Aug;50(8):1161-1170. < maxAFmutA | PMID: 30038395; PMC: PMC6237276 < maxAFmutA |

< maxAFmutA | < maxAFmutA |

35239,35240c35129 < MaxAFmutC |

BayesDel is a deleteriousness meta-score for coding and < MaxAFmutC | non-coding variants, single nucleotide --- > MaxAFmutC |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 35266c35155 < MaxAFmutC | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > MaxAFmutC | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 35286c35175 < MaxAFmutC | MutScore --- > MaxAFmutC | MutScore 35298,35331d35186 < MaxAFmutC |

PrimateAI-3D - hg38/hg19

< MaxAFmutC |

< MaxAFmutC | Interpretation: Scores range from 0 to 1, with higher values indicating greater < MaxAFmutC | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < MaxAFmutC | pathogenic from benign missense variants. 75% of all possible missense variants are classified < MaxAFmutC | as benign, 25% as pathogenic. < MaxAFmutC |

< MaxAFmutC |

< MaxAFmutC | PrimateAI-3D < MaxAFmutC | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < MaxAFmutC | 4.5 million benign missense variants from 233 primate species and common human variants. < MaxAFmutC | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < MaxAFmutC | homology models) combined with multiple sequence alignments from 592 species. The track < MaxAFmutC | contains pre-computed scores for all 70.7 million possible single nucleotide missense < MaxAFmutC | variants. < MaxAFmutC | Pathogenic variants are shown in red, < MaxAFmutC | benign in blue. < MaxAFmutC | Items can be filtered by prediction and by percentile score. < MaxAFmutC |

< MaxAFmutC | < MaxAFmutC |

PromoterAI - hg38

< MaxAFmutC |

< MaxAFmutC | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < MaxAFmutC | disruption of promoter function, negative scores indicate the variant is tolerated. < MaxAFmutC |

< MaxAFmutC |

< MaxAFmutC | PromoterAI < MaxAFmutC | predicts the impact of single nucleotide variants in gene < MaxAFmutC | promoter regions, scoring all possible substitutions within 500 bp of annotated < MaxAFmutC | transcription start sites. The track contains four bigWig subtracks (one per alternate < MaxAFmutC | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < MaxAFmutC | where overlapping transcripts produce different scores. < MaxAFmutC |

< MaxAFmutC | 35458,35477d35312 < MaxAFmutC | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < MaxAFmutC | Fiziev PP, Kuderna LFK et al. < MaxAFmutC | < MaxAFmutC | The landscape of tolerated genetic variation in humans and primates. < MaxAFmutC | Science. 2023 Jun 2;380(6648):eabn8197. < MaxAFmutC | PMID: 37262156; PMC: PMC10187174 < MaxAFmutC |

< MaxAFmutC | < MaxAFmutC |

< MaxAFmutC | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < MaxAFmutC | Dutta A, Shon J et al. < MaxAFmutC | < MaxAFmutC | Predicting the clinical impact of human mutation with deep neural networks. < MaxAFmutC | Nat Genet. 2018 Aug;50(8):1161-1170. < MaxAFmutC | PMID: 30038395; PMC: PMC6237276 < MaxAFmutC |

< MaxAFmutC | < MaxAFmutC |

35497,35498c35332 < MaxAFmutG |

BayesDel is a deleteriousness meta-score for coding and < MaxAFmutG | non-coding variants, single nucleotide --- > MaxAFmutG |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 35524c35358 < MaxAFmutG | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > MaxAFmutG | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 35544c35378 < MaxAFmutG | MutScore --- > MaxAFmutG | MutScore 35556,35589d35389 < MaxAFmutG |

PrimateAI-3D - hg38/hg19

< MaxAFmutG |

< MaxAFmutG | Interpretation: Scores range from 0 to 1, with higher values indicating greater < MaxAFmutG | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < MaxAFmutG | pathogenic from benign missense variants. 75% of all possible missense variants are classified < MaxAFmutG | as benign, 25% as pathogenic. < MaxAFmutG |

