aaref
reference amino acid "." if the variant is a splicing site SNP (2bp on each end of an intron)
aaalt
alternative amino acid "." if the variant is a splicing site SNP (2bp on each end of an intron)
rs_dbSNP
rs number from dbSNP
No histogram: Empty histogram for rs_dbSNP in a region: Too many unique values 101 for categorical histogram.
hg19_chr
chromosome as to hg19, "." means missing
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)
.png "hg19_pos(1-based)")
hg18_chr
chromosome as to hg18, "." means missing
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)
.png "hg18_pos(1-based)")
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
No histogram: Empty histogram for aapos in a region: Too many unique values 101 for categorical histogram.
genename
gene name; if the nsSNV can be assigned to multiple genes, gene names are separated by ";"
No histogram: Empty histogram for genename in a region: Too many unique values 101 for categorical histogram.
Ensembl_geneid
Ensembl gene id
No histogram: Empty histogram for Ensembl_geneid in a region: Too many unique values 101 for categorical histogram.
Ensembl_transcriptid
Ensembl transcript ids (Multiple entries separated by ";")
No histogram: Empty histogram for Ensembl_transcriptid in a region: Too many unique values 101 for categorical histogram.
Ensembl_proteinid
Ensembl protein ids Multiple entries separated by ";", corresponding to Ensembl_transcriptids
No histogram: Empty histogram for Ensembl_proteinid in a region: Too many unique values 101 for categorical histogram.
Uniprot_acc
Uniprot accession number matching the Ensembl_proteinid Multiple entries separated by ";".
No histogram: Empty histogram for Uniprot_acc in a region: Too many unique values 101 for categorical histogram.
Uniprot_entry
Uniprot entry ID matching the Ensembl_proteinid Multiple entries separated by ";".
No histogram: Empty histogram for Uniprot_entry in a region: Too many unique values 101 for categorical histogram.
HGVSc_ANNOVAR
HGVS coding variant presentation from ANNOVAR Multiple entries separated by ";", corresponds to Ensembl_transcriptid
No histogram: Empty histogram for HGVSc_ANNOVAR in a region: Too many unique values 101 for categorical histogram.
HGVSp_ANNOVAR
HGVS protein variant presentation from ANNOVAR Multiple entries separated by ";", corresponds to Ensembl_proteinid
No histogram: Empty histogram for HGVSp_ANNOVAR in a region: Too many unique values 101 for categorical histogram.
HGVSc_snpEff
HGVS coding variant presentation from snpEff Multiple entries separated by ";", corresponds to Ensembl_transcriptid
No histogram: Empty histogram for HGVSc_snpEff in a region: Too many unique values 101 for categorical histogram.
HGVSp_snpEff
HGVS protein variant presentation from snpEff Multiple entries separated by ";", corresponds to Ensembl_proteinid
No histogram: Empty histogram for HGVSp_snpEff in a region: Too many unique values 101 for categorical histogram.
HGVSc_VEP
HGVS coding variant presentation from VEP Multiple entries separated by ";", corresponds to Ensembl_transcriptid
No histogram: Empty histogram for HGVSc_VEP in a region: Too many unique values 101 for categorical histogram.
HGVSp_VEP
HGVS protein variant presentation from VEP Multiple entries separated by ";", corresponds to Ensembl_proteinid
No histogram: Empty histogram for HGVSp_VEP in a region: Too many unique values 101 for categorical histogram.
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
No histogram: Empty histogram for APPRIS in a region: Too many unique values 101 for categorical histogram.
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
No histogram: Can not merge categorical histograms; too many unique values 112
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
No histogram: Empty histogram for TSL in a region: Too many unique values 101 for categorical histogram.
VEP_canonical
canonical transcript used in Ensembl. Multiple entries separated by ";", matching Ensembl_transcriptid. See https://useast.ensembl.org/Help/Glossary?id=521
No histogram: Can not merge categorical histograms; too many unique values 103
cds_strand
coding sequence (CDS) strand (+ or -)
No histogram: Can not merge categorical histograms; too many unique values 101
refcodon
reference codon
No histogram: Empty histogram for refcodon in a region: Too many unique values 101 for categorical histogram.
codonpos
position on the codon (1, 2 or 3)
No histogram: Can not merge categorical histograms; too many unique values 124
codon_degeneracy
degenerate type (0, 2 or 3)
No histogram: Can not merge categorical histograms; too many unique values 124
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
AltaiNeandertal
genotype of a deep sequenced Altai Neanderthal
Denisova
genotype of a deep sequenced Denisova
VindijiaNeandertal
genotype of a deep sequenced Vindijia Neandertal
ChagyrskayaNeandertal
genotype of a deep sequenced Chagyrskaya Neandertal
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.
No histogram: Empty histogram for SIFT_score in a region: Too many unique values 101 for categorical histogram.
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.
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 ";"
No histogram: Empty histogram for SIFT_pred in a region: Too many unique values 101 for categorical histogram.
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
No histogram: Empty histogram for SIFT4G_score in a region: Too many unique values 101 for categorical histogram.
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.
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
No histogram: Empty histogram for SIFT4G_pred in a region: Too many unique values 101 for categorical histogram.
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.
No histogram: Empty histogram for Polyphen2_HDIV_score in a region: Too many unique values 101 for categorical histogram.
