dbNSFP version 5.0a Release: January 1, 2025 Copyright: Copyright © 2025 GENOS Bioinformatics LLC. All rights reserved. Website: dbnsfp.org License Notice: dbNSFP version 5.0a is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). You are free to share (copy and redistribute) the material in any medium or format under the following terms: Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. NonCommercial: You may not use the material for commercial purposes. NoDerivatives: If you remix, transform, or build upon the material, you may not distribute the modified material. For more details, refer to the full license here: https://creativecommons.org/licenses/by-nc-nd/4.0/ If you are interested in commercial usage of dbNSFP, please contact license@dbnsfp.org. Major sources: Variant determination: Gencode release 46/Ensembl 112, released May, 2024 (hg38) Functional predictions: SIFT ensembl 66, released Jan, 2015 http://provean.jcvi.org/index.php SIFT4G 2.4, released Nov. 1, 2016 http://sift.bii.a-star.edu.sg/sift4g/public//Homo_sapiens/ PROVEAN 1.1 ensembl 66, released Jan, 2015 http://provean.jcvi.org/index.php Polyphen-2 v2.2.2, released Feb, 2012 http://genetics.bwh.harvard.edu/pph2/ MutationTaster 2021, https://www.genecascade.org/MutationTaster2021/ MutationAssessor release 3, http://mutationassessor.org/ fathmm-XF, http://fathmm.biocompute.org.uk/fathmm-xf/ CADD v1.7, http://cadd.gs.washington.edu/ VEST v4.0, http://karchinlab.org/apps/appVest.html DANN, https://cbcl.ics.uci.edu/public_data/DANN/ MetaSVM and MetaLR, doi: 10.1093/hmg/ddu733 MetaRNN v1.0, http://www.liulab.science/metarnn.html Eigen & Eigen PC v1.1, http://www.columbia.edu/~ii2135/eigen.html M-CAP v1.3, http://bejerano.stanford.edu/MCAP/ REVEL release May 3, 2021, https://sites.google.com/site/revelgenomics/ MutPred v1.2, http://mutpred.mutdb.org/ MVP 1.0, https://github.com/ShenLab/missense gMVP, https://github.com/ShenLab/gMVP/ MPC release1, ftp://ftp.broadinstitute.org/pub/ExAC_release/release1/regional_missense_constraint/ PrimateAI, https://github.com/Illumina/PrimateAI deogen2, https://deogen2.mutaframe.com/ ALoFT 1.0, http://aloft.gersteinlab.org/ BayesDel v1, http://fengbj-laboratory.org/BayesDel/BayesDel.html ClinPred, https://sites.google.com/site/clinpred/home LIST-S2 v1.10, https://precomputed.list-s2.msl.ubc.ca/ VARITY, http://varity.varianteffect.org/ ESM1b, https://huggingface.co/spaces/ntranoslab/esm_variants/tree/main AlphaMissense, https://console.cloud.google.com/storage/browser/dm_alphamissense PHACTboost, https://github.com/CompGenomeLab/PHACTboost MutFormer, https://github.com/WGLab/mutformer MutScore, https://iob-genetic.shinyapps.io/mutscore/ Conservation scores: phyloP100way_vertebrate (hg38) http://hgdownload.soe.ucsc.edu/goldenPath/hg38/phyloP100way/ phyloP470way_mammalian (hg38) https://hgdownload.soe.ucsc.edu/goldenPath/hg38/phyloP470way/ phyloP17way_primate (hg38) http://hgdownload.soe.ucsc.edu/goldenPath/hg38/phyloP17way/ phastCons100way_vertebrate (hg38) http://hgdownload.soe.ucsc.edu/goldenPath/hg38/phastCons100way/ phastCons470way_mammalian (hg38) https://hgdownload.cse.ucsc.edu/goldenpath/hg38/phastCons470way/ phastCons17way_primate (hg38) http://hgdownload.soe.ucsc.edu/goldenPath/hg38/phastCons17way/ GERP++ http://mendel.stanford.edu/SidowLab/downloads/gerp/ GERP_91_mammals https://ftp.ensembl.org/pub/current_compara/conservation_scores/91_mammals.gerp_conservation_score/ bStatistic in CADDv1.7 http://cadd.gs.washington.edu/ Other variant annotation sources: Interpro v101 http://www.ebi.ac.uk/interpro/ 1000 Genomes project http://www.1000genomes.org/ TOPMed freeze8 https://legacy.bravo.sph.umich.edu/freeze8/hg38/downloads dbSNP b156 (hg38) https://ftp.ncbi.nih.gov/snp/archive/b156/VCF/GCF_000001405.40.gz clinvar release 20240909 (hg38) ftp://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/ gnomAD exome subset v2.1.1 http://gnomad.broadinstitute.org/downloads gnomAD joint v4.1 http://gnomad.broadinstitute.org/downloads ALFA (Allele Frequency Aggregator) 20241028 https://www.ncbi.nlm.nih.gov/snp/docs/gsr/alfa/ Ancestral alleles (hg38) in Ensembl 112 ftp://ftp.ensembl.org/pub/release-112/fasta/ancestral_alleles/homo_sapiens_ancestor_GRCh38.tar.gz Altai Neanderthal genotypes: http://cdna.eva.mpg.de/neandertal/Vindija/VCF/Altai/ Denisova genotypes: http://cdna.eva.mpg.de/neandertal/Vindija/VCF/Denisova/ Vindija33.19 genotypes: http://cdna.eva.mpg.de/neandertal/Vindija/VCF/Vindija33.19/ Chagyrskaya genotype: http://cdna.eva.mpg.de/neandertal/Chagyrskaya/VCF/ MANE release 1.3: https://ftp.ncbi.nlm.nih.gov/refseq/MANE/MANE_human/release_1.3/ Other gene annotation sources: HGNC, downloaded on August 12, 2024 Uniprot, Release 2024_04 IntAct, downloaded on October 22, 2024 GWAS catalog, r2024-10-21 Haploinsufficiency probability data, from doi:10.1371/journal.pgen.1001154 Recessive probability data, from DOI:10.1126/science.1215040 Residual Variation Intolerance Score (RVIS), v3 http://genic-intolerance.org/ Genome-wide haploinsufficiency score (GHIS), from doi: 10.1093/nar/gkv474 ExAC Functional Gene Constraint, from release0.3.1 ExAC CNV gene score, from release0.3.1 Gene Ontology (GO), downloaded on October 23, 2024 ConsensusPathDB, Release 35 Essential genes, from doi:10.1371/journal.pgen.1003484, doi: 10.1126/science.aac7041, doi: 10.1016/j.cell.2015.11.015, doi: 10.1126/science.aac7557, doi:10.1371/journal.pcbi.1002886 Mouse genes, from Mouse Genome Informatics (MGI), 6.24 Zebrafish genes, from The Zebrafish Information Network (ZFIN), downloaded on October 24, 2024 KEGG pathway, from http://www.openbioinformatics.org/gengen/tutorial_calculate_gsea.html BioCarta pathway, from http://www.openbioinformatics.org/gengen/tutorial_calculate_gsea.html GDI, from doi: 10.1073/pnas.1518646112 LoFtool, from DOI:10.1093/bioinformatics/btv602 HIPred, from doi:10.1093/bioinformatics/btx028 HPO, data release 2024-08-13, https://hpo.jax.org/app/download/annotation ClinGen Dosage Sensitivity, 2024-10-23 The Humnan Protein Atlas, downloaded on October 22, 2024 OMIM, downloaded on October 22, 2024 Orphanet, downloaded on October 22, 2024 Files: dbNSFP5.0a_variant.chr<#>.gz - gzipped dbNSFP variant database files by chromosomes dbNSFP5.0_gene.gz - gzipped dbNSFP gene database file dbNSFP5.0a.readme.txt - this file search_dbNSFP50a.jar - companion GUI Java program for searching dbNSFP5.0a search_dbNSFP50a.class - companion command-line Java program for searching dbNSFP5.0a search_dbNSFP50a.readme.pdf - README file for search_dbNSFP50a.class tryhg19.in - an example input file with hg19 genome positions tryhg18.in - an example input file with hg18 genome positions tryhg38.in - an example input file with hg38 genome positions try.vcf - an example of vcf input file Description: The dbNSFP is an integrated database of functional annotations from multiple sources for the comprehensive collection of human non-synonymous SNPs (nsSNVs). Its current version includes a total of 83,572,434 nsSNVs and ssSNVs (splice site SNVs). It compiles prediction scores from 34 prediction algorithms (SIFT, SIFT4G, PROVEAN, Polyphen2-HDIV, Polyphen2-HVAR, MutationTaster 2021, MutationAssessor, FATHMM-XF coding, CADD, VEST4, DANN, MetaSVM, MetaLR, MetaRNN, Eigen, Eigen-PC, M-CAP, REVEL, MutPred, MVP, gMVP, MPC, PrimateAI, GEOGEN2, ALoFT, BayesDel, ClinPred, LIST-S2, VARITY, ESM1b, AlphaMissense, PHACTboost, MutFormer, MutScore), 9 conservation scores (bStatistic, phyloP100way_vertebrate, phyloP470way_mammalian, phyloP17way_primate, phastCons100way_vertebrate, phastCons470way_mammalian, phastCons17way_primate, GERP++ and GERP_91) and other function annotations. Since version 2.0, dbNSFP is separated into two parts, dbNSFP_variant and dbNSFP_gene. As their names indicate, the former focuses on variant annotations (including prediction scores and conservation scores), and the latter focuses on gene annotations. Since version 2.6, dbscSNV is added as an attached database, which includes all potential human SNVs within splicing consensus regions (−3 to +8 at the 5’ splice site and −12 to +2 at the 3’ splice site), i.e. scSNVs, and predictions for their potential of altering splicing. Since version 3, two branches of dbNSFP are provided: "a" branch is suitable for academic use, which includes all the resources, and "c" branch is suitable for commercial use, which does not include those do not allow or require licenses for commercial usages, including Polyphen-2, CADD,VEST,M-CAP,REVEL,MutPred,ClinPred,MutScore,and PHACTboost. Columns of dbNSFP_variant: 1 chr: chromosome number 2 pos(1-based): physical position on the chromosome as to hg38 (1-based coordinate). For mitochondrial SNV, this position refers to the rCRS (GenBank: NC_012920). 3 ref: reference nucleotide allele (as on the + strand) 4 alt: alternative nucleotide allele (as on the + strand) 5 aaref: reference amino acid "." if the variant is a splicing site SNP (2bp on each end of an intron) 6 aaalt: alternative amino acid "." if the variant is a splicing site SNP (2bp on each end of an intron) 7 rs_dbSNP: rs number from dbSNP 8 hg19_chr: chromosome as to hg19, "." means missing 9 hg19_pos(1-based): physical position on the chromosome as to hg19 (1-based coordinate). For mitochondrial SNV, this position refers to a YRI sequence (GenBank: AF347015) 10 hg18_chr: chromosome as to hg18, "." means missing 11 hg18_pos(1-based): physical position on the chromosome as to hg18 (1-based coordinate) For mitochondrial SNV, this position refers to a YRI sequence (GenBank: AF347015) 12 aapos: amino acid position as to the protein. "-1" if the variant is a splicing site SNP (2bp on each end of an intron). Multiple entries separated by ";", corresponding to Ensembl_proteinid 13 genename: gene name; if the nsSNV can be assigned to multiple genes, gene names are separated by ";" 14 Ensembl_geneid: Ensembl gene id 15 Ensembl_transcriptid: Ensembl transcript ids (Multiple entries separated by ";") 16 Ensembl_proteinid: Ensembl protein ids Multiple entries separated by ";", corresponding to Ensembl_transcriptids 17 Uniprot_acc: Uniprot accession number matching the Ensembl_proteinid Multiple entries separated by ";". 18 Uniprot_entry: Uniprot entry ID matching the Ensembl_proteinid Multiple entries separated by ";". 19 HGVSc_snpEff: HGVS coding variant presentation from snpEff Multiple entries separated by ";", corresponds to Ensembl_transcriptid 20 HGVSp_snpEff: HGVS protein variant presentation from snpEff Multiple entries separated by ";", corresponds to Ensembl_proteinid 21 HGVSc_VEP: HGVS coding variant presentation from VEP Multiple entries separated by ";", corresponds to Ensembl_transcriptid 22 HGVSp_VEP: HGVS protein variant presentation from VEP Multiple entries separated by ";", corresponds to Ensembl_proteinid 23 APPRIS: APPRIS annotation for the transcripts matching Ensembl_transcriptid Multiple entries separated by ";". Potential values: principal1, principal2, principal3, principal4, principal5, alternative1, alternative2. See https://useast.ensembl.org/info/genome/genebuild/transcript_quality_tags.html 24 GENCODE_basic: Whether the transcript belongs to GENCODE_basic (5' and 3' complete transcripts). Multiple entries separated by ";", matching Ensembl_transcriptid. See https://useast.ensembl.org/info/genome/genebuild/transcript_quality_tags.html 25 TSL: Transcript Support Level. Multiple entries separated by ";", matching Ensembl_transcriptid. Potential values: 1 to 5, NA. See https://useast.ensembl.org/info/genome/genebuild/transcript_quality_tags.html 26 VEP_canonical: canonical transcript used in Ensembl. Multiple entries separated by ";", matching Ensembl_transcriptid. See https://useast.ensembl.org/Help/Glossary?id=521 27 MANE: transcripts annotated by the MANE project. Multiple entries separated by ";", matching Ensembl_transcriptid. Potential values include "Select" (representative transcripts) or "Plus_Clinical" (additional clinical relevant transcripts). See https://www.ncbi.nlm.nih.gov/refseq/MANE/ 28 cds_strand: coding sequence (CDS) strand (+ or -) 29 refcodon: reference codon 30 codonpos: position on the codon (1, 2 or 3) 31 codon_degeneracy: degenerate type (0, 2 or 3) 32 Ancestral_allele: ancestral allele based on 8 primates EPO. Ancestral alleles by Ensembl 84. The following comes from its original README file: ACTG - high-confidence call, ancestral state supported by the other two sequences actg - low-confidence call, ancestral state supported by one sequence only N - failure, the ancestral state is not supported by any other sequence - - the extant species contains an insertion at this position . - no coverage in the alignment 33 AltaiNeandertal: genotype of a deep sequenced Altai Neanderthal 34 Denisova: genotype of a deep sequenced Denisova 35 VindijiaNeandertal: genotype of a deep sequenced Vindijia Neandertal 36 ChagyrskayaNeandertal: genotype of a deep sequenced Chagyrskaya Neandertal 37 SIFT_score: SIFT score (SIFTori). Scores range from 0 to 1. The smaller the score the more likely the SNP has damaging effect. Multiple scores separated by ";", corresponding to Ensembl_proteinid. 38 SIFT_converted_rankscore: SIFTori scores were first converted to SIFTnew=1-SIFTori, then ranked among all SIFTnew scores in dbNSFP. The rankscore is the ratio of the rank the SIFTnew score over the total number of SIFTnew scores in dbNSFP. If there are multiple scores, only the most damaging (largest) rankscore is presented. The rankscores range from 0.00964 to 0.91255. 39 SIFT_pred: If SIFTori is smaller than 0.05 (rankscore>0.39575) the corresponding nsSNV is predicted as "D(amaging)"; otherwise it is predicted as "T(olerated)". Multiple predictions separated by ";" 40 SIFT4G_score: SIFT 4G score (SIFT4G). Scores range from 0 to 1. The smaller the score the more likely the SNP has damaging effect. Multiple scores separated by ",", corresponding to Ensembl_transcriptid 41 SIFT4G_converted_rankscore: SIFT4G scores were first converted to SIFT4Gnew=1-SIFT4G, then ranked among all SIFT4Gnew scores in dbNSFP. The rankscore is the ratio of the rank the SIFT4Gnew score over the total number of SIFT4Gnew scores in dbNSFP. If there are multiple scores, only the most damaging (largest) rankscore is presented. 