< MaxAFmutG |

< MaxAFmutG | PrimateAI-3D < MaxAFmutG | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < MaxAFmutG | 4.5 million benign missense variants from 233 primate species and common human variants. < MaxAFmutG | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < MaxAFmutG | homology models) combined with multiple sequence alignments from 592 species. The track < MaxAFmutG | contains pre-computed scores for all 70.7 million possible single nucleotide missense < MaxAFmutG | variants. < MaxAFmutG | Pathogenic variants are shown in red, < MaxAFmutG | benign in blue. < MaxAFmutG | Items can be filtered by prediction and by percentile score. < MaxAFmutG |

< MaxAFmutG | < MaxAFmutG |

PromoterAI - hg38

< MaxAFmutG |

< MaxAFmutG | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < MaxAFmutG | disruption of promoter function, negative scores indicate the variant is tolerated. < MaxAFmutG |

< MaxAFmutG |

< MaxAFmutG | PromoterAI < MaxAFmutG | predicts the impact of single nucleotide variants in gene < MaxAFmutG | promoter regions, scoring all possible substitutions within 500 bp of annotated < MaxAFmutG | transcription start sites. The track contains four bigWig subtracks (one per alternate < MaxAFmutG | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < MaxAFmutG | where overlapping transcripts produce different scores. < MaxAFmutG |

< MaxAFmutG | 35716,35735d35515 < MaxAFmutG | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < MaxAFmutG | Fiziev PP, Kuderna LFK et al. < MaxAFmutG | < MaxAFmutG | The landscape of tolerated genetic variation in humans and primates. < MaxAFmutG | Science. 2023 Jun 2;380(6648):eabn8197. < MaxAFmutG | PMID: 37262156; PMC: PMC10187174 < MaxAFmutG |

< MaxAFmutG | < MaxAFmutG |

< MaxAFmutG | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < MaxAFmutG | Dutta A, Shon J et al. < MaxAFmutG | < MaxAFmutG | Predicting the clinical impact of human mutation with deep neural networks. < MaxAFmutG | Nat Genet. 2018 Aug;50(8):1161-1170. < MaxAFmutG | PMID: 30038395; PMC: PMC6237276 < MaxAFmutG |

< MaxAFmutG | < MaxAFmutG |

35755,35756c35535 < MaxAFmutT |

BayesDel is a deleteriousness meta-score for coding and < MaxAFmutT | non-coding variants, single nucleotide --- > MaxAFmutT |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 35782c35561 < MaxAFmutT | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > MaxAFmutT | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 35802c35581 < MaxAFmutT | MutScore --- > MaxAFmutT | MutScore 35814,35847d35592 < MaxAFmutT |

PrimateAI-3D - hg38/hg19

< MaxAFmutT |

< MaxAFmutT | Interpretation: Scores range from 0 to 1, with higher values indicating greater < MaxAFmutT | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < MaxAFmutT | pathogenic from benign missense variants. 75% of all possible missense variants are classified < MaxAFmutT | as benign, 25% as pathogenic. < MaxAFmutT |

< MaxAFmutT |

< MaxAFmutT | PrimateAI-3D < MaxAFmutT | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < MaxAFmutT | 4.5 million benign missense variants from 233 primate species and common human variants. < MaxAFmutT | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < MaxAFmutT | homology models) combined with multiple sequence alignments from 592 species. The track < MaxAFmutT | contains pre-computed scores for all 70.7 million possible single nucleotide missense < MaxAFmutT | variants. < MaxAFmutT | Pathogenic variants are shown in red, < MaxAFmutT | benign in blue. < MaxAFmutT | Items can be filtered by prediction and by percentile score. < MaxAFmutT |

< MaxAFmutT | < MaxAFmutT |

PromoterAI - hg38

< MaxAFmutT |

< MaxAFmutT | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < MaxAFmutT | disruption of promoter function, negative scores indicate the variant is tolerated. < MaxAFmutT |

< MaxAFmutT |

< MaxAFmutT | PromoterAI < MaxAFmutT | predicts the impact of single nucleotide variants in gene < MaxAFmutT | promoter regions, scoring all possible substitutions within 500 bp of annotated < MaxAFmutT | transcription start sites. The track contains four bigWig subtracks (one per alternate < MaxAFmutT | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < MaxAFmutT | where overlapping transcripts produce different scores. < MaxAFmutT |