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.
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
No histogram: Empty histogram for Polyphen2_HDIV_pred in a region: Too many unique values 101 for categorical histogram.
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.
No histogram: Empty histogram for Polyphen2_HVAR_score in a region: Too many unique values 101 for categorical histogram.
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.
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
No histogram: Empty histogram for Polyphen2_HVAR_pred in a region: Too many unique values 101 for categorical histogram.
LRT_score
The original LRT two-sided p-value (LRTori), ranges from 0 to 1.
LRT_converted_rankscore
LRTori scores were first converted as LRTnew=1-LRTori*0.5 if Omega<1, or LRTnew=LRTori*0.5 if Omega>=1. Then LRTnew scores were ranked among all LRTnew scores in dbNSFP. The rankscore is the ratio of the rank over the total number of the scores in dbNSFP. The scores range from 0.00162 to 0.8433.
LRT_pred
LRT prediction, D(eleterious), N(eutral) or U(nknown), which is not solely determined by the score.
LRT_Omega
estimated nonsynonymous-to-synonymous-rate ratio (Omega, reported by LRT)
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
No histogram: Empty histogram for MutationTaster_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for MutationTaster_pred in a region: Too many unique values 101 for categorical histogram.
MutationTaster_model
MutationTaster prediction models.
No histogram: Empty histogram for MutationTaster_model in a region: Too many unique values 101 for categorical histogram.
MutationTaster_AAE
MutationTaster predicted amino acid change.
No histogram: Empty histogram for MutationTaster_AAE in a region: Too many unique values 101 for categorical histogram.
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.
No histogram: Empty histogram for MutationAssessor_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for MutationAssessor_pred in a region: Too many unique values 101 for categorical histogram.
FATHMM_score
FATHMM default score (weighted for human inherited-disease mutations with Disease Ontology) (FATHMMori). Scores range from -16.13 to 10.64. The smaller the score the more likely the SNP has damaging effect. Multiple scores separated by ";", corresponding to Ensembl_proteinid.
No histogram: Empty histogram for FATHMM_score in a region: Too many unique values 101 for categorical histogram.
FATHMM_converted_rankscore
FATHMMori scores were first converted to FATHMMnew=1-(FATHMMori+16.13)/26.77, then ranked among all FATHMMnew scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of FATHMMnew scores in dbNSFP. If there are multiple scores, only the most damaging (largest) rankscore is presented. The scores range from 0 to 1.
FATHMM_pred
If a FATHMMori score is <=-1.5 (or rankscore >=0.81332) the corresponding nsSNV is predicted as "D(AMAGING)"; otherwise it is predicted as "T(OLERATED)". Multiple predictions separated by ";", corresponding to Ensembl_proteinid.
No histogram: Empty histogram for FATHMM_pred in a region: Too many unique values 101 for categorical histogram.
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.
No histogram: Empty histogram for PROVEAN_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for PROVEAN_pred in a region: Too many unique values 101 for categorical histogram.
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.
No histogram: Empty histogram for VEST4_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
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.
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.
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.
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.
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.
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.
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),
No histogram: Empty histogram for MetaRNN_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Can not merge categorical histograms; too many unique values 101
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.
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.
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.
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.
No histogram: Empty histogram for REVEL_score in a region: Too many unique values 101 for categorical histogram.
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.
MutPred_score
General MutPred score. Scores range from 0 to 1. The larger the score the more likely the SNP has damaging effect.
No histogram: Empty histogram for MutPred_score in a region: Too many unique values 101 for categorical histogram.
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.
MutPred_protID
UniProt accession or Ensembl transcript ID used for MutPred_score calculation.
No histogram: Empty histogram for MutPred_protID in a region: Too many unique values 101 for categorical histogram.
MutPred_AAchange
Amino acid change used for MutPred_score calculation.
No histogram: Empty histogram for MutPred_AAchange in a region: Too many unique values 101 for categorical histogram.
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.
No histogram: Empty histogram for MutPred_Top5features in a region: Too many unique values 101 for categorical histogram.
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.
No histogram: Empty histogram for MVP_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for gMVP_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for MPC_score in a region: Too many unique values 101 for categorical histogram.
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.
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
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.
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.
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.
No histogram: Empty histogram for DEOGEN2_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for DEOGEN2_pred in a region: Too many unique values 101 for categorical histogram.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
No histogram: Empty histogram for LIST-S2_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for LIST-S2_pred in a region: Too many unique values 101 for categorical histogram.
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
No histogram: Empty histogram for VARITY_R_score in a region: Too many unique values 101 for categorical histogram.
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.
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
No histogram: Empty histogram for VARITY_ER_score in a region: Too many unique values 101 for categorical histogram.
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.
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
No histogram: Empty histogram for VARITY_R_LOO_score in a region: Too many unique values 101 for categorical histogram.
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.
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
No histogram: Empty histogram for VARITY_ER_LOO_score in a region: Too many unique values 101 for categorical histogram.
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.
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
No histogram: Empty histogram for ESM1b_score in a region: Too many unique values 101 for categorical histogram.
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.
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.
No histogram: Empty histogram for ESM1b_pred in a region: Too many unique values 101 for categorical histogram.