42 SIFT4G_pred: If SIFT4G is < 0.05 the corresponding nsSNV is predicted as "D(amaging)"; otherwise it is predicted as "T(olerated)". Multiple scores separated by ",", corresponding to Ensembl_transcriptid 43 Polyphen2_HDIV_score: Polyphen2 score based on HumDiv, i.e. hdiv_prob. The score ranges from 0 to 1. Multiple entries separated by ";", corresponding to Uniprot_acc. 44 Polyphen2_HDIV_rankscore: Polyphen2 HDIV scores were first ranked among all HDIV scores in dbNSFP. The rankscore is the ratio of the rank the score over the total number of the scores in dbNSFP. If there are multiple scores, only the most damaging (largest) rankscore is presented. The scores range from 0.03061 to 0.91137. 45 Polyphen2_HDIV_pred: Polyphen2 prediction based on HumDiv, "D" ("probably damaging", HDIV score in [0.957,1] or rankscore in [0.55859,0.91137]), "P" ("possibly damaging", HDIV score in [0.454,0.956] or rankscore in [0.37043,0.55681]) and "B" ("benign", HDIV score in [0,0.452] or rankscore in [0.03061,0.36974]). Score cutoff for binary classification is 0.5 for HDIV score or 0.38028 for rankscore, i.e. the prediction is "neutral" if the HDIV score is smaller than 0.5 (rankscore is smaller than 0.38028), and "deleterious" if the HDIV score is larger than 0.5 (rankscore is larger than 0.38028). Multiple entries are separated by ";", corresponding to Uniprot_acc. 46 Polyphen2_HVAR_score: Polyphen2 score based on HumVar, i.e. hvar_prob. The score ranges from 0 to 1. Multiple entries separated by ";", corresponding to Uniprot_acc. 47 Polyphen2_HVAR_rankscore: Polyphen2 HVAR scores were first ranked among all HVAR scores in dbNSFP. The rankscore is the ratio of the rank the score over the total number of the scores in dbNSFP. If there are multiple scores, only the most damaging (largest) rankscore is presented. The scores range from 0.01493 to 0.97581. 48 Polyphen2_HVAR_pred: Polyphen2 prediction based on HumVar, "D" ("probably damaging", HVAR score in [0.909,1] or rankscore in [0.65694,0.97581]), "P" ("possibly damaging", HVAR in [0.447,0.908] or rankscore in [0.47121,0.65622]) and "B" ("benign", HVAR score in [0,0.446] or rankscore in [0.01493,0.47076]). Score cutoff for binary classification is 0.5 for HVAR score or 0.48762 for rankscore, i.e. the prediction is "neutral" if the HVAR score is smaller than 0.5 (rankscore is smaller than 0.48762), and "deleterious" if the HVAR score is larger than 0.5 (rankscore is larger than 0.48762). Multiple entries are separated by ";", corresponding to Uniprot_acc. 49 MutationTaster_score: MutationTaster p-value (MTori), ranges from 0 to 1. Multiple scores are separated by ";". Information on corresponding transcript(s) can be found by querying http://www.mutationtaster.org/ChrPos.html 50 MutationTaster_converted_rankscore: The MTori scores were first converted. If the prediction is "A" or "D" MTnew=MTori; if the prediction is "N" or "P", MTnew=1-MTori. Then MTnew scores were ranked among all MTnew scores in dbNSFP. If there are multiple scores of a SNV, only the largest MTnew was used in ranking. The rankscore is the ratio of the rank of the score over the total number of MTnew scores in dbNSFP. The scores range from 0.08979 to 0.81001. 51 MutationTaster_pred: MutationTaster prediction, "A" ("disease_causing_automatic"), "D" ("disease_causing"), "N" ("polymorphism") or "P" ("polymorphism_automatic"). The score cutoff between "D" and "N" is 0.5 for MTnew and 0.31733 for the rankscore. 52 MutationTaster_model: MutationTaster prediction models. 53 MutationTaster_trees_benign: the number of decision trees of the Random Forest suggesting benign; trees_deleterious/(trees_benign+trees_deleterious) can be used as a measure for deleteriousness. 54 MutationTaster_trees_deleterious: the number of decision trees of the Random Forest suggesting deleterious; trees_deleterious/(trees_benign+trees_deleterious) can be used as a measure for deleteriousness. 55 MutationAssessor_score: MutationAssessor functional impact combined score (MAori). The score ranges from -5.17 to 6.49 in dbNSFP. Multiple entries are separated by ";", corresponding to Uniprot_entry. 56 MutationAssessor_rankscore: MAori scores were ranked among all MAori scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of MAori scores in dbNSFP. The scores range from 0 to 1. 57 MutationAssessor_pred: MutationAssessor's functional impact of a variant - predicted functional, i.e. high ("H") or medium ("M"), or predicted non-functional, i.e. low ("L") or neutral ("N"). The MAori score cutoffs between "H" and "M", "M" and "L", and "L" and "N", are 3.5, 1.935 and 0.8, respectively. The rankscore cutoffs between "H" and "M", "M" and "L", and "L" and "N", are 0.9307, 0.52043 and 0.19675, respectively. 58 PROVEAN_score: PROVEAN score (PROVEANori). Scores range from -14 to 14. The smaller the score the more likely the SNP has damaging effect. Multiple scores separated by ";", corresponding to Ensembl_proteinid. 59 PROVEAN_converted_rankscore: PROVEANori were first converted to PROVEANnew=1-(PROVEANori+14)/28, then ranked among all PROVEANnew scores in dbNSFP. The rankscore is the ratio of the rank the PROVEANnew score over the total number of PROVEANnew scores in dbNSFP. If there are multiple scores, only the most damaging (largest) rankscore is presented. The scores range from 0 to 1. 60 PROVEAN_pred: If PROVEANori <= -2.5 (rankscore>=0.54382) the corresponding nsSNV is predicted as "D(amaging)"; otherwise it is predicted as "N(eutral)". Multiple predictions separated by ";", corresponding to Ensembl_proteinid. 61 VEST4_score: VEST 4.0 score. Score ranges from 0 to 1. The larger the score the more likely the mutation may cause functional change. Multiple scores separated by ";", corresponding to Ensembl_transcriptid. Please note this score is free for non-commercial use. For more details please refer to http://wiki.chasmsoftware.org/index.php/SoftwareLicense. Commercial users should contact the Johns Hopkins Technology Transfer office. 62 VEST4_rankscore: VEST4 scores were ranked among all VEST4 scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of VEST4 scores in dbNSFP. In case there are multiple scores for the same variant, the largest score (most damaging) is presented. The scores range from 0 to 1. Please note VEST score is free for non-commercial use. For more details please refer to http://wiki.chasmsoftware.org/index.php/SoftwareLicense. Commercial users should contact the Johns Hopkins Technology Transfer office. 63 MetaSVM_score: Our support vector machine (SVM) based ensemble prediction score, which incorporated 10 scores (SIFT, PolyPhen-2 HDIV, PolyPhen-2 HVAR, GERP++, MutationTaster, Mutation Assessor, FATHMM, LRT, SiPhy, PhyloP) and the maximum frequency observed in the 1000 genomes populations. Larger value means the SNV is more likely to be damaging. Scores range from -2 to 3 in dbNSFP. 64 MetaSVM_rankscore: MetaSVM scores were ranked among all MetaSVM scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of MetaSVM scores in dbNSFP. The scores range from 0 to 1. 65 MetaSVM_pred: Prediction of our SVM based ensemble prediction score,"T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0. The rankscore cutoff between "D" and "T" is 0.82257. 66 MetaLR_score: Our logistic regression (LR) based ensemble prediction score, which incorporated 10 scores (SIFT, PolyPhen-2 HDIV, PolyPhen-2 HVAR, GERP++, MutationTaster, Mutation Assessor, FATHMM, LRT, SiPhy, PhyloP) and the maximum frequency observed in the 1000 genomes populations. Larger value means the SNV is more likely to be damaging. Scores range from 0 to 1. 67 MetaLR_rankscore: MetaLR scores were ranked among all MetaLR scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of MetaLR scores in dbNSFP. The scores range from 0 to 1. 68 MetaLR_pred: Prediction of our MetaLR based ensemble prediction score,"T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.5. The rankscore cutoff between "D" and "T" is 0.81101. 69 Reliability_index: Number of observed component scores (except the maximum frequency in the 1000 genomes populations) for MetaSVM and MetaLR. Ranges from 1 to 10. As MetaSVM and MetaLR scores are calculated based on imputed data, the less missing component scores, the higher the reliability of the scores and predictions. 70 MetaRNN_score: Our recurrent neural network (RNN) based ensemble prediction score, which incorporated 16 scores (SIFT, Polyphen2_HDIV, Polyphen2_HVAR, MutationAssessor, PROVEAN, VEST4, M-CAP, REVEL, MutPred, MVP, PrimateAI, DEOGEN2, CADD, fathmm-XF, Eigen and GenoCanyon), 8 conservation scores (GERP, phyloP100way_vertebrate, phyloP30way_mammalian, phyloP17way_primate, phastCons100way_vertebrate, phastCons30way_mammalian, phastCons17way_primate and SiPhy), and allele frequency information from the 1000 Genomes Project (1000GP), ExAC, and gnomAD. Larger value means the SNV is more likely to be damaging. Scores range from 0 to 1. 71 MetaRNN_rankscore: MetaRNN scores were ranked among all MetaRNN scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of MetaRNN scores in dbNSFP. The scores range from 0 to 1. 72 MetaRNN_pred: Prediction of our MetaRNN based ensemble prediction score,"T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.5. The rankscore cutoff between "D" and "T" is 0.6149. 73 M-CAP_score: M-CAP is hybrid ensemble score (details in DOI: 10.1038/ng.3703). Scores range from 0 to 1. The larger the score the more likely the SNP has damaging effect. 74 M-CAP_rankscore: M-CAP scores were ranked among all M-CAP scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of M-CAP scores in dbNSFP. 75 M-CAP_pred: Prediction of M-CAP score based on the authors' recommendation, "T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.025. 76 REVEL_score: REVEL is an ensemble score based on 13 individual scores for predicting the pathogenicity of missense variants. Scores range from 0 to 1. The larger the score the more likely the SNP has damaging effect. "REVEL scores are freely available for non-commercial use. For other uses, please contact Weiva Sieh" (weiva.sieh@mssm.edu) Multiple entries are separated by ";", corresponding to Ensembl_transcriptid. 77 REVEL_rankscore: REVEL scores were ranked among all REVEL scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of REVEL scores in dbNSFP. 78 MutPred_score: General MutPred score. Scores range from 0 to 1. The larger the score the more likely the SNP has damaging effect. 79 MutPred_rankscore: MutPred scores were ranked among all MutPred scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of MutPred scores in dbNSFP. 80 MutPred_protID: UniProt accession or Ensembl transcript ID used for MutPred_score calculation. 81 MutPred_AAchange: Amino acid change used for MutPred_score calculation. 82 MutPred_Top5features: Top 5 features (molecular mechanisms of disease) as predicted by MutPred with p values. MutPred_score > 0.5 and p < 0.05 are referred to as actionable hypotheses. MutPred_score > 0.75 and p < 0.05 are referred to as confident hypotheses. MutPred_score > 0.75 and p < 0.01 are referred to as very confident hypotheses. 83 MVP_score: A pathogenicity prediction score for missense variants using deep learning approach. The range of MVP score is from 0 to 1. The larger the score, the more likely the variant is pathogenic. The authors suggest thresholds of 0.7 and 0.75 for separating damaging vs tolerant variants in constrained genes (ExAC pLI >=0.5) and non-constrained genes (ExAC pLI<0.5), respectively. Details see doi: http://dx.doi.org/10.1101/259390 Multiple entries are separated by ";", corresponding to Ensembl_transcriptid. 84 MVP_rankscore: MVP scores were ranked among all MVP scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of MVP scores in dbNSFP. 85 gMVP_score: A pathogenicity prediction score for missense variants using a graph attention neural network model. The range of gMVP score is from 0 to 1. The larger the score, the more likely the variant is pathogenic. Details see doi: https://www.nature.com/articles/s42256-022-00561-w Multiple entries are separated by ";", corresponding to Ensembl_transcriptid. 86 gMVP_rankscore: gMVP scores were ranked among all gMVP scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of gMVP scores in dbNSFP. 87 MPC_score: A deleteriousness prediction score for missense variants based on regional missense constraint. The range of MPC score is 0 to 5. The larger the score, the more likely the variant is pathogenic. Details see doi: http://dx.doi.org/10.1101/148353. Multiple entries are separated by ";", corresponding to Ensembl_transcriptid. 88 MPC_rankscore: MPC scores were ranked among all MPC scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of MPC scores in dbNSFP. 89 PrimateAI_score: A pathogenicity prediction score for missense variants based on common variants of non-human primate species using a deep neural network. The range of PrimateAI score is 0 to 1. The larger the score, the more likely the variant is pathogenic. The authors suggest a threshold of 0.803 for separating damaging vs tolerant variants. Details see https://doi.org/10.1038/s41588-018-0167-z 90 PrimateAI_rankscore: PrimateAI scores were ranked among all PrimateAI scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of PrimateAI scores in dbNSFP. 91 PrimateAI_pred: Prediction of PrimateAI score based on the authors' recommendation, "T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.803. 92 DEOGEN2_score: A deleteriousness prediction score "which incorporates heterogeneous information about the molecular effects of the variants, the domains involved, the relevance of the gene and the interactions in which it participates". It ranges from 0 to 1. The larger the score, the more likely the variant is deleterious. The authors suggest a threshold of 0.5 for separating damaging vs tolerant variants. 93 DEOGEN2_rankscore: DEOGEN2 scores were ranked among all DEOGEN2 scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of DEOGEN2 scores in dbNSFP. 94 DEOGEN2_pred: Prediction of DEOGEN2 score based on the authors' recommendation, "T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.5. 95 BayesDel_addAF_score: A deleteriousness preidction meta-score for SNVs and indels with inclusion of MaxAF. See https://doi.org/10.1002/humu.23158 for details. The range of the score in dbNSFP is from -1.11707 to 0.750927. The higher the score, the more likely the variant is pathogenic. The author suggested cutoff between deleterious ("D") and tolerated ("T") is 0.0692655. 96 BayesDel_addAF_rankscore: BayesDel_addAF scores were ranked among all BayesDel_addAF scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of BayesDel_addAF scores in dbNSFP. 