< MaxAFmutT | 35974,35993d35718 < MaxAFmutT | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < MaxAFmutT | Fiziev PP, Kuderna LFK et al. < MaxAFmutT | < MaxAFmutT | The landscape of tolerated genetic variation in humans and primates. < MaxAFmutT | Science. 2023 Jun 2;380(6648):eabn8197. < MaxAFmutT | PMID: 37262156; PMC: PMC10187174 < MaxAFmutT |

< MaxAFmutT | < MaxAFmutT |

< MaxAFmutT | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < MaxAFmutT | Dutta A, Shon J et al. < MaxAFmutT | < MaxAFmutT | Predicting the clinical impact of human mutation with deep neural networks. < MaxAFmutT | Nat Genet. 2018 Aug;50(8):1161-1170. < MaxAFmutT | PMID: 30038395; PMC: PMC6237276 < MaxAFmutT |

< MaxAFmutT | < MaxAFmutT |

36220,36221c35945 < mcap |

BayesDel is a deleteriousness meta-score for coding and < mcap | non-coding variants, single nucleotide --- > mcap |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 36247c35971 < mcap | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > mcap | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 36267c35991 < mcap | MutScore --- > mcap | MutScore 36279,36312d36002 < mcap |

PrimateAI-3D - hg38/hg19

< mcap |

< mcap | Interpretation: Scores range from 0 to 1, with higher values indicating greater < mcap | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < mcap | pathogenic from benign missense variants. 75% of all possible missense variants are classified < mcap | as benign, 25% as pathogenic. < mcap |

< mcap |

< mcap | PrimateAI-3D < mcap | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < mcap | 4.5 million benign missense variants from 233 primate species and common human variants. < mcap | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < mcap | homology models) combined with multiple sequence alignments from 592 species. The track < mcap | contains pre-computed scores for all 70.7 million possible single nucleotide missense < mcap | variants. < mcap | Pathogenic variants are shown in red, < mcap | benign in blue. < mcap | Items can be filtered by prediction and by percentile score. < mcap |

< mcap | < mcap |

PromoterAI - hg38

< mcap |

< mcap | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < mcap | disruption of promoter function, negative scores indicate the variant is tolerated. < mcap |

< mcap |

< mcap | PromoterAI < mcap | predicts the impact of single nucleotide variants in gene < mcap | promoter regions, scoring all possible substitutions within 500 bp of annotated < mcap | transcription start sites. The track contains four bigWig subtracks (one per alternate < mcap | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < mcap | where overlapping transcripts produce different scores. < mcap |

< mcap | < mcap |

< mcap | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < mcap | Dutta A, Shon J et al. < mcap | < mcap | Predicting the clinical impact of human mutation with deep neural networks. < mcap | Nat Genet. 2018 Aug;50(8):1161-1170. < mcap | PMID: 30038395; PMC: PMC6237276 < mcap |

< mcap | < mcap |

41371,41372c41041 < mutScore |

BayesDel is a deleteriousness meta-score for coding and < mutScore | non-coding variants, single nucleotide --- > mutScore |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 41398c41067 < mutScore | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > mutScore | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 41418c41087 < mutScore | MutScore --- > mutScore | MutScore 41430,41463d41098 < mutScore |

PrimateAI-3D - hg38/hg19

< mutScore |

< mutScore | Interpretation: Scores range from 0 to 1, with higher values indicating greater < mutScore | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < mutScore | pathogenic from benign missense variants. 75% of all possible missense variants are classified < mutScore | as benign, 25% as pathogenic. < mutScore |

< mutScore |

< mutScore | PrimateAI-3D < mutScore | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < mutScore | 4.5 million benign missense variants from 233 primate species and common human variants. < mutScore | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < mutScore | homology models) combined with multiple sequence alignments from 592 species. The track < mutScore | contains pre-computed scores for all 70.7 million possible single nucleotide missense < mutScore | variants. < mutScore | Pathogenic variants are shown in red, < mutScore | benign in blue. < mutScore | Items can be filtered by prediction and by percentile score. < mutScore |