EVE_score
EVE is a unsupervised model designed to predict the clinical relevance of human single amino acid variants by examining the sequences of various organisms throughout evolutionary history. The EVE score ranges from 0 to 1. The larger the score, the more likely the variant is pathogenic. Detals see https://doi.org/10.1038/s41586-021-04043-8.
No histogram: Empty histogram for EVE_score in a region: Too many unique values 101 for categorical histogram.
EVE_rankscore
EVE scores were ranked among all EVE scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of EVE scores in dbNSFP.
EVE_Class10_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 10% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 105
EVE_Class20_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 20% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 117
EVE_Class25_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 25% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 119
EVE_Class30_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 30% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 121
EVE_Class40_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 40% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 122
EVE_Class50_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 50% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 122
EVE_Class60_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 60% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 126
EVE_Class70_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 70% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 126
EVE_Class75_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 75% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 126
EVE_Class80_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 80% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 127
EVE_Class90_pred
The EVE classification (B)enign, (U)ncertain, or (P)athogenic when setting 90% as uncertain in a Gaussian mixture model.
No histogram: Can not merge categorical histograms; too many unique values 127
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.
No histogram: Empty histogram for AlphaMissense_score in a region: Too many unique values 101 for categorical histogram.
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.
AlphaMissense_pred
The AlphaMissense classification of likely (B)enign, (A)mbiguous, or likely (P)athogenic with
No histogram: Empty histogram for AlphaMissense_pred in a region: Too many unique values 101 for categorical histogram.
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).
No histogram: Empty histogram for PHACTboost_score in a region: Too many unique values 101 for categorical histogram.
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.
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).
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.
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).
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.
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.
No histogram: Empty histogram for Aloft_Fraction_transcripts_affected in a region: Too many unique values 101 for categorical histogram.
Aloft_prob_Tolerant
Probability of the SNP being classified as benign by ALoFT multiple values separated by ";", corresponding to Ensembl_proteinid.
No histogram: Empty histogram for Aloft_prob_Tolerant in a region: Too many unique values 101 for categorical histogram.
Aloft_prob_Recessive
Probability of the SNP being classified as recessive disease-causing by ALoFT multiple values separated by ";", corresponding to Ensembl_proteinid.
No histogram: Empty histogram for Aloft_prob_Recessive in a region: Too many unique values 101 for categorical histogram.
Aloft_prob_Dominant
Probability of the SNP being classified as dominant disease-causing by ALoFT multiple values separated by ";", corresponding to Ensembl_proteinid.
No histogram: Empty histogram for Aloft_prob_Dominant in a region: Too many unique values 101 for categorical histogram.
Aloft_pred
final classification predicted by ALoFT; values can be Tolerant, Recessive or Dominant multiple values separated by ";", corresponding to Ensembl_proteinid.
No histogram: Can not merge categorical histograms; too many unique values 101
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.
No histogram: Can not merge categorical histograms; too many unique values 101
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)."
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)."
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)."
CADD_raw_hg19
CADD raw score for functional prediction of a SNP using the hg19 model. 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 -9.777566 to 30.05914 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)."
CADD_raw_rankscore_hg19
CADD raw scores were ranked among all CADD_raw_hg19 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)."
CADD_phred_hg19
CADD phred-like score using the hg19 model. This is phred-like rank score based on whole genome CADD raw scores. Please refer to Kircher et al. (2014) Nature Genetics
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.
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.
fathmm-MKL_coding_score
fathmm-MKL 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/btv009.
fathmm-MKL_coding_rankscore
fathmm-MKL coding scores were ranked among all fathmm-MKL coding scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of fathmm-MKL coding scores in dbNSFP.
fathmm-MKL_coding_pred
If a fathmm-MKL_coding_score is >0.5 (or rankscore >0.28317) the corresponding nsSNV is predicted as "D(AMAGING)"; otherwise it is predicted as "N(EUTRAL)".
fathmm-MKL_coding_group
the groups of features (labeled A-J) used to obtained the score. More details can be found in doi: 10.1093/bioinformatics/btv009.
No histogram: Can not merge categorical histograms; too many unique values 101
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.
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.
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)".
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).
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.
Eigen-phred_coding
Eigen score in phred scale.
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).
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.
Eigen-PC-phred_coding
Eigen PC score in phred scale.
GenoCanyon_score
A functional prediction score based on conservation and biochemical annotations using an unsupervised statistical learning. (doi:10.1038/srep10576)
GenoCanyon_rankscore
GenoCanyon_score scores were ranked among all integrated fitCons scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of GenoCanyon_score scores in dbNSFP.
integrated_fitCons_score
fitCons score predicts the fraction of genomic positions belonging to a specific function class (defined by epigenomic "fingerprint") that are under selective pressure. Scores range from 0 to 1, with a larger score indicating a higher proportion of nucleic sites of the functional class the genomic position belong to are under selective pressure, therefore more likely to be functional important. Integrated (i6) scores are integrated across three cell types (GM12878, H1-hESC and HUVEC). More details can be found in doi:10.1038/ng.3196.
integrated_fitCons_rankscore
integrated fitCons scores were ranked among all integrated fitCons scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of integrated fitCons scores in dbNSFP.
integrated_confidence_value
0 - highly significant scores (approx. p<.003); 1 - significant scores (approx. p<.05); 2 - informative scores (approx. p<.25); 3 - other scores (approx. p>=.25).