97 BayesDel_addAF_pred: Prediction of BayesDel_addAF score based on the authors' recommendation, "T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.0692655. 98 BayesDel_noAF_score: A deleteriousness preidction meta-score for SNVs and indels without inclusion of MaxAF. See https://doi.org/10.1002/humu.23158 for details. The range of the score in dbNSFP is from -1.31914 to 0.840878. The higher the score, the more likely the variant is pathogenic. The author suggested cutoff between deleterious ("D") and tolerated ("T") is -0.0570105. 99 BayesDel_noAF_rankscore: BayesDel_noAF scores were ranked among all BayesDel_noAF scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of BayesDel_noAF scores in dbNSFP. 100 BayesDel_noAF_pred: Prediction of BayesDel_noAF score based on the authors' recommendation, "T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is -0.0570105. 101 ClinPred_score: A deleteriousness preidction meta-score for nonsynonymous SNVs. See https://doi.org/10.1016/j.ajhg.2018.08.005. for details. The range of the score in dbNSFP is from 0 to 1. The higher the score, the more likely the variant is pathogenic. The author suggested cutoff between deleterious ("D") and tolerated ("T") is 0.5. 102 ClinPred_rankscore: ClinPred scores were ranked among all ClinPred scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of ClinPred scores in dbNSFP. 103 ClinPred_pred: Prediction of ClinPred score based on the authors' recommendation, "T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.5. 104 LIST-S2_score: A deleteriousness preidction score for nonsynonymous SNVs. See https://doi.org/10.1093/nar/gkaa288. for details. The range of the score in dbNSFP is from 0 to 1. The higher the score, the more likely the variant is pathogenic. The author suggested cutoff between deleterious ("D") and tolerated ("T") is 0.85. 105 LIST-S2_rankscore: LIST-S2 scores were ranked among all LIST-S2 scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of LIST-S2 scores in dbNSFP. 106 LIST-S2_pred: Prediction of LIST-S2 score based on the authors' recommendation, "T(olerated)" or "D(amaging)". The score cutoff between "D" and "T" is 0.85. 107 VARITY_R_score: VARITY_R scores are pathogenicity prediction scores for rare human missense variants. The range of VARITY_R score is from 0 to 1. The larger the score, the more likely the variant is pathogenic. Details see doi: https://doi.org/10.1016/j.ajhg.2021.08.012 108 VARITY_R_rankscore: VARITY_R scores were ranked among all VARITY_R scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of VARITY_R scores in dbNSFP. 109 VARITY_ER_score: VARITY_ER scores are pathogenicity prediction scores for extreme rare human missense variants. The range of VARITY_ER score is from 0 to 1. The larger the score, the more likely the variant is pathogenic. Details see doi: https://doi.org/10.1016/j.ajhg.2021.08.012 110 VARITY_ER_rankscore: VARITY_ER scores were ranked among all VARITY_ER scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of VARITY_ER scores in dbNSFP. 111 VARITY_R_LOO_score: "Same as VARITY_R except the prediction on the variants used for training was made using Leave-One-Variant out." Details see doi: https://doi.org/10.1016/j.ajhg.2021.08.012 112 VARITY_R_LOO_rankscore: VARITY_R_LOO scores were ranked among all VARITY_R_LOO scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of VARITY_R_LOO scores in dbNSFP. 113 VARITY_ER_LOO_score: "Same as VARITY_ER except the prediction on the variants used for training was made using Leave-One-Variant out." Details see https://doi.org/10.1016/j.ajhg.2021.08.012 114 VARITY_ER_LOO_rankscore: VARITY_ER_LOO scores were ranked among all VARITY_ER_LOO scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of VARITY_ER_LOO scores in dbNSFP. 115 ESM1b_score: ESM1b scores are log-likelihood ratio (LLR) scores for predicting the pathogenic effects of coding variants based on a 650-million-parameter protein language model, ESM1b. The range of ESM1b score in dbNSFP is from -24.538 to 6.937. The smaller the score, the more likely the variant is pathogenic. Details see doi: https://doi.org/10.1038/s41588-023-01465-0 116 ESM1b_rankscore: ESM1b scores were firstly negated (i.e., -ESM1b_score), then ranked among all -ESM1b_score scores in dbNSFP. The rankscore is the ratio of the rank of the -ESM1b_score over the total number of scores in dbNSFP. 117 ESM1b_pred: The authors do not recommend a threshold for separating deleterious (D) variants versus tolerated (T) variants. This prediction is based on the threshold of -7.5 described in their paper that yields a true-positive rate of 81% and a true-negative rate of 82% in their ClinVar and HGMD test datasets. 118 AlphaMissense_score: AlphaMissense is a unsupervised model for predicting the pathogenicity of human missense variants by incorporating structural context of an AlphaFold-derived system. The AlphaMissense score ranges from 0 to 1. The larger the score, the more likely the variant is pathogenic. Details see https://doi.org/10.1126/science.adg7492. License information: Copyright (2023) DeepMind Technologies Limited. All materials are licensed under the Creative Commons Attribution 4.0 International License (CC-BY) (the “License”). You may obtain a copy of the License at: https://creativecommons.org/licenses/by/4.0/legalcode. 119 AlphaMissense_rankscore: AlphaMissense scores were ranked among all AlphaMissense scores in dbNSFP. The rankscore is the ratio of the rank of the AlphaMissense_score over the total number of scores in dbNSFP. 120 AlphaMissense_pred: The AlphaMissense classification of likely (B)enign, (A)mbiguous, or likely (P)athogenic with 90% expected precision estimated from ClinVar for likely benign and likely pathogenic classes. 121 PHACTboost_score: "PHACTboost is a gradiatent boosting tree based classifier that combines PHACT scores with information from multiple sequence alignment, phylogenetic trees, and ancestral reconstruction." The range of the score is from 0 to 1, the larger the score the more likely the variant is pathegenic. Details see https://doi.org/10.1093/molbev/msae136. The authors recommend to use 0.62 as the cutoff for binary prediction (personal communication). 122 PHACTboost_rankscore: PHACTboost scores were ranked among all PHACTboost scores in dbNSFP. The rankscore is the ratio of the rank of the PHACTboost_score over the total number of scores in dbNSFP. 123 MutFormer_score: "MutFormer is an application of the BERT (Bidirectional Encoder Representations from Transformers) NLP (Natural Language Processing) model with an added adaptive vocabulary to protein context, for the purpose of predicting the effect of missense mutations on protein function." The range of the score is from 0 to 1, the larger the score the more likely the variant is pathegenic. Details see https://doi.org/10.1016/j.xinn.2023.100487. The authors recommend to use 0.8838 as the cutoff for binary prediction (personal communication). 124 MutFormer_rankscore: MutFormer scores were ranked among all MutFormer scores in dbNSFP. The rankscore is the ratio of the rank of the MutFormer_score over the total number of scores in dbNSFP. 125 MutScore_score: MutScore is an ensemble score which integerate multiple unsupervised scores for DNA substitutions with additional positional clustering information. The range of the score is from 0 to 1, the larger the score the more likely the variant is pathegenic. Details see https://doi.org/10.1016/j.ajhg.2022.01.006. The authors recommend to use 0.5 as the cutoff for binary prediction (personal communication). 126 MutScore_rankscore: MutScore scores were ranked among all MutScore scores in dbNSFP. The rankscore is the ratio of the rank of the MutScore_score over the total number of scores in dbNSFP. 127 Aloft_Fraction_transcripts_affected: the fraction of the transcripts of the gene affected i.e. No. of transcripts affected by the SNP/Total no. of protein_coding transcripts for the gene multiple values separated by ";", corresponding to Ensembl_proteinid. 128 Aloft_prob_Tolerant: Probability of the SNP being classified as benign by ALoFT multiple values separated by ";", corresponding to Ensembl_proteinid. 129 Aloft_prob_Recessive: Probability of the SNP being classified as recessive disease-causing by ALoFT multiple values separated by ";", corresponding to Ensembl_proteinid. 130 Aloft_prob_Dominant: Probability of the SNP being classified as dominant disease-causing by ALoFT multiple values separated by ";", corresponding to Ensembl_proteinid. 131 Aloft_pred: final classification predicted by ALoFT; values can be Tolerant, Recessive or Dominant multiple values separated by ";", corresponding to Ensembl_proteinid. 132 Aloft_Confidence: Confidence level of Aloft_pred; values can be "High Confidence" (p < 0.05) or "Low Confidence" (p > 0.05) multiple values separated by ";", corresponding to Ensembl_proteinid. 133 CADD_raw: CADD raw score for functional prediction of a SNP. Please refer to Kircher et al. (2014) Nature Genetics 46(3):310-5 for details. The larger the score the more likely the SNP has damaging effect. Scores range from -28.377575 to 25.511592 in dbNSFP. Please note the following copyright statement for CADD: "CADD scores (http://cadd.gs.washington.edu/) are Copyright 2013 University of Washington and Hudson-Alpha Institute for Biotechnology (all rights reserved) but are freely available for all academic, non-commercial applications. For commercial licensing information contact Jennifer McCullar (mccullaj@uw.edu)." 134 CADD_raw_rankscore: CADD raw scores were ranked among all CADD raw scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of CADD raw scores in dbNSFP. Please note the following copyright statement for CADD: "CADD scores (http://cadd.gs.washington.edu/) are Copyright 2013 University of Washington and Hudson-Alpha Institute for Biotechnology (all rights reserved) but are freely available for all academic, non-commercial applications. For commercial licensing information contact Jennifer McCullar (mccullaj@uw.edu)." 135 CADD_phred: CADD phred-like score. This is phred-like rank score based on whole genome CADD raw scores. Please refer to Kircher et al. (2014) Nature Genetics 46(3):310-5 for details. The larger the score the more likely the SNP has damaging effect. Please note the following copyright statement for CADD: "CADD scores (http://cadd.gs.washington.edu/) are Copyright 2013 University of Washington and Hudson-Alpha Institute for Biotechnology (all rights reserved) but are freely available for all academic, non-commercial applications. For commercial licensing information contact Jennifer McCullar (mccullaj@uw.edu)." 136 DANN_score: DANN is a functional prediction score retrained based on the training data of CADD using deep neural network. Scores range from 0 to 1. A larger number indicate a higher probability to be damaging. More information of this score can be found in doi: 10.1093/bioinformatics/btu703. 137 DANN_rankscore: DANN scores were ranked among all DANN scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of DANN scores in dbNSFP. 138 fathmm-XF_coding_score: fathmm-XF p-values. Scores range from 0 to 1. SNVs with scores >0.5 are predicted to be deleterious, and those <0.5 are predicted to be neutral or benign. Scores close to 0 or 1 are with the highest-confidence. Coding scores are trained using 10 groups of features. More details of the score can be found in doi: 10.1093/bioinformatics/btx536. 139 fathmm-XF_coding_rankscore: fathmm-XF coding scores were ranked among all fathmm-XF coding scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of fathmm-XF coding scores in dbNSFP. 140 fathmm-XF_coding_pred: If a fathmm-XF_coding_score is >0.5, the corresponding nsSNV is predicted as "D(AMAGING)"; otherwise it is predicted as "N(EUTRAL)". 141 Eigen-raw_coding: Eigen score for coding SNVs. A functional prediction score based on conservation, allele frequencies, and deleteriousness prediction using an unsupervised learning method (doi: 10.1038/ng.3477). 142 Eigen-raw_coding_rankscore: Eigen-raw scores were ranked among all Eigen-raw scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of Eigen-raw scores in dbNSFP. 143 Eigen-phred_coding: Eigen score in phred scale. 144 Eigen-PC-raw_coding: Eigen PC score for genome-wide SNVs. A functional prediction score based on conservation, allele frequencies, deleteriousness prediction (for missense SNVs) and epigenomic signals (for synonymous and non-coding SNVs) using an unsupervised learning method (doi: 10.1038/ng.3477). 145 Eigen-PC-raw_coding_rankscore: Eigen-PC-raw scores were ranked among all Eigen-PC-raw scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of Eigen-PC-raw scores in dbNSFP. 146 Eigen-PC-phred_coding: Eigen PC score in phred scale. 147 GERP++_NR: GERP++ neutral rate 148 GERP++_RS: GERP++ RS score, the larger the score, the more conserved the site. Scores range from -12.3 to 6.17. 149 GERP++_RS_rankscore: GERP++ RS scores were ranked among all GERP++ RS scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of GERP++ RS scores in dbNSFP. 150 GERP_91_mammals: GERP conservation score calculated based on multiple sequence alignments of 91 mammals. 151 GERP_91_mammals_rankscore: GERP (91 mammals) scores were ranked among all GERP (91 mammals) scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of GERP_91_mammals scores in dbNSFP. 152 phyloP100way_vertebrate: phyloP (phylogenetic p-values) conservation score based on the multiple alignments of 100 vertebrate genomes (including human). The larger the score, the more conserved the site. Scores range from -20.0 to 10.003 in dbNSFP. 153 phyloP100way_vertebrate_rankscore: phyloP100way_vertebrate scores were ranked among all phyloP100way_vertebrate scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of phyloP100way_vertebrate scores in dbNSFP. 154 phyloP470way_mammalian: phyloP (phylogenetic p-values) conservation score based on the multiple alignments of 470 mammalian genomes (including human). The larger the score, the more conserved the site. Scores range from -20 to 11.936 in dbNSFP. 155 phyloP470way_mammalian_rankscore: phyloP470way_mammalian scores were ranked among all phyloP470way_mammalian scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of phyloP470way_mammalian scores in dbNSFP. 156 phyloP17way_primate: a conservation score based on 17way alignment primate set, the higher the more conservative. Scores range from -13.362 to 0.756 in dbNSFP. 