< mutScore | < mutScore |

PromoterAI - hg38

< mutScore |

< mutScore | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < mutScore | disruption of promoter function, negative scores indicate the variant is tolerated. < mutScore |

< mutScore |

< mutScore | PromoterAI < mutScore | predicts the impact of single nucleotide variants in gene < mutScore | promoter regions, scoring all possible substitutions within 500 bp of annotated < mutScore | transcription start sites. The track contains four bigWig subtracks (one per alternate < mutScore | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < mutScore | where overlapping transcripts produce different scores. < mutScore |

< mutScore | 41590,41609d41224 < mutScore | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < mutScore | Fiziev PP, Kuderna LFK et al. < mutScore | < mutScore | The landscape of tolerated genetic variation in humans and primates. < mutScore | Science. 2023 Jun 2;380(6648):eabn8197. < mutScore | PMID: 37262156; PMC: PMC10187174 < mutScore |

< mutScore | < mutScore |

< mutScore | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < mutScore | Dutta A, Shon J et al. < mutScore | < mutScore | Predicting the clinical impact of human mutation with deep neural networks. < mutScore | Nat Genet. 2018 Aug;50(8):1161-1170. < mutScore | PMID: 30038395; PMC: PMC6237276 < mutScore |

< mutScore | < mutScore |

42593,42594c42208 < noAFmutA |

BayesDel is a deleteriousness meta-score for coding and < noAFmutA | non-coding variants, single nucleotide --- > noAFmutA |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 42620c42234 < noAFmutA | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > noAFmutA | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 42640c42254 < noAFmutA | MutScore --- > noAFmutA | MutScore 42652,42685d42265 < noAFmutA |

PrimateAI-3D - hg38/hg19

< noAFmutA |

< noAFmutA | Interpretation: Scores range from 0 to 1, with higher values indicating greater < noAFmutA | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < noAFmutA | pathogenic from benign missense variants. 75% of all possible missense variants are classified < noAFmutA | as benign, 25% as pathogenic. < noAFmutA |

< noAFmutA |

< noAFmutA | PrimateAI-3D < noAFmutA | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < noAFmutA | 4.5 million benign missense variants from 233 primate species and common human variants. < noAFmutA | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < noAFmutA | homology models) combined with multiple sequence alignments from 592 species. The track < noAFmutA | contains pre-computed scores for all 70.7 million possible single nucleotide missense < noAFmutA | variants. < noAFmutA | Pathogenic variants are shown in red, < noAFmutA | benign in blue. < noAFmutA | Items can be filtered by prediction and by percentile score. < noAFmutA |

< noAFmutA | < noAFmutA |

PromoterAI - hg38

< noAFmutA |

< noAFmutA | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < noAFmutA | disruption of promoter function, negative scores indicate the variant is tolerated. < noAFmutA |

< noAFmutA |

< noAFmutA | PromoterAI < noAFmutA | predicts the impact of single nucleotide variants in gene < noAFmutA | promoter regions, scoring all possible substitutions within 500 bp of annotated < noAFmutA | transcription start sites. The track contains four bigWig subtracks (one per alternate < noAFmutA | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < noAFmutA | where overlapping transcripts produce different scores. < noAFmutA |

< noAFmutA | 42812,42831d42391 < noAFmutA | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < noAFmutA | Fiziev PP, Kuderna LFK et al. < noAFmutA | < noAFmutA | The landscape of tolerated genetic variation in humans and primates. < noAFmutA | Science. 2023 Jun 2;380(6648):eabn8197. < noAFmutA | PMID: 37262156; PMC: PMC10187174 < noAFmutA |

< noAFmutA | < noAFmutA |

< noAFmutA | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < noAFmutA | Dutta A, Shon J et al. < noAFmutA | < noAFmutA | Predicting the clinical impact of human mutation with deep neural networks. < noAFmutA | Nat Genet. 2018 Aug;50(8):1161-1170. < noAFmutA | PMID: 30038395; PMC: PMC6237276 < noAFmutA |