GM12878_fitCons_score
fitCons score predicts the fraction of genomic positions belonging to a specific function class (defined by epigenomic "fingerprint") that are under selective pressure. Scores range from 0 to 1, with a larger score indicating a higher proportion of nucleic sites of the functional class the genomic position belong to are under selective pressure, therefore more likely to be functional important. GM12878 fitCons scores are based on cell type GM12878. More details can be found in doi:10.1038/ng.3196.
GM12878_fitCons_rankscore
GM12878 fitCons scores were ranked among all GM12878 fitCons scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of GM12878 fitCons scores in dbNSFP.
GM12878_confidence_value
0 - highly significant scores (approx. p<.003); 1 - significant scores (approx. p<.05); 2 - informative scores (approx. p<.25); 3 - other scores (approx. p>=.25).
H1-hESC_fitCons_score
fitCons score predicts the fraction of genomic positions belonging to a specific function class (defined by epigenomic "fingerprint") that are under selective pressure. Scores range from 0 to 1, with a larger score indicating a higher proportion of nucleic sites of the functional class the genomic position belong to are under selective pressure, therefore more likely to be functional important. GM12878 fitCons scores are based on cell type H1-hESC. More details can be found in doi:10.1038/ng.3196.
H1-hESC_fitCons_rankscore
H1-hESC fitCons scores were ranked among all H1-hESC fitCons scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of H1-hESC fitCons scores in dbNSFP.
H1-hESC_confidence_value
0 - highly significant scores (approx. p<.003); 1 - significant scores (approx. p<.05); 2 - informative scores (approx. p<.25); 3 - other scores (approx. p>=.25).
HUVEC_fitCons_score
fitCons score predicts the fraction of genomic positions belonging to a specific function class (defined by epigenomic "fingerprint") that are under selective pressure. Scores range from 0 to 1, with a larger score indicating a higher proportion of nucleic sites of the functional class the genomic position belong to are under selective pressure, therefore more likely to be functional important. GM12878 fitCons scores are based on cell type HUVEC. More details can be found in doi:10.1038/ng.3196.
HUVEC_fitCons_rankscore
HUVEC fitCons scores were ranked among all HUVEC fitCons scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of HUVEC fitCons scores in dbNSFP.
HUVEC_confidence_value
0 - highly significant scores (approx. p<.003); 1 - significant scores (approx. p<.05); 2 - informative scores (approx. p<.25); 3 - other scores (approx. p>=.25).
LINSIGHT
"The LINSIGHT score measures the probability of negative selection on noncoding sites" Details refer to doi:10.1038/ng.3810.
LINSIGHT_rankscore
LINSIGHT scores were ranked among all LINSIGHT scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of LINSIGHT scores in dbNSFP.
GERP++_NR
GERP++ neutral rate
GERP++_RS
GERP++ RS score, the larger the score, the more conserved the site. Scores range from -12.3 to 6.17.
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.
GERP_91_mammals
GERP conservation score calculated based on multiple sequence alignments of 91 mammals.
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.
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.
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.
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.
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.
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.
phyloP17way_primate_rankscore
the rank of the phyloP17way_primate score among all phyloP17way_primate scores in dbNSFP.
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.
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.
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.
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.
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.
phastCons17way_primate_rankscore
the rank of the phastCons17way_primate score among all phastCons17way_primate scores in dbNSFP.
SiPhy_29way_pi
The estimated stationary distribution of A, C, G and T at the site, using SiPhy algorithm based on 29 mammals genomes.
No histogram: Empty histogram for SiPhy_29way_pi in a region: Too many unique values 101 for categorical histogram.
SiPhy_29way_logOdds
SiPhy score based on 29 mammals genomes. The larger the score, the more conserved the site. Scores range from 0 to 37.9718 in dbNSFP.
SiPhy_29way_logOdds_rankscore
SiPhy_29way_logOdds scores were ranked among all SiPhy_29way_logOdds scores in dbNSFP. The rankscore is the ratio of the rank of the score over the total number of SiPhy_29way_logOdds scores in dbNSFP.
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.
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.
1000Gp3_AC
Alternative allele counts in the whole 1000 genomes phase 3 (1000Gp3) data.
1000Gp3_AF
Alternative allele frequency in the whole 1000Gp3 data.
1000Gp3_AFR_AC
Alternative allele counts in the 1000Gp3 African descendent samples.
1000Gp3_AFR_AF
Alternative allele frequency in the 1000Gp3 African descendent samples.
1000Gp3_EUR_AC
Alternative allele counts in the 1000Gp3 European descendent samples.
1000Gp3_EUR_AF
Alternative allele frequency in the 1000Gp3 European descendent samples.
1000Gp3_AMR_AC
Alternative allele counts in the 1000Gp3 American descendent samples.
1000Gp3_AMR_AF
Alternative allele frequency in the 1000Gp3 American descendent samples.
1000Gp3_EAS_AC
Alternative allele counts in the 1000Gp3 East Asian descendent samples.
1000Gp3_EAS_AF
Alternative allele frequency in the 1000Gp3 East Asian descendent samples.
1000Gp3_SAS_AC
Alternative allele counts in the 1000Gp3 South Asian descendent samples.
1000Gp3_SAS_AF
Alternative allele frequency in the 1000Gp3 South Asian descendent samples.