157 phyloP17way_primate_rankscore: the rank of the phyloP17way_primate score among all phyloP17way_primate scores in dbNSFP. 158 phastCons100way_vertebrate: phastCons conservation score based on the multiple alignments of 100 vertebrate genomes (including human). The larger the score, the more conserved the site. Scores range from 0 to 1. 159 phastCons100way_vertebrate_rankscore: phastCons100way_vertebrate scores were ranked among all phastCons100way_vertebrate scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of phastCons100way_vertebrate scores in dbNSFP. 160 phastCons470way_mammalian: phastCons conservation score based on the multiple alignments of 470 mammalian genomes (including human). The larger the score, the more conserved the site. Scores range from 0 to 1. 161 phastCons470way_mammalian_rankscore: phastCons470way_mammalian scores were ranked among all phastCons470way_mammalian scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of phastCons470way_mammalian scores in dbNSFP. 162 phastCons17way_primate: a conservation score based on 17way alignment primate set, The larger the score, the more conserved the site. Scores range from 0 to 1. 163 phastCons17way_primate_rankscore: the rank of the phastCons17way_primate score among all phastCons17way_primate scores in dbNSFP. 164 bStatistic: Background selection (B) value estimates from doi.org/10.1371/journal.pgen.1000471. Ranges from 0 to 1000. It estimates the expected fraction (*1000) of neutral diversity present at a site. Values close to 0 represent near complete removal of diversity as a result of background selection and values near 1000 indicating absent of background selection. Data from CADD v1.4. 165 bStatistic_converted_rankscore: bStatistic scores were first converted to -bStatistic, then ranked among all -bStatistic scores in dbNSFP. The rankscore is the ratio of the rank of -bStatistic over the total number of -bStatistic scores in dbNSFP. 166 1000Gp3_AC: Alternative allele counts in the whole 1000 genomes phase 3 (1000Gp3) data. 167 1000Gp3_AF: Alternative allele frequency in the whole 1000Gp3 data. 168 1000Gp3_AFR_AC: Alternative allele counts in the 1000Gp3 African descendent samples. 169 1000Gp3_AFR_AF: Alternative allele frequency in the 1000Gp3 African descendent samples. 170 1000Gp3_EUR_AC: Alternative allele counts in the 1000Gp3 European descendent samples. 171 1000Gp3_EUR_AF: Alternative allele frequency in the 1000Gp3 European descendent samples. 172 1000Gp3_AMR_AC: Alternative allele counts in the 1000Gp3 American descendent samples. 173 1000Gp3_AMR_AF: Alternative allele frequency in the 1000Gp3 American descendent samples. 174 1000Gp3_EAS_AC: Alternative allele counts in the 1000Gp3 East Asian descendent samples. 175 1000Gp3_EAS_AF: Alternative allele frequency in the 1000Gp3 East Asian descendent samples. 176 1000Gp3_SAS_AC: Alternative allele counts in the 1000Gp3 South Asian descendent samples. 177 1000Gp3_SAS_AF: Alternative allele frequency in the 1000Gp3 South Asian descendent samples. 178 TOPMed_frz8_AC: Alternative allele counts in the TOPMed freeze 8 samples. 179 TOPMed_frz8_AN: Total allele count in the TOPMed freeze 8 samples. 180 TOPMed_frz8_AF: Alternative allele frequency in the TOPMed freeze 8 samples. 181 gnomAD2.1.1_exomes_flag: information from gnomAD exome data indicating whether the variant falling within low-complexity (lcr) or segmental duplication (segdup) or decoy regions. The flag can be either "." for high-quality PASS or not reported/polymorphic in gnomAD exomes, "lcr" for within lcr, "segdup" for within segdup, or "decoy" for with decoy region. 182 gnomAD2.1.1_exomes_controls_AC: Alternative allele count in the controls subset of whole gnomAD exome samples v2.1.1 183 gnomAD2.1.1_exomes_controls_AN: Total allele count in the controls subset of whole gnomAD exome samples v2.1.1 184 gnomAD2.1.1_exomes_controls_AF: Alternative allele frequency in the controls subset of whole gnomAD exome samples v2.1.1 185 gnomAD2.1.1_exomes_controls_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of whole gnomAD exome samples v2.1.1 186 gnomAD2.1.1_exomes_non_neuro_AC: Alternative allele count in the non-neuro subset of whole gnomAD exome samples v2.1.1 187 gnomAD2.1.1_exomes_non_neuro_AN: Total allele count in the non-neuro subset of whole gnomAD exome samples v2.1.1 188 gnomAD2.1.1_exomes_non_neuro_AF: Alternative allele frequency in the non-neuro subset of whole gnomAD exome samples v2.1.1 189 gnomAD2.1.1_exomes_non_neuro_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of whole gnomAD exome samples v2.1.1 190 gnomAD2.1.1_exomes_non_cancer_AC: Alternative allele count in the non-cancer subset of whole gnomAD exome samples v2.1.1 191 gnomAD2.1.1_exomes_non_cancer_AN: Total allele count in the non-cancer subset of whole gnomAD exome samples v2.1.1 192 gnomAD2.1.1_exomes_non_cancer_AF: Alternative allele frequency in the non-cancer subset of whole gnomAD exome samples v2.1.1 193 gnomAD2.1.1_exomes_non_cancer_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of whole gnomAD exome samples v2.1.1 194 gnomAD2.1.1_exomes_controls_AFR_AC: Alternative allele count in the controls subset of African/African American gnomAD exome samples v2.1.1 195 gnomAD2.1.1_exomes_controls_AFR_AN: Total allele count in the controls subset of African/African American gnomAD exome samples v2.1.1 196 gnomAD2.1.1_exomes_controls_AFR_AF: Alternative allele frequency in the controls subset of African/African American gnomAD exome samples v2.1.1 197 gnomAD2.1.1_exomes_controls_AFR_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of African/African American gnomAD exome samples v2.1.1 198 gnomAD2.1.1_exomes_controls_AMR_AC: Alternative allele count in the controls subset of Latino gnomAD exome samples v2.1.1 199 gnomAD2.1.1_exomes_controls_AMR_AN: Total allele count in the controls subset of Latino gnomAD exome samples v2.1.1 200 gnomAD2.1.1_exomes_controls_AMR_AF: Alternative allele frequency in the controls subset of Latino gnomAD exome samples v2.1.1 201 gnomAD2.1.1_exomes_controls_AMR_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of Latino gnomAD exome samples v2.1.1 202 gnomAD2.1.1_exomes_controls_ASJ_AC: Alternative allele count in the controls subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 203 gnomAD2.1.1_exomes_controls_ASJ_AN: Total allele count in the controls subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 204 gnomAD2.1.1_exomes_controls_ASJ_AF: Alternative allele frequency in the controls subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 205 gnomAD2.1.1_exomes_controls_ASJ_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 206 gnomAD2.1.1_exomes_controls_EAS_AC: Alternative allele count in the controls subset of East Asian gnomAD exome samples v2.1.1 207 gnomAD2.1.1_exomes_controls_EAS_AN: Total allele count in the controls subset of East Asian gnomAD exome samples v2.1.1 208 gnomAD2.1.1_exomes_controls_EAS_AF: Alternative allele frequency in the controls subset of East Asian gnomAD exome samples v2.1.1 209 gnomAD2.1.1_exomes_controls_EAS_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of East Asian gnomAD exome samples v2.1.1 210 gnomAD2.1.1_exomes_controls_FIN_AC: Alternative allele count in the controls subset of Finnish gnomAD exome samples v2.1.1 211 gnomAD2.1.1_exomes_controls_FIN_AN: Total allele count in the controls subset of Finnish gnomAD exome samples v2.1.1 212 gnomAD2.1.1_exomes_controls_FIN_AF: Alternative allele frequency in the controls subset of Finnish gnomAD exome samples v2.1.1 213 gnomAD2.1.1_exomes_controls_FIN_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of Finnish gnomAD exome samples v2.1.1 214 gnomAD2.1.1_exomes_controls_NFE_AC: Alternative allele count in the controls subset of Non-Finnish European gnomAD exome samples v2.1.1 215 gnomAD2.1.1_exomes_controls_NFE_AN: Total allele count in the controls subset of Non-Finnish European gnomAD exome samples v2.1.1 216 gnomAD2.1.1_exomes_controls_NFE_AF: Alternative allele frequency in the controls subset of Non-Finnish European gnomAD exome samples v2.1.1 217 gnomAD2.1.1_exomes_controls_NFE_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of Non-Finnish European gnomAD exome samples v2.1.1 218 gnomAD2.1.1_exomes_controls_SAS_AC: Alternative allele count in the controls subset of South Asian gnomAD exome samples v2.1.1 219 gnomAD2.1.1_exomes_controls_SAS_AN: Total allele count in the controls subset of South Asian gnomAD exome samples v2.1.1 220 gnomAD2.1.1_exomes_controls_SAS_AF: Alternative allele frequency in the controls subset of South Asian gnomAD exome samples v2.1.1 221 gnomAD2.1.1_exomes_controls_SAS_nhomalt: Count of individuals with homozygous alternative allele in the controls subset of South Asian gnomAD exome samples v2.1.1 222 gnomAD2.1.1_exomes_controls_POPMAX_AC: Allele count in the controls subset of population with the maximum AF 223 gnomAD2.1.1_exomes_controls_POPMAX_AN: Total number of alleles in the controls subset of population with the maximum AF 224 gnomAD2.1.1_exomes_controls_POPMAX_AF: Maximum allele frequency across populations (excluding samples of Ashkenazi, Finnish, and indeterminate ancestry) in the controls subset 225 gnomAD2.1.1_exomes_controls_POPMAX_nhomalt: Count of homozygous individuals in the controls subset of population with the maximum allele frequency 226 gnomAD2.1.1_exomes_non_neuro_AFR_AC: Alternative allele count in the non-neuro subset of African/African American gnomAD exome samples v2.1.1 227 gnomAD2.1.1_exomes_non_neuro_AFR_AN: Total allele count in the non-neuro subset of African/African American gnomAD exome samples v2.1.1 228 gnomAD2.1.1_exomes_non_neuro_AFR_AF: Alternative allele frequency in the non-neuro subset of African/African American gnomAD exome samples v2.1.1 229 gnomAD2.1.1_exomes_non_neuro_AFR_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of African/African American gnomAD exome samples v2.1.1 230 gnomAD2.1.1_exomes_non_neuro_AMR_AC: Alternative allele count in the non-neuro subset of Latino gnomAD exome samples v2.1.1 231 gnomAD2.1.1_exomes_non_neuro_AMR_AN: Total allele count in the non-neuro subset of Latino gnomAD exome samples v2.1.1 232 gnomAD2.1.1_exomes_non_neuro_AMR_AF: Alternative allele frequency in the non-neuro subset of Latino gnomAD exome samples v2.1.1 233 gnomAD2.1.1_exomes_non_neuro_AMR_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of Latino gnomAD exome samples v2.1.1 234 gnomAD2.1.1_exomes_non_neuro_ASJ_AC: Alternative allele count in the non-neuro subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 235 gnomAD2.1.1_exomes_non_neuro_ASJ_AN: Total allele count in the non-neuro subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 236 gnomAD2.1.1_exomes_non_neuro_ASJ_AF: Alternative allele frequency in the non-neuro subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 237 gnomAD2.1.1_exomes_non_neuro_ASJ_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 238 gnomAD2.1.1_exomes_non_neuro_EAS_AC: Alternative allele count in the non-neuro subset of East Asian gnomAD exome samples v2.1.1 239 gnomAD2.1.1_exomes_non_neuro_EAS_AN: Total allele count in the non-neuro subset of East Asian gnomAD exome samples v2.1.1 240 gnomAD2.1.1_exomes_non_neuro_EAS_AF: Alternative allele frequency in the non-neuro subset of East Asian gnomAD exome samples v2.1.1 241 gnomAD2.1.1_exomes_non_neuro_EAS_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of East Asian gnomAD exome samples v2.1.1 242 gnomAD2.1.1_exomes_non_neuro_FIN_AC: Alternative allele count in the non-neuro subset of Finnish gnomAD exome samples v2.1.1 243 gnomAD2.1.1_exomes_non_neuro_FIN_AN: Total allele count in the non-neuro subset of Finnish gnomAD exome samples v2.1.1 244 gnomAD2.1.1_exomes_non_neuro_FIN_AF: Alternative allele frequency in the non-neuro subset of Finnish gnomAD exome samples v2.1.1 245 gnomAD2.1.1_exomes_non_neuro_FIN_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of Finnish gnomAD exome samples v2.1.1 246 gnomAD2.1.1_exomes_non_neuro_NFE_AC: Alternative allele count in the non-neuro subset of Non-Finnish European gnomAD exome samples v2.1.1 247 gnomAD2.1.1_exomes_non_neuro_NFE_AN: Total allele count in the non-neuro subset of Non-Finnish European gnomAD exome samples v2.1.1 248 gnomAD2.1.1_exomes_non_neuro_NFE_AF: Alternative allele frequency in the non-neuro subset of Non-Finnish European gnomAD exome samples v2.1.1 249 gnomAD2.1.1_exomes_non_neuro_NFE_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of Non-Finnish European gnomAD exome samples v2.1.1 250 gnomAD2.1.1_exomes_non_neuro_SAS_AC: Alternative allele count in the non-neuro subset of South Asian gnomAD exome samples v2.1.1 251 gnomAD2.1.1_exomes_non_neuro_SAS_AN: Total allele count in the non-neuro subset of South Asian gnomAD exome samples v2.1.1 252 gnomAD2.1.1_exomes_non_neuro_SAS_AF: Alternative allele frequency in the non-neuro subset of South Asian gnomAD exome samples v2.1.1 253 gnomAD2.1.1_exomes_non_neuro_SAS_nhomalt: Count of individuals with homozygous alternative allele in the non-neuro subset of South Asian gnomAD exome samples v2.1.1 254 gnomAD2.1.1_exomes_non_neuro_POPMAX_AC: Allele count in the non-neuro subset of population with the maximum AF 255 gnomAD2.1.1_exomes_non_neuro_POPMAX_AN: Total number of alleles in the non-neuro subset of population with the maximum AF 256 gnomAD2.1.1_exomes_non_neuro_POPMAX_AF: Maximum allele frequency across populations (excluding samples of Ashkenazi, Finnish, and indeterminate ancestry) in the non-neuro subset 257 gnomAD2.1.1_exomes_non_neuro_POPMAX_nhomalt: Count of homozygous individuals in the non-neuro subset of population with the maximum allele frequency 258 gnomAD2.1.1_exomes_non_cancer_AFR_AC: Alternative allele count in the non-cancer subset of African/African American gnomAD exome samples v2.1.1 259 gnomAD2.1.1_exomes_non_cancer_AFR_AN: Total allele count in the non-cancer subset of African/African American gnomAD exome samples v2.1.1 260 gnomAD2.1.1_exomes_non_cancer_AFR_AF: Alternative allele frequency in the non-cancer subset of African/African American gnomAD exome samples v2.1.1 261 gnomAD2.1.1_exomes_non_cancer_AFR_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of African/African American gnomAD exome samples v2.1.1 262 gnomAD2.1.1_exomes_non_cancer_AMR_AC: Alternative allele count in the non-cancer subset of Latino gnomAD exome samples v2.1.1 263 gnomAD2.1.1_exomes_non_cancer_AMR_AN: Total allele count in the non-cancer subset of Latino gnomAD exome samples