< noAFmutA | < noAFmutA |

42851,42852c42411 < noAFmutC |

BayesDel is a deleteriousness meta-score for coding and < noAFmutC | non-coding variants, single nucleotide --- > noAFmutC |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 42878c42437 < noAFmutC | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > noAFmutC | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 42898c42457 < noAFmutC | MutScore --- > noAFmutC | MutScore 42910,42943d42468 < noAFmutC |

PrimateAI-3D - hg38/hg19

< noAFmutC |

< noAFmutC | Interpretation: Scores range from 0 to 1, with higher values indicating greater < noAFmutC | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < noAFmutC | pathogenic from benign missense variants. 75% of all possible missense variants are classified < noAFmutC | as benign, 25% as pathogenic. < noAFmutC |

< noAFmutC |

< noAFmutC | PrimateAI-3D < noAFmutC | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < noAFmutC | 4.5 million benign missense variants from 233 primate species and common human variants. < noAFmutC | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < noAFmutC | homology models) combined with multiple sequence alignments from 592 species. The track < noAFmutC | contains pre-computed scores for all 70.7 million possible single nucleotide missense < noAFmutC | variants. < noAFmutC | Pathogenic variants are shown in red, < noAFmutC | benign in blue. < noAFmutC | Items can be filtered by prediction and by percentile score. < noAFmutC |

< noAFmutC | < noAFmutC |

PromoterAI - hg38

< noAFmutC |

< noAFmutC | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < noAFmutC | disruption of promoter function, negative scores indicate the variant is tolerated. < noAFmutC |

< noAFmutC |

< noAFmutC | PromoterAI < noAFmutC | predicts the impact of single nucleotide variants in gene < noAFmutC | promoter regions, scoring all possible substitutions within 500 bp of annotated < noAFmutC | transcription start sites. The track contains four bigWig subtracks (one per alternate < noAFmutC | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < noAFmutC | where overlapping transcripts produce different scores. < noAFmutC |

< noAFmutC | 43070,43089d42594 < noAFmutC | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < noAFmutC | Fiziev PP, Kuderna LFK et al. < noAFmutC | < noAFmutC | The landscape of tolerated genetic variation in humans and primates. < noAFmutC | Science. 2023 Jun 2;380(6648):eabn8197. < noAFmutC | PMID: 37262156; PMC: PMC10187174 < noAFmutC |

< noAFmutC | < noAFmutC |

< noAFmutC | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < noAFmutC | Dutta A, Shon J et al. < noAFmutC | < noAFmutC | Predicting the clinical impact of human mutation with deep neural networks. < noAFmutC | Nat Genet. 2018 Aug;50(8):1161-1170. < noAFmutC | PMID: 30038395; PMC: PMC6237276 < noAFmutC |

< noAFmutC | < noAFmutC |

43109,43110c42614 < noAFmutG |

BayesDel is a deleteriousness meta-score for coding and < noAFmutG | non-coding variants, single nucleotide --- > noAFmutG |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 43136c42640 < noAFmutG | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > noAFmutG | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 43156c42660 < noAFmutG | MutScore --- > noAFmutG | MutScore 43168,43201d42671 < noAFmutG |

PrimateAI-3D - hg38/hg19

< noAFmutG |

< noAFmutG | Interpretation: Scores range from 0 to 1, with higher values indicating greater < noAFmutG | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < noAFmutG | pathogenic from benign missense variants. 75% of all possible missense variants are classified < noAFmutG | as benign, 25% as pathogenic. < noAFmutG |

< noAFmutG |

< noAFmutG | PrimateAI-3D < noAFmutG | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < noAFmutG | 4.5 million benign missense variants from 233 primate species and common human variants. < noAFmutG | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < noAFmutG | homology models) combined with multiple sequence alignments from 592 species. The track < noAFmutG | contains pre-computed scores for all 70.7 million possible single nucleotide missense < noAFmutG | variants. < noAFmutG | Pathogenic variants are shown in red, < noAFmutG | benign in blue. < noAFmutG | Items can be filtered by prediction and by percentile score. < noAFmutG |