TWINSUK_AC
Alternative allele count in called genotypes in UK10K TWINSUK cohort.
TWINSUK_AF
Alternative allele frequency in called genotypes in UK10K TWINSUK cohort.
ALSPAC_AC
Alternative allele count in called genotypes in UK10K ALSPAC cohort.
ALSPAC_AF
Alternative allele frequency in called genotypes in UK10K ALSPAC cohort.
UK10K_AC
Alternative allele count in combined genotypes in UK10K cohort (TWINSUK+ALSPAC).
UK10K_AF
Alternative allele frequency in combined genotypes in UK10K cohort (TWINSUK+ALSPAC).
ESP6500_AA_AC
Alternative allele count in the African American samples of the NHLBI GO Exome Sequencing Project (ESP6500 data set).
ESP6500_AA_AF
Alternative allele frequency in the African American samples of the NHLBI GO Exome Sequencing Project (ESP6500 data set).
ESP6500_EA_AC
Alternative allele count in the European American samples of the NHLBI GO Exome Sequencing Project (ESP6500 data set).
ESP6500_EA_AF
Alternative allele frequency in the European American samples of the NHLBI GO Exome Sequencing Project (ESP6500 data set).
ExAC_AC
Allele count in total ExAC samples (60,706 samples)
ExAC_AF
Allele frequency in total ExAC samples
ExAC_Adj_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in total ExAC samples
ExAC_Adj_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in total ExAC samples
ExAC_AFR_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in African & African American ExAC samples
ExAC_AFR_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in African & African American ExAC samples
ExAC_AMR_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in American ExAC samples
ExAC_AMR_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in American ExAC samples
ExAC_EAS_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in East Asian ExAC samples
ExAC_EAS_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in East Asian ExAC samples
ExAC_FIN_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in Finnish ExAC samples
ExAC_FIN_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in Finnish ExAC samples
ExAC_NFE_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in Non-Finnish European ExAC samples
ExAC_NFE_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in Non-Finnish European ExAC samples
ExAC_SAS_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in South Asian ExAC samples
ExAC_SAS_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in South Asian ExAC samples
ExAC_nonTCGA_AC
Allele count in total ExAC_nonTCGA samples (53,105 samples)
ExAC_nonTCGA_AF
Allele frequency in total ExAC_nonTCGA samples
ExAC_nonTCGA_Adj_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in total ExAC_nonTCGA samples
ExAC_nonTCGA_Adj_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in total ExAC_nonTCGA samples
ExAC_nonTCGA_AFR_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in African & African American ExAC_nonTCGA samples
ExAC_nonTCGA_AFR_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in African & African American ExAC_nonTCGA samples
ExAC_nonTCGA_AMR_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in American ExAC_nonTCGA samples
ExAC_nonTCGA_AMR_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in American ExAC_nonTCGA samples
ExAC_nonTCGA_EAS_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in East Asian ExAC_nonTCGA samples
ExAC_nonTCGA_EAS_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in East Asian ExAC_nonTCGA samples
ExAC_nonTCGA_FIN_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in Finnish ExAC_nonTCGA samples
ExAC_nonTCGA_FIN_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in Finnish ExAC_nonTCGA samples
ExAC_nonTCGA_NFE_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in Non-Finnish European ExAC_nonTCGA samples
ExAC_nonTCGA_NFE_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in Non-Finnish European ExAC_nonTCGA samples
ExAC_nonTCGA_SAS_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in South Asian ExAC_nonTCGA samples
ExAC_nonTCGA_SAS_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in South Asian ExAC_nonTCGA samples
ExAC_nonpsych_AC
Allele count in total ExAC_nonpsych samples (45,376 samples)
ExAC_nonpsych_AF
Allele frequency in total ExAC_nonpsych samples
ExAC_nonpsych_Adj_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in total ExAC_nonpsych samples
ExAC_nonpsych_Adj_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in total ExAC_nonpsych samples
ExAC_nonpsych_AFR_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in African & African American ExAC_nonpsych samples
ExAC_nonpsych_AFR_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in African & African American ExAC_nonpsych samples
ExAC_nonpsych_AMR_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in American ExAC_nonpsych samples
ExAC_nonpsych_AMR_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in American ExAC_nonpsych samples
ExAC_nonpsych_EAS_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in East Asian ExAC_nonpsych samples
ExAC_nonpsych_EAS_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in East Asian ExAC_nonpsych samples
ExAC_nonpsych_FIN_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in Finnish ExAC_nonpsych samples
ExAC_nonpsych_FIN_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in Finnish ExAC_nonpsych samples
ExAC_nonpsych_NFE_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in Non-Finnish European ExAC_nonpsych samples
ExAC_nonpsych_NFE_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in Non-Finnish European ExAC_nonpsych samples
ExAC_nonpsych_SAS_AC
Adjusted Alt allele counts (DP >= 10 & GQ >= 20) in South Asian ExAC_nonpsych samples
ExAC_nonpsych_SAS_AF
Adjusted Alt allele frequency (DP >= 10 & GQ >= 20) in South Asian ExAC_nonpsych samples
gnomAD_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.