v2.1.1 264 gnomAD2.1.1_exomes_non_cancer_AMR_AF: Alternative allele frequency in the non-cancer subset of Latino gnomAD exome samples v2.1.1 265 gnomAD2.1.1_exomes_non_cancer_AMR_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of Latino gnomAD exome samples v2.1.1 266 gnomAD2.1.1_exomes_non_cancer_ASJ_AC: Alternative allele count in the non-cancer subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 267 gnomAD2.1.1_exomes_non_cancer_ASJ_AN: Total allele count in the non-cancer subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 268 gnomAD2.1.1_exomes_non_cancer_ASJ_AF: Alternative allele frequency in the non-cancer subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 269 gnomAD2.1.1_exomes_non_cancer_ASJ_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of Ashkenazi Jewish gnomAD exome samples v2.1.1 270 gnomAD2.1.1_exomes_non_cancer_EAS_AC: Alternative allele count in the non-cancer subset of East Asian gnomAD exome samples v2.1.1 271 gnomAD2.1.1_exomes_non_cancer_EAS_AN: Total allele count in the non-cancer subset of East Asian gnomAD exome samples v2.1.1 272 gnomAD2.1.1_exomes_non_cancer_EAS_AF: Alternative allele frequency in the non-cancer subset of East Asian gnomAD exome samples v2.1.1 273 gnomAD2.1.1_exomes_non_cancer_EAS_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of East Asian gnomAD exome samples v2.1.1 274 gnomAD2.1.1_exomes_non_cancer_FIN_AC: Alternative allele count in the non-cancer subset of Finnish gnomAD exome samples v2.1.1 275 gnomAD2.1.1_exomes_non_cancer_FIN_AN: Total allele count in the non-cancer subset of Finnish gnomAD exome samples v2.1.1 276 gnomAD2.1.1_exomes_non_cancer_FIN_AF: Alternative allele frequency in the non-cancer subset of Finnish gnomAD exome samples v2.1.1 277 gnomAD2.1.1_exomes_non_cancer_FIN_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of Finnish gnomAD exome samples v2.1.1 278 gnomAD2.1.1_exomes_non_cancer_NFE_AC: Alternative allele count in the non-cancer subset of Non-Finnish European gnomAD exome samples v2.1.1 279 gnomAD2.1.1_exomes_non_cancer_NFE_AN: Total allele count in the non-cancer subset of Non-Finnish European gnomAD exome samples v2.1.1 280 gnomAD2.1.1_exomes_non_cancer_NFE_AF: Alternative allele frequency in the non-cancer subset of Non-Finnish European gnomAD exome samples v2.1.1 281 gnomAD2.1.1_exomes_non_cancer_NFE_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of Non-Finnish European gnomAD exome samples v2.1.1 282 gnomAD2.1.1_exomes_non_cancer_SAS_AC: Alternative allele count in the non-cancer subset of South Asian gnomAD exome samples v2.1.1 283 gnomAD2.1.1_exomes_non_cancer_SAS_AN: Total allele count in the non-cancer subset of South Asian gnomAD exome samples v2.1.1 284 gnomAD2.1.1_exomes_non_cancer_SAS_AF: Alternative allele frequency in the non-cancer subset of South Asian gnomAD exome samples v2.1.1 285 gnomAD2.1.1_exomes_non_cancer_SAS_nhomalt: Count of individuals with homozygous alternative allele in the non-cancer subset of South Asian gnomAD exome samples v2.1.1 286 gnomAD2.1.1_exomes_non_cancer_POPMAX_AC: Allele count in the non-cancer subset of population with the maximum AF 287 gnomAD2.1.1_exomes_non_cancer_POPMAX_AN: Total number of alleles in the non-cancer subset of population with the maximum AF 288 gnomAD2.1.1_exomes_non_cancer_POPMAX_AF: Maximum allele frequency across populations (excluding samples of Ashkenazi, Finnish, and indeterminate ancestry) in the non-cancer subset 289 gnomAD2.1.1_exomes_non_cancer_POPMAX_nhomalt: Count of homozygous individuals in the non-cancer subset of population with the maximum allele frequency 290 gnomAD4.1_joint_flag: information from gnomAD joint (genome+exome) data indicating whether the variant falling within low-complexity (lcr) or segmental duplication (segdup) or decoy regions. The flag can be either "." for high-quality PASS or not reported/polymorphic in gnomAD exomes, "lcr" for within lcr, "segdup" for within segdup, or "decoy" for with decoy region. 291 gnomAD4.1_joint_AC: Alternative allele count in the whole gnomAD joint (genome+exome) samples v4.1 292 gnomAD4.1_joint_AN: Total allele count in the whole gnomAD joint (genome+exome) samples v4.1 293 gnomAD4.1_joint_AF: Alternative allele frequency in the whole gnomAD genome samples v4.1 294 gnomAD4.1_joint_nhomalt: Count of individuals with homozygous alternative allele in the whole gnomAD joint (genome+exome) samples v4.1 295 gnomAD4.1_joint_POPMAX_AC: Allele count in the population with the maximum AF 296 gnomAD4.1_joint_POPMAX_AN: Total number of alleles in the population with the maximum AF 297 gnomAD4.1_joint_POPMAX_AF: Maximum allele frequency across populations (excluding samples of Ashkenazi, Finnish, and indeterminate ancestry) 298 gnomAD4.1_joint_POPMAX_nhomalt: Count of homozygous individuals in the population with the maximum allele frequency 299 gnomAD4.1_joint_AFR_AC: Alternative allele count in the African/African American gnomAD joint (genome+exome) samples v4.1 300 gnomAD4.1_joint_AFR_AN: Total allele count in the African/African American gnomAD joint (genome+exome) samples v4.1 301 gnomAD4.1_joint_AFR_AF: Alternative allele frequency in the African/African American gnomAD joint (genome+exome) samples v4.1 302 gnomAD4.1_joint_AFR_nhomalt: Count of individuals with homozygous alternative allele in the African/African American gnomAD joint (genome+exome) samples v4.1 303 gnomAD4.1_joint_AMI_AC: Alternative allele count in the Amish gnomAD joint (genome+exome) samples v4.1 304 gnomAD4.1_joint_AMI_AN: Total allele count in the Amish gnomAD joint (genome+exome) samples v4.1 305 gnomAD4.1_joint_AMI_AF: Alternative allele frequency in the Amish gnomAD joint (genome+exome) samples v4.1 306 gnomAD4.1_joint_AMI_nhomalt: Count of individuals with homozygous alternative allele in the Amish gnomAD joint (genome+exome) samples v4.1 307 gnomAD4.1_joint_AMR_AC: Alternative allele count in the Latino gnomAD joint (genome+exome) samples v4.1 308 gnomAD4.1_joint_AMR_AN: Total allele count in the Latino gnomAD joint (genome+exome) samples v4.1 309 gnomAD4.1_joint_AMR_AF: Alternative allele frequency in the Latino gnomAD joint (genome+exome) samples v4.1 310 gnomAD4.1_joint_AMR_nhomalt: Count of individuals with homozygous alternative allele in the Latino gnomAD joint (genome+exome) samples v4.1 311 gnomAD4.1_joint_ASJ_AC: Alternative allele count in the Ashkenazi Jewish gnomAD joint (genome+exome) samples v4.1 312 gnomAD4.1_joint_ASJ_AN: Total allele count in the Ashkenazi Jewish gnomAD joint (genome+exome) samples v4.1 313 gnomAD4.1_joint_ASJ_AF: Alternative allele frequency in the Ashkenazi Jewish gnomAD joint (genome+exome) samples v4.1 314 gnomAD4.1_joint_ASJ_nhomalt: Count of individuals with homozygous alternative allele in the Ashkenazi Jewish gnomAD joint (genome+exome) samples v4.1 315 gnomAD4.1_joint_EAS_AC: Alternative allele count in the East Asian gnomAD joint (genome+exome) samples v4.1 316 gnomAD4.1_joint_EAS_AN: Total allele count in the East Asian gnomAD joint (genome+exome) samples v4.1 317 gnomAD4.1_joint_EAS_AF: Alternative allele frequency in the East Asian gnomAD joint (genome+exome) samples v4.1 318 gnomAD4.1_joint_EAS_nhomalt: Count of individuals with homozygous alternative allele in the East Asian gnomAD joint (genome+exome) samples v4.1 319 gnomAD4.1_joint_FIN_AC: Alternative allele count in the Finnish gnomAD joint (genome+exome) samples v4.1 320 gnomAD4.1_joint_FIN_AN: Total allele count in the Finnish gnomAD joint (genome+exome) samples v4.1 321 gnomAD4.1_joint_FIN_AF: Alternative allele frequency in the Finnish gnomAD joint (genome+exome) samples v4.1 322 gnomAD4.1_joint_FIN_nhomalt: Count of individuals with homozygous alternative allele in the Finnish gnomAD joint (genome+exome) samples v4.1 323 gnomAD4.1_joint_MID_AC: Alternative allele count in the Middle Eastern gnomAD joint (genome+exome) samples v4.1 324 gnomAD4.1_joint_MID_AN: Total allele count in the Middle Eastern gnomAD joint (genome+exome) samples v4.1 325 gnomAD4.1_joint_MID_AF: Alternative allele frequency in the Middle Eastern gnomAD joint (genome+exome) samples v4.1 326 gnomAD4.1_joint_MID_nhomalt: Count of individuals with homozygous alternative allele in the Middle Eastern gnomAD joint (genome+exome) samples v4.1 327 gnomAD4.1_joint_NFE_AC: Alternative allele count in the Non-Finnish European gnomAD joint (genome+exome) samples v4.1 328 gnomAD4.1_joint_NFE_AN: Total allele count in the Non-Finnish European gnomAD joint (genome+exome) samples v4.1 329 gnomAD4.1_joint_NFE_AF: Alternative allele frequency in the Non-Finnish European gnomAD joint (genome+exome) samples v4.1 330 gnomAD4.1_joint_NFE_nhomalt: Count of individuals with homozygous alternative allele in the Non-Finnish European gnomAD joint (genome+exome) samples v4.1 331 gnomAD4.1_joint_SAS_AC: Alternative allele count in the South Asian gnomAD joint (genome+exome) samples v4.1 332 gnomAD4.1_joint_SAS_AN: Total allele count in the South Asian gnomAD joint (genome+exome) samples v4.1 333 gnomAD4.1_joint_SAS_AF: Alternative allele frequency in the South Asian gnomAD joint (genome+exome) samples v4.1 334 gnomAD4.1_joint_SAS_nhomalt: Count of individuals with homozygous alternative allele in the South Asian gnomAD joint (genome+exome) samples v4.1 335 ALFA_European_AC: Alternative allele count of the European samples in the Allele Frequency Aggregator 336 ALFA_European_AN: Total allele count of the European samples in the Allele Frequency Aggregator 337 ALFA_European_AF: Alternative allele frequency of the European samples in the Allele Frequency Aggregator 338 ALFA_African_Others_AC: Alternative allele count of the individuals with African ancestry in the Allele Frequency Aggregator 339 ALFA_African_Others_AN: Total allele count of the individuals with African ancestry in the Allele Frequency Aggregator 340 ALFA_African_Others_AF: Alternative allele frequency of the individuals with African ancestry in the Allele Frequency Aggregator 341 ALFA_East_Asian_AC: Alternative allele count of the East Asian samples in the Allele Frequency Aggregator 342 ALFA_East_Asian_AN: Total allele count of the East Asian samples in the Allele Frequency Aggregator 343 ALFA_East_Asian_AF: Alternative allele frequency of the East Asian samples in the Allele Frequency Aggregator 344 ALFA_African_American_AC: Alternative allele count of the African American samples in the Allele Frequency Aggregator 345 ALFA_African_American_AN: Total allele count of the African American samples in the Allele Frequency Aggregator 346 ALFA_African_American_AF: Alternative allele frequency of the African American samples in the Allele Frequency Aggregator 347 ALFA_Latin_American_1_AC: Alternative allele count of the Latin American individiuals with Afro-Caribbean ancestry in the Allele Frequency Aggregator 348 ALFA_Latin_American_1_AN: Total allele count of the Latin American individiuals with Afro-Caribbean ancestry in the Allele Frequency Aggregator 349 ALFA_Latin_American_1_AF: Alternative allele frequency of the Latin American individiuals with Afro-Caribbean ancestry in the Allele Frequency Aggregator 350 ALFA_Latin_American_2_AC: Alternative allele count of the Latin American individiuals with mostly European and Native American Ancestry in the Allele Frequency Aggregator 351 ALFA_Latin_American_2_AN: Total allele count of the Latin American individiuals with mostly European and Native American Ancestry in the Allele Frequency Aggregator 352 ALFA_Latin_American_2_AF: Alternative allele frequency of the Latin American individiuals with mostly European and Native American Ancestry in the Allele Frequency Aggregator 353 ALFA_Other_Asian_AC: Alternative allele count of the Asian individiuals excluding South or East Asian in the Allele Frequency Aggregator 354 ALFA_Other_Asian_AN: Total allele count of the Asian individiuals excluding South or East Asian in the Allele Frequency Aggregator 355 ALFA_Other_Asian_AF: Alternative allele frequency of the Asian individiuals excluding South or East Asian in the Allele Frequency Aggregator 356 ALFA_South_Asian_AC: Alternative allele count of the South Asian samples in the Allele Frequency Aggregator 357 ALFA_South_Asian_AN: Total allele count of the South Asian samples in the Allele Frequency Aggregator 358 ALFA_South_Asian_AF: Alternative allele frequency of the South Asian samples in the Allele Frequency Aggregator 359 ALFA_Other_AC: Alternative allele count of the samples whose self-reported population is inconsistent with the GRAF-assigned population in the Allele Frequency Aggregator 360 ALFA_Other_AN: Total allele count of the samples whose self-reported population is inconsistent with the GRAF-assigned population in the Allele Frequency Aggregator 361 ALFA_Other_AF: Alternative allele frequency of the samples whose self-reported population is inconsistent with the GRAF-assigned population in the Allele Frequency Aggregator 362 ALFA_African_AC: Alternative allele count of the all African samples (African_Others and African_American) in the Allele Frequency Aggregator 363 ALFA_African_AN: Total allele count of the all African samples (African_Others and African_American) in the Allele Frequency Aggregator 364 ALFA_African_AF: Alternative allele frequency of the all African samples (African_Others and African_American) in the Allele Frequency Aggregator 365 ALFA_Asian_AC: Alternative allele count of the all Asian individuals (East_Asian and Other_Asian, excluding South_Asian) in the Allele Frequency Aggregator 366 ALFA_Asian_AN: Total allele count of the all Asian individuals (East_Asian and Other_Asian, excluding South_Asian) in the Allele Frequency Aggregator 367 ALFA_Asian_AF: Alternative allele frequency of the all Asian individuals (East_Asian and Other_Asian, excluding South_Asian) in the Allele Frequency Aggregator 368 ALFA_Total_AC: Alternative allele count of the total samples in the Allele Frequency Aggregator 369 ALFA_Total_AN: Total allele count of the total samples in the Allele Frequency Aggregator 370 ALFA_Total_AF: Alternative allele frequency of the total samples in the Allele Frequency Aggregator 371 clinvar_id: clinvar variation ID 372 clinvar_clnsig: clinical significance by clinvar Possible values: Benign, Likely_benign, Likely_pathogenic, Pathogenic, drug_response, histocompatibility. A negative score means the score is for the ref allele 373 clinvar_trait: the trait/disease the clinvar_clnsig referring to 374 clinvar_review: ClinVar Review Status summary Possible values: no assertion criteria provided, criteria provided, single submitter, criteria provided, multiple submitters, no conflicts, reviewed by expert panel, practice guideline 375 clinvar_hgvs: variant in HGVS format 376 clinvar_var_source: source of the variant 377 clinvar_MedGen_id: MedGen ID of the trait/disease the clinvar_trait referring to 378 clinvar_OMIM_id: OMIM ID of the trait/disease the clinvar_trait referring to 379 clinvar_Orphanet_id: Orphanet ID of the trait/disease the clinvar_trait referring to 380 Interpro_domain: domain or conserved site on which the variant locates. Domain annotations come from Interpro database. The number in the brackets following a specific domain is the count of times Interpro assigns the variant position to that domain, typically coming from different predicting databases. Multiple entries separated by ";". Note 1: Missing data is designated as '.'