< noAFmutG | < noAFmutG |

PromoterAI - hg38

< noAFmutG |

< noAFmutG | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < noAFmutG | disruption of promoter function, negative scores indicate the variant is tolerated. < noAFmutG |

< noAFmutG |

< noAFmutG | PromoterAI < noAFmutG | predicts the impact of single nucleotide variants in gene < noAFmutG | promoter regions, scoring all possible substitutions within 500 bp of annotated < noAFmutG | transcription start sites. The track contains four bigWig subtracks (one per alternate < noAFmutG | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < noAFmutG | where overlapping transcripts produce different scores. < noAFmutG |

< noAFmutG | 43328,43347d42797 < noAFmutG | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < noAFmutG | Fiziev PP, Kuderna LFK et al. < noAFmutG | < noAFmutG | The landscape of tolerated genetic variation in humans and primates. < noAFmutG | Science. 2023 Jun 2;380(6648):eabn8197. < noAFmutG | PMID: 37262156; PMC: PMC10187174 < noAFmutG |

< noAFmutG | < noAFmutG |

< noAFmutG | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < noAFmutG | Dutta A, Shon J et al. < noAFmutG | < noAFmutG | Predicting the clinical impact of human mutation with deep neural networks. < noAFmutG | Nat Genet. 2018 Aug;50(8):1161-1170. < noAFmutG | PMID: 30038395; PMC: PMC6237276 < noAFmutG |

< noAFmutG | < noAFmutG |

43367,43368c42817 < noAFmutT |

BayesDel is a deleteriousness meta-score for coding and < noAFmutT | non-coding variants, single nucleotide --- > noAFmutT |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 43394c42843 < noAFmutT | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > noAFmutT | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 43414c42863 < noAFmutT | MutScore --- > noAFmutT | MutScore 43426,43459d42874 < noAFmutT |

PrimateAI-3D - hg38/hg19

< noAFmutT |

< noAFmutT | Interpretation: Scores range from 0 to 1, with higher values indicating greater < noAFmutT | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < noAFmutT | pathogenic from benign missense variants. 75% of all possible missense variants are classified < noAFmutT | as benign, 25% as pathogenic. < noAFmutT |

< noAFmutT |

< noAFmutT | PrimateAI-3D < noAFmutT | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < noAFmutT | 4.5 million benign missense variants from 233 primate species and common human variants. < noAFmutT | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < noAFmutT | homology models) combined with multiple sequence alignments from 592 species. The track < noAFmutT | contains pre-computed scores for all 70.7 million possible single nucleotide missense < noAFmutT | variants. < noAFmutT | Pathogenic variants are shown in red, < noAFmutT | benign in blue. < noAFmutT | Items can be filtered by prediction and by percentile score. < noAFmutT |

< noAFmutT | < noAFmutT |

PromoterAI - hg38

< noAFmutT |

< noAFmutT | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < noAFmutT | disruption of promoter function, negative scores indicate the variant is tolerated. < noAFmutT |

< noAFmutT |

< noAFmutT | PromoterAI < noAFmutT | predicts the impact of single nucleotide variants in gene < noAFmutT | promoter regions, scoring all possible substitutions within 500 bp of annotated < noAFmutT | transcription start sites. The track contains four bigWig subtracks (one per alternate < noAFmutT | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < noAFmutT | where overlapping transcripts produce different scores. < noAFmutT |

< noAFmutT | 43586,43605d43000 < noAFmutT | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < noAFmutT | Fiziev PP, Kuderna LFK et al. < noAFmutT | < noAFmutT | The landscape of tolerated genetic variation in humans and primates. < noAFmutT | Science. 2023 Jun 2;380(6648):eabn8197. < noAFmutT | PMID: 37262156; PMC: PMC10187174 < noAFmutT |

< noAFmutT | < noAFmutT |

< noAFmutT | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < noAFmutT | Dutta A, Shon J et al. < noAFmutT | < noAFmutT | Predicting the clinical impact of human mutation with deep neural networks. < noAFmutT | Nat Genet. 2018 Aug;50(8):1161-1170. < noAFmutT | PMID: 30038395; PMC: PMC6237276 < noAFmutT |