gnomAD_exomes_AC
Alternative allele count in the whole gnomAD exome samples v4.0.0
gnomAD_exomes_AN
Total allele count in the whole gnomAD exome samples v4.0.0
gnomAD_exomes_AF
Alternative allele frequency in the whole gnomAD exome samples v4.0.0
gnomAD_exomes_nhomalt
Count of individuals with homozygous alternative allele in the whole gnomAD exome samples v4.0.0
gnomAD_exomes_POPMAX_AC
Allele count in the population with the maximum AF
gnomAD_exomes_POPMAX_AN
Total number of alleles in the population with the maximum AF
gnomAD_exomes_POPMAX_AF
Maximum allele frequency across populations (excluding samples of Ashkenazi, Finnish, and indeterminate ancestry)
gnomAD_exomes_POPMAX_nhomalt
Count of homozygous individuals in the population with the maximum allele frequency
gnomAD_exomes_AFR_AC
Alternative allele count in the African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_AFR_AN
Total allele count in the African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_AFR_AF
Alternative allele frequency in the African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_AFR_nhomalt
Count of individuals with homozygous alternative allele in the African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_AMR_AC
Alternative allele count in the Latino gnomAD exome samples v4.0.0
gnomAD_exomes_AMR_AN
Total allele count in the Latino gnomAD exome samples v4.0.0
gnomAD_exomes_AMR_AF
Alternative allele frequency in the Latino gnomAD exome samples v4.0.0
gnomAD_exomes_AMR_nhomalt
Count of individuals with homozygous alternative allele in the Latino gnomAD exome samples v4.0.0
gnomAD_exomes_ASJ_AC
Alternative allele count in the Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_ASJ_AN
Total allele count in the Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_ASJ_AF
Alternative allele frequency in the Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_ASJ_nhomalt
Count of individuals with homozygous alternative allele in the Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_EAS_AC
Alternative allele count in the East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_EAS_AN
Total allele count in the East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_EAS_AF
Alternative allele frequency in the East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_EAS_nhomalt
Count of individuals with homozygous alternative allele in the East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_FIN_AC
Alternative allele count in the Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_FIN_AN
Total allele count in the Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_FIN_AF
Alternative allele frequency in the Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_FIN_nhomalt
Count of individuals with homozygous alternative allele in the Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_MID_AC
Alternative allele count in the Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_MID_AN
Total allele count in the Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_MID_AF
Alternative allele frequency in the Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_MID_nhomalt
Count of individuals with homozygous alternative allele in the Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_NFE_AC
Alternative allele count in the Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_NFE_AN
Total allele count in the Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_NFE_AF
Alternative allele frequency in the Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_NFE_nhomalt
Count of individuals with homozygous alternative allele in the Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_SAS_AC
Alternative allele count in the South Asian gnomAD exome samples v4.0.0
gnomAD_exomes_SAS_AN
Total allele count in the South Asian gnomAD exome samples v4.0.0
gnomAD_exomes_SAS_AF
Alternative allele frequency in the South Asian gnomAD exome samples v4.0.0
gnomAD_exomes_SAS_nhomalt
Count of individuals with homozygous alternative allele in the South Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AC
Alternative allele count in the non-UKBiobank subset of whole gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AN
Total allele count in the non-UKBiobank subset of whole gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AF
Alternative allele frequency in the non-UKBiobank subset of whole gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of whole gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AFR_AC
Alternative allele count in the non-UKBiobank subset of African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AFR_AN
Total allele count in the non-UKBiobank subset of African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AFR_AF
Alternative allele frequency in the non-UKBiobank subset of African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AFR_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of African/African American gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AMR_AC
Alternative allele count in the non-UKBiobank subset of Latino gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AMR_AN
Total allele count in the non-UKBiobank subset of Latino gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AMR_AF
Alternative allele frequency in the non-UKBiobank subset of Latino gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_AMR_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of Latino gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_ASJ_AC
Alternative allele count in the non-UKBiobank subset of Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_ASJ_AN
Total allele count in the non-UKBiobank subset of Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_ASJ_AF
Alternative allele frequency in the non-UKBiobank subset of Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_ASJ_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of Ashkenazi Jewish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_EAS_AC
Alternative allele count in the non-UKBiobank subset of East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_EAS_AN
Total allele count in the non-UKBiobank subset of East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_EAS_AF
Alternative allele frequency in the non-UKBiobank subset of East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_EAS_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of East Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_FIN_AC
Alternative allele count in the non-UKBiobank subset of Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_FIN_AN
Total allele count in the non-UKBiobank subset of Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_FIN_AF
Alternative allele frequency in the non-UKBiobank subset of Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_FIN_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of Finnish gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_MID_AC
Alternative allele count in the non-UKBiobank subset of Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_MID_AN
Total allele count in the non-UKBiobank subset of Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_MID_AF
Alternative allele frequency in the non-UKBiobank subset of Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_MID_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of Middle Eastern gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_NFE_AC
Alternative allele count in the non-UKBiobank subset of Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_NFE_AN
Total allele count in the non-UKBiobank subset of Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_NFE_AF
Alternative allele frequency in the non-UKBiobank subset of Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_NFE_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of Non-Finnish European gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_SAS_AC
Alternative allele count in the non-UKBiobank subset of South Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_SAS_AN
Total allele count in the non-UKBiobank subset of South Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_SAS_AF
Alternative allele frequency in the non-UKBiobank subset of South Asian gnomAD exome samples v4.0.0
gnomAD_exomes_non_ukb_SAS_nhomalt
Count of individuals with homozygous alternative allele in the non-UKBiobank subset of South Asian gnomAD exome samples v4.0.0
gnomAD_genomes_flag
information from gnomAD genome 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.