. Columns of dbNSFP_gene: Gene_name: Gene symbol from HGNC Ensembl_gene: Ensembl gene id (from HGNC) chr: Chromosome number (from HGNC) 381 Gene_old_names: Old gene symbol (from HGNC) 382 Gene_other_names: Other gene names (from HGNC) 383 Uniprot_acc(HGNC/Uniprot): Uniprot acc number (from HGNC and Uniprot) 384 Uniprot_id(HGNC/Uniprot): Uniprot id (from HGNC and Uniprot) 385 Entrez_gene_id: Entrez gene id (from HGNC) 386 CCDS_id: CCDS id (from HGNC) 387 Refseq_id: Refseq gene id (from HGNC) 388 ucsc_id: UCSC gene id (from HGNC) 389 MIM_id: MIM gene id (from HGNC) 390 OMIM_id: MIM gene id from OMIM 391 Gene_full_name: Gene full name (from HGNC) 392 Pathway(Uniprot): Pathway description from Uniprot 393 Pathway(BioCarta)_short: Short name of the Pathway(s) the gene belongs to (from BioCarta) 394 Pathway(BioCarta)_full: Full name(s) of the Pathway(s) the gene belongs to (from BioCarta) 395 Pathway(ConsensusPathDB): Pathway(s) the gene belongs to (from ConsensusPathDB) 396 Pathway(KEGG)_id: ID(s) of the Pathway(s) the gene belongs to (from KEGG) 397 Pathway(KEGG)_full: Full name(s) of the Pathway(s) the gene belongs to (from KEGG) 398 Function_description: Function description of the gene (from Uniprot) 399 Disease_description: Disease(s) the gene caused or associated with (from Uniprot) 400 MIM_phenotype_id: MIM id(s) of the phenotype the gene caused or associated with (from Uniprot) 401 MIM_disease: MIM disease name(s) with MIM id(s) in "[]" (from Uniprot) 402 Orphanet_disorder_id: Orphanet Number of the disorder the gene caused or associated with 403 Orphanet_disorder: Disorder name from Orphanet 404 Orphanet_association_type: the type of association beteen the gene and the disorder 405 Trait_association(GWAS): Trait(s) the gene associated with (from GWAS catalog) 406 MGI_mouse_gene: Homolog mouse gene name from MGI 407 MGI_mouse_phenotype: Phenotype description for the homolog mouse gene from MGI 408 ZFIN_zebrafish_gene: Homolog zebrafish gene name from ZFIN 409 ZFIN_zebrafish_structure: Affected structure of the homolog zebrafish gene from ZFIN 410 ZFIN_zebrafish_phenotype_quality: Phenotype description for the homolog zebrafish gene from ZFIN 411 ZFIN_zebrafish_phenotype_tag: Phenotype tag for the homolog zebrafish gene from ZFIN 412 HPO_id: ID of the mapped Human Phenotype Ontology. Multiple IDs are separated by ";" 413 HPO_name: Name of the mapped Human Phenotype Ontology. Multiple names are separated by ";" 414 GO_biological_process: GO terms for biological process 415 GO_cellular_component: GO terms for cellular component 416 GO_molecular_function: GO terms for molecular function 417 P(HI): Estimated probability of haploinsufficiency of the gene (from doi:10.1371/journal.pgen.1001154) 418 HIPred_score: Estimated probability of haploinsufficiency of the gene (from doi:10.1093/bioinformatics/btx028) 419 HIPred: HIPred prediction of haploinsufficiency of the gene. Y(es) or N(o). (from doi:10.1093/bioinformatics/btx028) 420 GHIS: A score predicting the gene haploinsufficiency. The higher the score the more likely the gene is haploinsufficient. (from doi: 10.1093/nar/gkv474) 421 ClinGen_Haploinsufficiency_Score: Haploinsufficiency score from ClinGen 422 ClinGen_Haploinsufficiency_Description: description of haploinsufficiency from ClinGen 423 ClinGen_Haploinsufficiency_PMID: PMIDs describing the haploinsufficiency from ClinGen 424 ClinGen_Haploinsufficiency_Disease: diseases associated with the haploinsufficiency from ClinGen 425 P(rec): Estimated probability that gene is a recessive disease gene (from DOI:10.1126/science.1215040) 426 Known_rec_info: Known recessive status of the gene (from DOI:10.1126/science.1215040) "lof-tolerant = seen in homozygous state in at least one 1000G individual" "recessive = known OMIM recessive disease" (original annotations from DOI:10.1126/science.1215040) 427 RVIS_EVS: Residual Variation Intolerance Score, a measure of intolerance of mutational burden, the higher the score the more tolerant to mutational burden the gene is. Based on EVS (ESP6500) data. from doi:10.1371/journal.pgen.1003709 428 RVIS_percentile_EVS: The percentile rank of the gene based on RVIS, the higher the percentile the more tolerant to mutational burden the gene is. Based on EVS (ESP6500) data. 429 LoF-FDR_ExAC: "A gene's corresponding FDR p-value for preferential LoF depletion among the ExAC population. Lower FDR corresponds with genes that are increasingly depleted of LoF variants." cited from RVIS document. 430 RVIS_ExAC: "ExAC-based RVIS; setting 'common' MAF filter at 0.05% in at least one of the six individual ethnic strata from ExAC." cited from RVIS document. 431 RVIS_percentile_ExAC: "Genome-Wide percentile for the new ExAC-based RVIS; setting 'common' MAF filter at 0.05% in at least one of the six individual ethnic strata from ExAC." cited from RVIS document. 432 ExAC_pLI: "the probability of being loss-of-function intolerant (intolerant of both heterozygous and homozygous lof variants)" based on ExAC r0.3 data 433 ExAC_pRec: "the probability of being intolerant of homozygous, but not heterozygous lof variants" based on ExAC r0.3 data 434 ExAC_pNull: "the probability of being tolerant of both heterozygous and homozygous lof variants" based on ExAC r0.3 data 435 ExAC_nonTCGA_pLI: "the probability of being loss-of-function intolerant (intolerant of both heterozygous and homozygous lof variants)" based on ExAC r0.3 nonTCGA subset 436 ExAC_nonTCGA_pRec: "the probability of being intolerant of homozygous, but not heterozygous lof variants" based on ExAC r0.3 nonTCGA subset 437 ExAC_nonTCGA_pNull: "the probability of being tolerant of both heterozygous and homozygous lof variants" based on ExAC r0.3 nonTCGA subset 438 ExAC_nonpsych_pLI: "the probability of being loss-of-function intolerant (intolerant of both heterozygous and homozygous lof variants)" based on ExAC r0.3 nonpsych subset 439 ExAC_nonpsych_pRec: "the probability of being intolerant of homozygous, but not heterozygous lof variants" based on ExAC r0.3 nonpsych subset 440 ExAC_nonpsych_pNull: "the probability of being tolerant of both heterozygous and homozygous lof variants" based on ExAC r0.3 nonpsych subset 441 gnomAD_pLI: "the probability of being loss-of-function intolerant (intolerant of both heterozygous and homozygous lof variants)" based on gnomAD 2.1 data 442 gnomAD_pRec: "the probability of being intolerant of homozygous, but not heterozygous lof variants" based on gnomAD 2.1 data 443 gnomAD_pNull: "the probability of being tolerant of both heterozygous and homozygous lof variants" based on gnomAD 2.1 data 444 ExAC_del.score: "Winsorised deletion intolerance z-score" based on ExAC r0.3.1 CNV data 445 ExAC_dup.score: "Winsorised duplication intolerance z-score" based on ExAC r0.3.1 CNV data 446 ExAC_cnv.score: "Winsorised cnv intolerance z-score" based on ExAC r0.3.1 CNV data 447 ExAC_cnv_flag: "Gene is in a known region of recurrent CNVs mediated by tandem segmental duplications and intolerance scores are more likely to be biased or noisy." from ExAC r0.3.1 CNV release 448 GDI: gene damage index score, "a genome-wide, gene-level metric of the mutational damage that has accumulated in the general population" from doi: 10.1073/pnas.1518646112. The higher the score the less likely the gene is to be responsible for monogenic diseases. 449 GDI-Phred: Phred-scaled GDI scores 450 Gene damage prediction (all disease-causing genes): gene damage prediction (low/medium/high) by GDI for all diseases 451 Gene damage prediction (all Mendelian disease-causing genes): gene damage prediction (low/medium/high) by GDI for all Mendelian diseases 452 Gene damage prediction (Mendelian AD disease-causing genes): gene damage prediction (low/medium/high) by GDI for Mendelian autosomal dominant diseases 453 Gene damage prediction (Mendelian AR disease-causing genes): gene damage prediction (low/medium/high) by GDI for Mendelian autosomal recessive diseases 454 Gene damage prediction (all PID disease-causing genes): gene damage prediction (low/medium/high) by GDI for all primary immunodeficiency diseases 455 Gene damage prediction (PID AD disease-causing genes): gene damage prediction (low/medium/high) by GDI for primary immunodeficiency autosomal dominant diseases 456 Gene damage prediction (PID AR disease-causing genes): gene damage prediction (low/medium/high) by GDI for primary immunodeficiency autosomal recessive diseases 457 Gene damage prediction (all cancer disease-causing genes): gene damage prediction (low/medium/high) by GDI for all cancer disease 458 Gene damage prediction (cancer recessive disease-causing genes): gene damage prediction (low/medium/high) by GDI for cancer recessive disease 459 Gene damage prediction (cancer dominant disease-causing genes): gene damage prediction (low/medium/high) by GDI for cancer dominant disease 460 LoFtool_score: a percentile score for gene intolerance to functional change. The lower the score the higher gene intolerance to functional change. For details see doi: 10.1093/bioinformatics/btv602. 461 Essential_gene: Essential ("E") or Non-essential phenotype-changing ("N") based on Mouse Genome Informatics database. from doi:10.1371/journal.pgen.1003484 462 Essential_gene_CRISPR: Essential ("E") or Non-essential phenotype-changing ("N") based on large scale CRISPR experiments. from doi: 10.1126/science.aac7041 463 Essential_gene_CRISPR2: Essential ("E"), context-Specific essential ("S"), or Non-essential phenotype-changing ("N") based on large scale CRISPR experiments. from http://dx.doi.org/10.1016/j.cell.2015.11.015 464 Essential_gene_gene-trap: Essential ("E"), HAP1-Specific essential ("H"), KBM7-Specific essential ("K"), or Non-essential phenotype-changing ("N"), based on large scale mutagenesis experiments. from doi: 10.1126/science.aac7557 465 Gene_indispensability_score: A probability prediction of the gene being essential. From doi:10.1371/journal.pcbi.1002886 466 Gene_indispensability_pred: Essential ("E") or loss-of-function tolerant ("N") based on Gene_indispensability_score. 467 Tissue_specificity(Uniprot): Tissue specificity description from Uniprot 468 HPA_consensus_adipose_tissue: The consensus nTPM value for the gene in tissue type adipose_tissue, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 469 HPA_consensus_adrenal_gland: The consensus nTPM value for the gene in tissue type adrenal_gland, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 470 HPA_consensus_amygdala: The consensus nTPM value for the gene in tissue type amygdala, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 471 HPA_consensus_appendix: The consensus nTPM value for the gene in tissue type appendix, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 472 HPA_consensus_basal_ganglia: The consensus nTPM value for the gene in tissue type basal_ganglia, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 473 HPA_consensus_bone_marrow: The consensus nTPM value for the gene in tissue type bone_marrow, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 474 HPA_consensus_breast: The consensus nTPM value for the gene in tissue type breast, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 475 HPA_consensus_cerebellum: The consensus nTPM value for the gene in tissue type cerebellum, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 476 HPA_consensus_cerebral_cortex: The consensus nTPM value for the gene in tissue type cerebral_cortex, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 477 HPA_consensus_cervix: The consensus nTPM value for the gene in tissue type cervix, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 478 HPA_consensus_choroid_plexus: The consensus nTPM value for the gene in tissue type choroid_plexus, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 479 HPA_consensus_colon: The consensus nTPM value for the gene in tissue type colon, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 480 HPA_consensus_duodenum: The consensus nTPM value for the gene in tissue type duodenum, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 481 HPA_consensus_endometrium: The consensus nTPM value for the gene in tissue type endometrium, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 482 HPA_consensus_epididymis: The consensus nTPM value for the gene in tissue type epididymis, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 483 HPA_consensus_esophagus: The consensus nTPM value for the gene in tissue type esophagus, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 484 HPA_consensus_fallopian_tube: The consensus nTPM value for the gene in tissue type fallopian_tube, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 485 HPA_consensus_gallbladder: The consensus nTPM value for the gene in tissue type gallbladder, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 486 HPA_consensus_heart_muscle: The consensus nTPM value for the gene in tissue type heart_muscle, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 487 HPA_consensus_hippocampal_formation: The consensus nTPM value for the gene in tissue type hippocampal_formation, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 488 HPA_consensus_hypothalamus: The consensus nTPM value for the gene in tissue type hypothalamus, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 489 HPA_consensus_kidney: The consensus nTPM value for the gene in tissue type kidney, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 490 HPA_consensus_liver: The consensus nTPM value for the gene in tissue type liver, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 491 HPA_consensus_lung: The consensus nTPM value for the