< noAFmutT | < noAFmutT |

48367,48368c47762 < predictionScoresSuper |

BayesDel is a deleteriousness meta-score for coding and < predictionScoresSuper | non-coding variants, single nucleotide --- > predictionScoresSuper |

BayesDel is a deleteriousness meta-score for coding and non-coding variants, single nucleotide 48394c47788 < predictionScoresSuper | The Mendelian Clinically Applicable Pathogenicity (M-CAP) --- > predictionScoresSuper | The Mendelian Clinically Applicable Pathogenicity (M-CAP) 48414c47808 < predictionScoresSuper | MutScore --- > predictionScoresSuper | MutScore 48426,48459d47819 < predictionScoresSuper |

PrimateAI-3D - hg38/hg19

< predictionScoresSuper |

< predictionScoresSuper | Interpretation: Scores range from 0 to 1, with higher values indicating greater < predictionScoresSuper | predicted pathogenicity. The authors suggest a clinical threshold of 0.821 for distinguishing < predictionScoresSuper | pathogenic from benign missense variants. 75% of all possible missense variants are classified < predictionScoresSuper | as benign, 25% as pathogenic. < predictionScoresSuper |

< predictionScoresSuper |

< predictionScoresSuper | PrimateAI-3D < predictionScoresSuper | (Gao et al, Science 2023) is a semi-supervised 3D convolutional neural network trained on < predictionScoresSuper | 4.5 million benign missense variants from 233 primate species and common human variants. < predictionScoresSuper | It operates on voxelized protein structures at 2 Å resolution (from AlphaFold or < predictionScoresSuper | homology models) combined with multiple sequence alignments from 592 species. The track < predictionScoresSuper | contains pre-computed scores for all 70.7 million possible single nucleotide missense < predictionScoresSuper | variants. < predictionScoresSuper | Pathogenic variants are shown in red, < predictionScoresSuper | benign in blue. < predictionScoresSuper | Items can be filtered by prediction and by percentile score. < predictionScoresSuper |

< predictionScoresSuper | < predictionScoresSuper |

PromoterAI - hg38

< predictionScoresSuper |

< predictionScoresSuper | Interpretation: Scores range from -1 to 1. Positive scores indicate predicted < predictionScoresSuper | disruption of promoter function, negative scores indicate the variant is tolerated. < predictionScoresSuper |

< predictionScoresSuper |

< predictionScoresSuper | PromoterAI < predictionScoresSuper | predicts the impact of single nucleotide variants in gene < predictionScoresSuper | promoter regions, scoring all possible substitutions within 500 bp of annotated < predictionScoresSuper | transcription start sites. The track contains four bigWig subtracks (one per alternate < predictionScoresSuper | allele) covering 39.5 million positions, plus a bigBed track for the 3.8% of positions < predictionScoresSuper | where overlapping transcripts produce different scores. < predictionScoresSuper |

< predictionScoresSuper | 48583,48602d47942 < predictionScoresSuper |

< predictionScoresSuper | < predictionScoresSuper |

< predictionScoresSuper | Gao H, Hamp T, Ede J, Schraiber JG, McRae J, Singer-Berk M, Yang Y, Dietrich ASD, < predictionScoresSuper | Fiziev PP, Kuderna LFK et al. < predictionScoresSuper | < predictionScoresSuper | The landscape of tolerated genetic variation in humans and primates. < predictionScoresSuper | Science. 2023 Jun 2;380(6648):eabn8197. < predictionScoresSuper | PMID: 37262156; PMC: PMC10187174 < predictionScoresSuper |

< predictionScoresSuper | < predictionScoresSuper |

< predictionScoresSuper | Sundaram L, Gao H, Padigepati SR, McRae JF, Li Y, Kosmicki JA, Fritzilas N, Hakenberg J, < predictionScoresSuper | Dutta A, Shon J et al. < predictionScoresSuper | < predictionScoresSuper | Predicting the clinical impact of human mutation with deep neural networks. < predictionScoresSuper | Nat Genet. 2018 Aug;50(8):1161-1170. < predictionScoresSuper | PMID: 30038395; PMC: PMC6237276