gnomAD_genomes_AC
Alternative allele count in the whole gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_AN
Total allele count in the whole gnomAD genome samples v4.0.0
gnomAD_genomes_AF
Alternative allele frequency in the whole gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_nhomalt
Count of individuals with homozygous alternative allele in the whole gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_POPMAX_AC
Allele count in the population with the maximum AF
gnomAD_genomes_POPMAX_AN
Total number of alleles in the population with the maximum AF
gnomAD_genomes_POPMAX_AF
Maximum allele frequency across populations (excluding samples of Ashkenazi, Finnish, and indeterminate ancestry)
gnomAD_genomes_POPMAX_nhomalt
Count of homozygous individuals in the population with the maximum allele frequency
gnomAD_genomes_AFR_AC
Alternative allele count in the African/African American gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_AFR_AN
Total allele count in the African/African American gnomAD genome samples v4.0.0
gnomAD_genomes_AFR_AF
Alternative allele frequency in the African/African American gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_AFR_nhomalt
Count of individuals with homozygous alternative allele in the African/African American gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_AMI_AC
Alternative allele count in the Amish gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_AMI_AN
Total allele count in the Amish gnomAD genome samples v4.0.0
gnomAD_genomes_AMI_AF
Alternative allele frequency in the Amish gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_AMI_nhomalt
Count of individuals with homozygous alternative allele in the Amish gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_AMR_AC
Alternative allele count in the Latino gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_AMR_AN
Total allele count in the Latino gnomAD genome samples v4.0.0
gnomAD_genomes_AMR_AF
Alternative allele frequency in the Latino gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_AMR_nhomalt
Count of individuals with homozygous alternative allele in the Latino gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_ASJ_AC
Alternative allele count in the Ashkenazi Jewish gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_ASJ_AN
Total allele count in the Ashkenazi Jewish gnomAD genome samples v4.0.0
gnomAD_genomes_ASJ_AF
Alternative allele frequency in the Ashkenazi Jewish gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_ASJ_nhomalt
Count of individuals with homozygous alternative allele in the Ashkenazi Jewish gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_EAS_AC
Alternative allele count in the East Asian gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_EAS_AN
Total allele count in the East Asian gnomAD genome samples v4.0.0
gnomAD_genomes_EAS_AF
Alternative allele frequency in the East Asian gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_EAS_nhomalt
Count of individuals with homozygous alternative allele in the East Asian gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_FIN_AC
Alternative allele count in the Finnish gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_FIN_AN
Total allele count in the Finnish gnomAD genome samples v4.0.0
gnomAD_genomes_FIN_AF
Alternative allele frequency in the Finnish gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_FIN_nhomalt
Count of individuals with homozygous alternative allele in the Finnish gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_MID_AC
Alternative allele count in the Middle Eastern gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_MID_AN
Total allele count in the Middle Eastern gnomAD genome samples v4.0.0
gnomAD_genomes_MID_AF
Alternative allele frequency in the Middle Eastern gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_MID_nhomalt
Count of individuals with homozygous alternative allele in the Middle Eastern gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_NFE_AC
Alternative allele count in the Non-Finnish European gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_NFE_AN
Total allele count in the Non-Finnish European gnomAD genome samples v4.0.0
gnomAD_genomes_NFE_AF
Alternative allele frequency in the Non-Finnish European gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_NFE_nhomalt
Count of individuals with homozygous alternative allele in the Non-Finnish European gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
gnomAD_genomes_SAS_AC
Alternative allele count in the South Asian gnomAD genome samples v4.0.0 For mtDNA, this is sum of AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95") and AC_het ("Allele count restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_SAS_AN
Total allele count in the South Asian gnomAD genome samples v4.0.0
gnomAD_genomes_SAS_AF
Alternative allele frequency in the South Asian gnomAD genome samples v4.0.0 For mtDNA, this is sum of AF_hom ("Allele frequency restricted to variants with a heteroplasmy level >= 0.95") and AF_het ("Allele frequency restricted to variants with a heteroplasmy level >= 0.10 and < 0.95")
gnomAD_genomes_SAS_nhomalt
Count of individuals with homozygous alternative allele in the South Asian gnomAD genome samples v4.0.0 For mtDNA, this is AC_hom ("Allele count restricted to variants with a heteroplasmy level >= 0.95")
ALFA_European_AC
Alternative allele count of the European samples in the Allele Frequency Aggregator
ALFA_European_AN
Total allele count of the European samples in the Allele Frequency Aggregator
ALFA_European_AF
Alternative allele frequency of the European samples in the Allele Frequency Aggregator
ALFA_African_Others_AC
Alternative allele count of the individuals with African ancestry in the Allele Frequency Aggregator
ALFA_African_Others_AN
Total allele count of the individuals with African ancestry in the Allele Frequency Aggregator
ALFA_African_Others_AF
Alternative allele frequency of the individuals with African ancestry in the Allele Frequency Aggregator