gene in tissue type lung, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 492 HPA_consensus_lymph_node: The consensus nTPM value for the gene in tissue type lymph_node, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 493 HPA_consensus_midbrain: The consensus nTPM value for the gene in tissue type midbrain, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 494 HPA_consensus_ovary: The consensus nTPM value for the gene in tissue type ovary, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 495 HPA_consensus_pancreas: The consensus nTPM value for the gene in tissue type pancreas, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 496 HPA_consensus_parathyroid_gland: The consensus nTPM value for the gene in tissue type parathyroid_gland, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 497 HPA_consensus_pituitary_gland: The consensus nTPM value for the gene in tissue type pituitary_gland, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 498 HPA_consensus_placenta: The consensus nTPM value for the gene in tissue type placenta, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 499 HPA_consensus_prostate: The consensus nTPM value for the gene in tissue type prostate, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 500 HPA_consensus_rectum: The consensus nTPM value for the gene in tissue type rectum, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 501 HPA_consensus_retina: The consensus nTPM value for the gene in tissue type retina, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 502 HPA_consensus_salivary_gland: The consensus nTPM value for the gene in tissue type salivary_gland, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 503 HPA_consensus_seminal_vesicle: The consensus nTPM value for the gene in tissue type seminal_vesicle, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 504 HPA_consensus_skeletal_muscle: The consensus nTPM value for the gene in tissue type skeletal_muscle, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 505 HPA_consensus_skin: The consensus nTPM value for the gene in tissue type skin, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 506 HPA_consensus_small_intestine: The consensus nTPM value for the gene in tissue type small_intestine, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 507 HPA_consensus_smooth_muscle: The consensus nTPM value for the gene in tissue type smooth_muscle, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 508 HPA_consensus_spinal_cord: The consensus nTPM value for the gene in tissue type spinal_cord, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 509 HPA_consensus_spleen: The consensus nTPM value for the gene in tissue type spleen, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 510 HPA_consensus_stomach: The consensus nTPM value for the gene in tissue type stomach, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 511 HPA_consensus_testis: The consensus nTPM value for the gene in tissue type testis, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 512 HPA_consensus_thymus: The consensus nTPM value for the gene in tissue type thymus, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 513 HPA_consensus_thyroid_gland: The consensus nTPM value for the gene in tissue type thyroid_gland, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 514 HPA_consensus_tongue: The consensus nTPM value for the gene in tissue type tongue, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 515 HPA_consensus_tonsil: The consensus nTPM value for the gene in tissue type tonsil, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 516 HPA_consensus_urinary_bladder: The consensus nTPM value for the gene in tissue type urinary_bladder, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 517 HPA_consensus_vagina: The consensus nTPM value for the gene in tissue type vagina, represents the maximum nTPM value based on the Human Protein Atlas HPA and GTEx. 518 HPA_consensus_highly_expressed: The tissue type the gene is highly_expressed, which is identified as outliers > Q3 + 1.5 * IQR based on the box plot of the gene's nTPM values in all tissues. Columns of dbscSNV1.1: chr: chromosome number pos: physical position on the chromosome as to hg19 (1-based coordinate) ref: reference nucleotide allele (as on the + strand) alt: alternative nucleotide allele (as on the + strand) hg38_chr: chromosome number as to hg38 hg38_pos: physical position on the chromosome as to hg38 (1-based coordinate) RefSeq?: whether the SNV is a scSNV according to RefSeq Ensembl?: whether the SNV is a scSNV according to Ensembl RefSeq_region: functional region the SNV located according to RefSeq RefSeq_gene: gene name according to RefSeq RefSeq_functional_consequence: functional consequence of the SNV according to RefSeq RefSeq_id_c.change_p.change: SNV in format of c.change and p.change according to RefSeq Ensembl_region: functional region the SNV located according to Ensembl Ensembl_gene: gene id according to Ensembl Ensembl_functional_consequence: functional consequence of the SNV according to Ensembl Ensembl_id_c.change_p.change: SNV in format of c.change and p.change according to Ensembl ada_score: ensemble prediction score based on ada-boost. Ranges 0 to 1. The larger the score the higher probability the scSNV will affect splicing. The suggested cutoff for a binary prediction (affecting splicing vs. not affecting splicing) is 0.6. rf_score: ensemble prediction score based on random forests. Ranges 0 to 1. The larger the score the higher probability the scSNV will affect splicing. The suggested cutoff for a binary prediction (affecting splicing vs. not affecting splicing) is 0.6. Note 1: Missing data is designated as '.'. Note 2: Multiple annotations are separated by ';' Please cite: Liu X, Jian X, and Boerwinkle E. 2011. dbNSFP: a lightweight database of human non-synonymous SNPs and their functional predictions. Human Mutation. 32:894-899. Liu X, Li C, Mou C, Dong Y, and Tu Y. 2020. dbNSFP v4: a comprehensive database of transcript-specific functional predictions and annotations for human nonsynonymous and splice-site SNVs. Genome Medicine. 12:103. Contact: Xiaoming Liu, Ph.D. Associate Professor, USF Genomics, College of Public Health, University of South Florida Email: xmliu.uth{at}gmail.com Changelog: February 23, 2011: dbNSFP and search_dbNSFP v0.9 released. April 4, 2011: A bug related to the prediction scores of MutationTaster is fixed. dbNSFP v1.0 released. A change to the chromosome search order of the search_dbNSFP. A readme file added. search_dbNSFP v1.0 released. May 30, 2011: dbNSFP and search_dbNSFP v1.1 released. Version 1.1 added the following entries: rs numbers from UniSNP (a cleaned version of dbSNP build 129), allele frequency recorded in dbSNP, allele frequency reported by 1000 Genomes Project, alternative gene names, descriptive gene name, database cross references (gene IDs of HGNC, MIM, Ensembl and HPRD). The unziped database is 18Gb. May 31, 2011: dbNSFP_light and search_dbNSFP_light v1.0 released. dbNSFP_light v1.0 is a light version of dbNSFP, which contains less annotation entries but some additional 9,285,316 NSs that are not in CCDS version 20090327. Scores of PhyloP, SIFT, Polyphen2, LRT and MutationTaster are included but missing data are not imputed. Prediction of LRT and MutationTaster are also included, as well as the omega estimated by LRT. The unziped database is 6Gb. October 24, 2011: dbNSFP_light v1.1 and search_dbNSFP_light v1.1 released. dbNSFP v1.2 and search_dbNSFP v1.2 released. The new versions added GERP++ neutral rates and RS scores. October 25, 2011: dbNSFP v1.3 released. It added Uniprot ID, accession number and amino acid position based on Polyphen-2 annotation. Users now can search amino acid change directly referring to a Uniprot ID or accession number. November 3, 2011: dbNSFP_light v1.2 released. It added Uniprot ID, accession number and amino acid position based on Polyphen-2 annotation. Users now can search amino acid change directly referring to a Uniprot ID or accession number. November 10, 2011: A bug fixed in the companion search program for dbNSFP v1.3, which causes invalid search using AA mutations with Uniprot ID or accession number. December 16, 2011: dbNSFP_light v1.3 released. It updated SIFT scores (August, 2011 version) and Polyphen-2 scores (May, 2011 version). Uniprot ID, accession number and amino acid position based on the Polyphen-2 annotations have been updated too. April 11, 2012: dbNSFP2.0b1_variant released. This is beta test version of the variant sub-database of dbNSFP v2.0, which is rebuilt based on Gencode release 9 / Ensembl version 64. June 2, 2012: dbNSFP v2.0b2 released. It includes both the dbNSFP_variant and dbNSFP_gene sub-databases. Slight changes have been made to the Ensembl gene and transcript ids of dbNSFP_variant in order to be compatible to other database sources. July 2, 2012: dbNSFP v2.0b3 released. An additional 2.2 million splicing site SNPs have been added to dbNSFP_variant. In the table those SNPs have missing (".") in aaref, aaalt and "-1" in aapos. There's no change to the format of search input file. August 28, 2012: The companion java search program search_dbNSFP20b3 is updated. Added features include supporting vcf file as input file and options for output contents (columns). October 27, 2012: dbNSFP v2.0b4 is released. A new functional prediction score MutationAssessor is added (I thank Mr. Yevgeniy Antipin for his recommendation). Allele frequencies from ESP 5400 data set are replaced by ESP 6500 data set. February 25, 2013: dbNSFP v2.0 is released. A new functional prediction score FATHMM is added. March 22, 2013: A bug which caused a lot of missing FATHMM scores has been fixed. May 31, 2013: The source code of the companion Java search program is now available under the RECEX SHARED SOURCE LICENSE. October 3, 2013: dbNSFP v2.1 is released. MutationTaster and FATHMM scores have been updated. Converted scores of SIFT, LRT, MutationTaster, MutationAssessor and FATHMM have been added. Columns of SIFT and FATHMM predictions have been added. The gene database has also been updated. Database IDs are updated. GO Slim terms, pathway and protein interaction information from the ConsensusPathDB, and list of essential and non-essential genes (based on phenotypes of mouse homologs) have been added. January 23, 2014: dbNSFP v2.2 is released. SIFT and FATHMM now have multiple scores corresponding to different Ensembl ENSP ids and amino acid positions (aapos_SIFT and aapos_FATHMM). Accordingly, our companion search program now supports SNP searches based on Ensembl ENSP ids and amino acid positions. A bug is fixed for a small proportion of MutationTaster scores. January 26, 2014: dbNSFP v2.3 is released. Two ensemble scores (RadialSVM and LR) and their predictions have been added. February 12, 2014: A bug was fixed in dbNSFP v2.2 and v2.3, which caused missing delimiters in columns aapos_SIFT, SIFT_score_converted and SIFT_pred. (I thank Mr. Yevgeniy Antipin for his reminder). March 5, 2014: dbNSFP v2.4 is released. A whole genome functional prediction score called CADD was added, along with five more conservation scores (phyloP46way_primate, phyloP100way_vertebrate, phastCons46way_primate, phastCons46way_placental, phastCons100way_vertebarate). To facilitate comparison between scores, we added rank scores for most functional prediction scores and conservation scores, and replacing the "converted" scores in the previous versions. June 1, 2014: dbNSFP v2.5 is released. A new functional score VEST 3.0 has been added. We thank Dr. Karchin for kindly providing the score. A bug that causes the MutationTaster score error since v2.1 for variants with a prediction of "Polymorphism_automatic" has been fixed. We thank John McGuigan and James Ireland for reporting this bug. As MutationTaster can also predict splicing change and other functional effects, in case a variant has multiple predictions based on their different model, we took the most damaging score and prediction for dbNSFP. July 26, 2014: dbNSFP v2.6 is released. rs numbers from dbSNP 141 have been added to the variant database files. Mouse and zebra fish homolog genes and phenotypes have been added to the gene database file (I thank Alex Li for his suggestion and helps). Trait_association(GWAS) was also updated. An attached database called dbscSNV is available for download. It includes all potential human SNVs within splicing consensus regions (−3 to +8 at the 5’ splice site and −12 to +2 at the 3’ splice site), i.e. scSNVs, related functional annotations and two ensemble prediction scores for predicting their potential of altering splicing. A manuscript describing those scores have been submitted. search_dbNSFP26 now supports searching dbNSFP along with dbscSNV using option "-s". September 12, 2014: dbNSFP v2.7 is released. Chromosomes and positions of human reference hg38 have been added. search_ dbNSFP27.class now supports query dbNSFP using the positions based on hg38 with the "-v hg38" option. clinvar (freeze 20140902) annotations have been added. Allele frequencies from 2303 exomes of African Americans and 3203 exomes of European Americans from the Atherosclerosis Risk in Communities Study (ARIC) cohort study have been added. As the columns for gene interactions in dbNSFP_gene table contain very long strings, especially for gene UBC, which may cause problems when viewing the results in Excel, now we only report the number of interacting genes in those columns. Full information is retained in the dbNSFP_gene.complete table. November 21, 2014: dbNSFP v2.8 is released. COSMIC (Catalogue Of Somatic Mutations In Cancer) annotation have been added. Pathway information from BioCarta and KEGG (old version) has been added to the dbNSFP2.8_gene. A bug causing inconsistency between MutationTaster scores and MutationTaster_pred, which affects v2.5 to v2.7, has been fixed. I thank Adam Novak for reporting this bug. February 3, 2015: dbNSFP v2.9 is released. SIFT score has been updated to ensembl66 version. PROVEAN score (Protein Variation Effect Analyzer) v1.1 has been added. I thank Yongwook Choi from jcvi for providing the SIFT and PROVEAN scores. CADD score has been updated to 1.3 version. Please note the following copyright statement for CADD: "CADD scores (http://cadd.gs.washington.edu/) are Copyright 2013 University of Washington and Hudson-Alpha Institute for Biotechnology (all rights reserved) but are freely available for all