ALFA_East_Asian_AC
Alternative allele count of the East Asian samples in the Allele Frequency Aggregator
ALFA_East_Asian_AN
Total allele count of the East Asian samples in the Allele Frequency Aggregator
ALFA_East_Asian_AF
Alternative allele frequency of the East Asian samples in the Allele Frequency Aggregator
ALFA_African_American_AC
Alternative allele count of the African American samples in the Allele Frequency Aggregator
ALFA_African_American_AN
Total allele count of the African American samples in the Allele Frequency Aggregator
ALFA_African_American_AF
Alternative allele frequency of the African American samples in the Allele Frequency Aggregator
ALFA_Latin_American_1_AC
Alternative allele count of the Latin American individiuals with Afro-Caribbean ancestry in the Allele Frequency Aggregator
ALFA_Latin_American_1_AN
Total allele count of the Latin American individiuals with Afro-Caribbean ancestry in the Allele Frequency Aggregator
ALFA_Latin_American_1_AF
Alternative allele frequency of the Latin American individiuals with Afro-Caribbean ancestry in the Allele Frequency Aggregator
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
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
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
ALFA_Other_Asian_AC
Alternative allele count of the Asian individiuals excluding South or East Asian in the Allele Frequency Aggregator
ALFA_Other_Asian_AN
Total allele count of the Asian individiuals excluding South or East Asian in the Allele Frequency Aggregator
ALFA_Other_Asian_AF
Alternative allele frequency of the Asian individiuals excluding South or East Asian in the Allele Frequency Aggregator
ALFA_South_Asian_AC
Alternative allele count of the South Asian samples in the Allele Frequency Aggregator
ALFA_South_Asian_AN
Total allele count of the South Asian samples in the Allele Frequency Aggregator
ALFA_South_Asian_AF
Alternative allele frequency of the South Asian samples in the Allele Frequency Aggregator
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
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
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
ALFA_African_AC
Alternative allele count of the all African samples (African_Others and African_American) in the Allele Frequency Aggregator
ALFA_African_AN
Total allele count of the all African samples (African_Others and African_American) in the Allele Frequency Aggregator
ALFA_African_AF
Alternative allele frequency of the all African samples (African_Others and African_American) in the Allele Frequency Aggregator
ALFA_Asian_AC
Alternative allele count of the all Asian individuals (East_Asian and Other_Asian, excluding South_Asian) in the Allele Frequency Aggregator
ALFA_Asian_AN
Total allele count of the all Asian individuals (East_Asian and Other_Asian, excluding South_Asian) in the Allele Frequency Aggregator
ALFA_Asian_AF
Alternative allele frequency of the all Asian individuals (East_Asian and Other_Asian, excluding South_Asian) in the Allele Frequency Aggregator
ALFA_Total_AC
Alternative allele count of the total samples in the Allele Frequency Aggregator
ALFA_Total_AN
Total allele count of the total samples in the Allele Frequency Aggregator
ALFA_Total_AF
Alternative allele frequency of the total samples in the Allele Frequency Aggregator
clinvar_id
clinvar variation ID
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
clinvar_trait
the trait/disease the clinvar_clnsig referring to
No histogram: Empty histogram for clinvar_trait in a region: Too many unique values 101 for categorical histogram.
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
clinvar_hgvs
variant in HGVS format
No histogram: Empty histogram for clinvar_hgvs in a region: Too many unique values 101 for categorical histogram.
clinvar_var_source
source of the variant
No histogram: Empty histogram for clinvar_var_source in a region: Too many unique values 101 for categorical histogram.
clinvar_MedGen_id
MedGen ID of the trait/disease the clinvar_trait referring to
No histogram: Empty histogram for clinvar_MedGen_id in a region: Too many unique values 101 for categorical histogram.
clinvar_OMIM_id
OMIM ID of the trait/disease the clinvar_trait referring to
No histogram: Can not merge categorical histograms; too many unique values 103
clinvar_Orphanet_id
Orphanet ID of the trait/disease the clinvar_trait referring to
No histogram: Can not merge categorical histograms; too many unique values 102
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 ";".
No histogram: Empty histogram for Interpro_domain in a region: Too many unique values 101 for categorical histogram.
GTEx_V8_eQTL_gene
target gene of the (significant) eQTL SNP
No histogram: Can not merge categorical histograms; too many unique values 115
GTEx_V8_eQTL_tissue
tissue type of the expression data with which the eQTL/gene pair is detected
No histogram: Can not merge categorical histograms; too many unique values 112
GTEx_V8_sQTL_gene
target gene of the (significant) sQTL SNP
No histogram: Can not merge categorical histograms; too many unique values 104
GTEx_V8_sQTL_tissue
tissue type of the expression data with which the sQTL/gene pair is detected
No histogram: Can not merge categorical histograms; too many unique values 101
eQTLGen_snp_id
id of the eQTL SNP
No histogram: Can not merge categorical histograms; too many unique values 117
eQTLGen_gene_id
id of the target gene of the (significant) eQTL SNP
No histogram: Can not merge categorical histograms; too many unique values 102
eQTLGen_gene_symbol
symbol of the target gene of the (significant) eQTL SNP
No histogram: Can not merge categorical histograms; too many unique values 102
eQTLGen_cis_or_trans
eQTL type, cis or trans
Geuvadis_eQTL_target_gene
Ensembl gene ID of the eQTL associated with, from the Geuvadis project 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)
No histogram: Can not merge categorical histograms; too many unique values 107
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