academic, non-commercial applications. For commercial licensing information contact Jennifer McCullar (mccullaj@uw.edu)." Allele frequency v0.3 of ~60,706 unrelated individuals from The Exome Aggregation Consortium (ExAC) has been added. ExAC data are released under a Fort Lauderdale Agreement. Please refer to http://exac.broadinstitute.org/terms for terms of use. I also want to thank Dr. CS (Jonathan) Liu from Softgenetics for providing hosting space. April 6, 2015: dbNSFP v3.0b1 is released. The core set of nsSNVs and ssSNVs has been rebuilt based on Gencode 22/ Ensembl 79 with human reference sequence hg38. Putative genes have been included. Genes with incomplete 5' have been excluded (I thank Chris Gillies for reporting the issues for genes with incomplete 5' end.) Genes on mitochondrial DNA have been included. Allele frequencies from the UK10K cohorts and genotypes of two Neanderthals have been added. Some resources have been updated, including the MutationTaster (I thank Dr. Dominik Seelow for kindly providing the scores), allele frequencies from the 1000 Genomes Project populations, ancestral alleles, dbSNP, ClinVar and InterPro. The presentation of the prediction scores has been improved by adding columns for the corresponding transcript/protein ids. PhyloP and PhastCons conservation scores based on hg19 have been replaced by the scores based on hg38. Some resources have been dropped due to various reasons, including SLR test statistic, UniSNP ids, allele frequencies from the ARIC cohorts and allele counts in COSMIC. dbNSFP_gene has also been completely rebuilt using the up-to-date resources. Residual Variation Intolerance Scores (RVIS) have been added. GO Slim terms have been replaced by full GO terms. Two branches of dbNSFP are now provided: dbNSFP3.0b1a suitable for academic use, which includes all the resources, and dbNSFP3.0b1c suitable for commercial use, which does not include VEST3 and CADD. April 12, 2015: dbNSFP v3.0b2 is released. This update fixed the issues due to inconsistent mitochondrial reference sequences used by different resources. I thank Dr. Lishuang Shen at MEEI for helping solving the issues. For mitochondrial SNV, the pos (i.e. hg38) refers to the rCRS (GenBank: NC_012920) and hg19_pos refers to a YRI sequence (GenBank: AF347015). The ancestral allele of mitochondrial SNV now comes from the Reconstructed Sapiens Reference Sequence (RSRS, doi:10.1016/j.ajhg.2012.03.002). The affected content include ancestral alleles, Neanderthal/Denisova genotypes and MutationTaster columns of the chrM file. The rankscores of MutationTaster has also been updated to reflect the update of its chrM scores. dbscSNV has been updated to v1.1 and added hg38 positions liftovered from its hg19 positions. Using search_dbNSFP30b2a or search_dbNSFP30b2c you can search dbscSNV1.1 along with dbNSFP v3.0b2 with either hg19 coordinates or hg38 coordinates. August 3, 2015: dbNSFP v3.0 is released. Three new functional prediction scores (DANN, fathmm-MKL and fitCons) and two conservation scores (phyloP20way_mammalian and phastCons20way_mammalian) have been added to dbNSFP v3.0a. All five scores except DANN are also included in bNSFP v3.0c. For commercial application of DANN, please contact Daniel Quang (dxquang@uci.edu). CADD scores have been updated to v1.3. I thank Dr. Xueqiu Jian and Kirill Prusov for suggestions on README files. dbNSFP v3.0 will be integrated into our new whole genome annotation pipeline WGSA version 0.6. Please join our Email group for news and updates from dbNSFP. Columns updated: CADD_raw (dbNSFP v3.0a only), CADD_raw_rankscore (dbNSFP v3.0a only), CADD_phred (dbNSFP v3.0a only). New columns: DANN_score (dbNSFP v3.0a only), DANN_rankscore (dbNSFP v3.0a only), fathmm-MKL_coding_score, fathmm-MKL_coding_rankscore, fathmm-MKL_coding_pred, fathmm-MKL_coding_group, integrated_fitCons_score, integrated_fitCons_rankscore, integrated_confidence_value, GM12878_fitCons_score, GM12878_fitCons_rankscore, GM12878_confidence_value, H1-hESC_fitCons_score, H1-hESC_fitCons_rankscore, H1-hESC_confidence_value, HUVEC_fitCons_score, HUVEC_fitCons_rankscore, HUVEC_confidence_value. November 24, 2015: dbNSFP v3.1 is released. Significant eQTLs from GTEx V6 has been added. dbSNP rs has been updated to build 144. Gene expression information (rpkm of RNAseq) of 53 tissues from GTEx V6 has been added to dbNSFP_gene. Three gene intolerance scores (RVIS based on ExAC r0.3, GDI and LoFtool) has been added to dbNSFP_gene. March 20, 2016: dbNSFP v3.2 is released. Eigen score, Eigen PC score (doi: 10.1038/ng.3477) and GenoCanyon score (doi:10.1038/srep10576) have been added. Allele frequencies of two commonly used subsets of ExAC data (nonTCGA and nonpsych) have been added. Mutation Assessor scores have been updated to release 3. PhyloP7way_vertebrate and PhastCons7way_vertebrate conservation scores have been updated to PhyloP100way_vertebrate and PhastCons100way_vertebrate, respectively. rankscores have been updated accordingly. Ancestral alleles have been updated based on Ensembl 84. dbSNP has been updated to build 146. Clinvar has been updated to 20160302. InterPro has been updated to v56. Gene name cross-links, IntAct, Uniprot, GWAS catalog, BioGRID, GO, ConsensusPathDB, mouse genes and zebra fish genes information for the dbNSFP_gene table have been updated. November 30, 2016: dbNSFP v3.3 and v2.9.2 are released. M-CAP score (DOI: 10.1038/ng.3703) has been added. We thank Dr. Gill Bejerano for providing the score. Eigen and Eigen PC scores have been updated to v1.1. dbSNP has been updated to v147. clinvar has been updated to 20161101. March 12, 2017: dbNSFP v3.4 and v2.9.3 are released. REVEL score ( doi: 10.1016/j.ajhg.2016.08.016) and MutPred score (doi: 10.1093/bioinformatics/btp528) have been added. SORVA gene ranking scores (doi: 10.1101/103218) have been added to gene annotation. August 6, 2017: dbNSFP v3.5 is released. Allele frequencies from the exomes and genomes of the Genome Aggregation Database (gnomAD) have been added. Interpro, dbSNP, clinvar, ancestral alleles, Altai Neanderthal genotypes, Denisova genotypes and GTEx eQTLs have been updated. dbNSFP_gene has been rebuilt with updated annotations. Other changes to dbNSFP_gene include: Interactions columns now show the gene list instead of the total number; GTEx gene expression annotations have been removed; LoF FDR p-value from RVIS has been added; Genome-wide haploinsufficiency score (GHIS) has been added; LoF and CNV intolerance/tolerance scores based on ExAC data have been added. December 8, 2018: dbNSFP v4.0b1 is released for beta testing. The core set of nsSNVs and ssSNVs has been rebuilt based on Gencode 29/ Ensembl 94 with human reference sequence hg38. Eight deleteriousness prediction scores (ALoFT, DEOGEN2, FATHMM-XF, MPC, MVP, PrimateAI, LINSIGHT, SIFT4G) have been added. Three conservation scores (phyloP17way_primate, phastCons17way_primate, bStatistic) have been added. Allele frequencies from the gnomAD consortium, eQTLs from the Geuvadis project, and genotypes of a Vindija33.19 Neanderthal have been added. Some resources have been updated, including VEST (We thank Dr. Karchin), CADD, M-CAP, ancestral alleles, dbSNP, ClinVar, GTEx and InterPro. The presentation of the prediction scores has been further improved by adding the correspondence to transcript/protein ids in a systematic way. APPRIS, GENCODE_basic, TSL and VEP_canonical have been added to facilitate the choice of appropriate transcripts. dbNSFP_gene has also been completely rebuilt using the up-to-date resources. HIPred, gene constraint scores from the gnomAD data, essential genes predictions based on CRISPR, gene-trap and gene networks have been added. Two branches of dbNSFP are provided: dbNSFP4.0b1a suitable for academic use, which includes all the resources, and dbNSFP4.0b1c suitable for commercial use, which does not include Polyphen2, VEST, REVEL, CADD, LINSIGHT, and GenoCanyon. Please contact Dr. Xiaoming Liu (xmliu.uth{at}gmail.com) for commercial usage of dbNSFP. December 30, 2018: A bug causing id mapping issue from Uniprot to Ensembl, which further causing increased missing rates of Polyphen2, MutationAssessor and DEOGEN2, has been found and fixed (We thank Dr. Daniele Raimondi). February 20, 2019: sprot_varsplic was included in the mapping from Uniprot to Ensembl. Fixed column title inconsistency between the README file and data file. (We thank Kevin Xin and Julius Jacobsen for pointing out the inconsistency.) dbMTS was added as an attached database. search_dbNSFP added support for searching dbMTS with option '-m'. May 3, 2019: dbNSFP v4.0 is released. HGVS c. and p. presentations from ANNOVAR, SnpEff and VEP have been added. search_dbNSFP now supports search based on HGVS c. and p. presentations. Please refer to search_dbNSFP40a.readme.pdf or search_dbNSFP40c.readme.pdf for details. MedGen ID, OMIM ID and Orphanet ID from clinvar have been added. December 5, 2019: A minor bug is fixed in dbNSFP v4.0. In the previous release the content of the following columns were compressed, i.e. if annotations for all transcripts are identical, only one annotation was presented: genename, cds_strand, refcodon, codonpos, codon_degeneracy, FATHMM_score, FATHMM_pred, Interpro_domain. In this release those columns are decompressed, i.e. have the same number of annotations as the number of transcripts. A Java-based graphic user interface (GUI) search program (search_dbNSFP40a.jar or search_dbNSFP40c.jar) has been added. Users can double-click the jar file to launch the GUI (it supports commandline also, please check the search_dbNSFP readme pdf for details). May 15, 2020: A minor bug is fixed in dbNSFP v4.0. In the previous release, the column Primate_AI_pred was not 100% correct. We thank Alex Kouris for reporting this issue. June 16, 2020: dbNSFP v4.1 is released. BayesDel (https://doi.org/10.1002/humu.23158), ClinPred (https://doi.org/10.1016/j.ajhg.2018.08.005) and LIST-S2 (https://doi.org/10.1093/nar/gkaa288) scores have been added. CADD has been updated to v1.6, CADD score based on hg19 model has been added. Clinvar, GTEx and gnomAD genomes have been updated. HPO terms have been added to the dbNSFP_gene. search_dbNSFP programs now support searching SpliceAI as an attached database. Jan 27, 2021: The command-line only version of the search programs for v4.1a and v4.1c were added. Feb 10, 2021: A bug fixed. In the previous release, the gnomAD_pLI, gnomAD_pRec and gnomAD_pNull scores in dbNSFP4.1_gene.gz and dbNSFP4.1_gene.complete.gz have a problem that the scores are not always corresponding to the canonical transcripts of the genes. We thank Dr. Raphaël Helaers for reporting this bug. March 12, 2021: A bug fixed. In the previous release, some ALoFT scores/information are missing in dbNSFP. We thank Dr. Shuwei Li for reporting this bug. April 6, 2021: dbNSFP v4.2 is released. MetaRNN scores have been added. Allele frequencies of gnomAD exome have been updated to r2.1.1. Allele Frequencies of gnomAD genome have been updated to v3.1. dbSNP has been updated to 154. clinvar has been updated to 20210131. February 18, 2022: dbNSFP v4.3 is released. REVEL scores have been updated with transcript ids, i.e., the scores are now transcript-specific. Genotypes of Chagyrskaya neandertals have been added. dbSNP has been updated to b155. clinvar has been updated to 20220122. May 6, 2023: dbNSFP v4.4 is released. gMVP and VARITY scores have been added. Allele frequencies of ALFA (Allele Frequency Aggregator) have been added. dbSNP has been updated to b156. clinvar has been updated to 20230430. phyloP30way_mammalian has been replaced by phyloP470way_mammalian. phastCons30way_mammalian has been replaced by phastCons470way_mammalian. A bug in MutPred scores (not all SNVs causing the same AA change have scores) has been fixed. November 2, 2023: dbNSFP v4.5 is released. ClinVar has been updated to 20231028. ESM1b, EVE and AlphaMissense scores have been added. AlphaMissense scores are for non-commercial research use only: "AlphaMissense Database Copyright (2023) DeepMind Technologies Limited. All predictions are provided for non-commercial research use only under CC BY-NC-SA license." This distribution of the derived AlphaMissense_score, AlphaMissense_rankscore, and AlphaMissense_pred in dbNSFP are also under CC BY-NC-SA license and only included in the "a" branch of dbNSFP. A copy of CC BY-NC-SA license can be found at https://creativecommons.org/licenses/by-nc-sa/4.0/. February 18, 2024: dbNSFP v4.6 is released. ClinVar has been updated to 20240215. GTEx V8 splicing QTLs (sQTLs) have been added. eQTLs from eQTLGen phase I have been added. There was a bug in v4.5 causing a large proportion of ESM1b scores to be misaligned. It has been fixed. We thank Dr. In-Hee Lee for reporting this bug. March 3, 2024: dbNSFP v4.7 is released. CADD has been updated to v1.7. Allele frequencies of gnomAD exomes and genomes have been updated to v4.0.0. One bug in v4.6 causing eQTLGen eQTLs of some tissues missing has been fixed. March 13, 2024: AlphaMissense scores are now licensed under the Creative Commons Attribution 4.0 International License (CC-BY), thereby been added to dbNSFP v4.7 "c" branch. June 13, 2024: dbNSFP v4.8 is released. MutFormer and PHACTboost scores have been added. GERP conservation score calculated based on 91 mammals has been added. August 8, 2024: dbNSFP v4.9 is released. MutScore has been added. ClinVar has been updated. January 1, 2025: dbNSFP v5.0 is released. Fully rebuilt based on Gencode 46. Allele frequencies from TOPMed freeze8, and gnomAD exome controls, non-neuro, and non-cancer subsets from v2.1.1 have been added. Transcripts annotations from the MANE project has been added. MutationTaster has been updated to MutationTaster2021. Allele frequencies from gnomAD have been updated to v4.1 joint data set (genome+exome). bStatistic ancestral alleles, and ClinVar have been updated. LRT, FATHMM, fathmm-MKL, fitCons, LINSIGHT, GenoCanyon, EVE, Siphy scores, allele frequencies from ESP, ExAC, UK10K, and GTEx, eQTLGen and Geuvadis eQTLs have been retired. The gene table has also been rebuilt. ClinGen Dosage Sensitivity and Humnan Protein Atlas consensus gene expression levels have been added. HGNC, Uniprot, IntAct, GWAS catalog, Interpro, Gene Ontology, ConsensusPathDB, HPO, mouse homolog genes, zebrafish homolog genes, HPO, OMIM, Orphanet have been updated. The egenetics and GNF/Atlas expression, gene interactions and SORVA statistic have been retired.