EVE missense variant effect scores for the HGF locus (chr7, GRCh38/hg38). Each row is an amino acid substitution; each column is a protein position. Hovering over a cell shows the substitution and EVE score.
We would like to thank Andrew Smith at the University of Southern California, who contributed the original implementation of this interface, and Jonathan Casper, who developed it into the version released at the UCSC Genome Browser. We also thank Lou Nassar, Gerardo Perez, Clay Fischer, Brian Raney, Max Haeussler, and Jairo Navarro for testing, feedback, and documentation.
-We are pleased to announce the release of two new proteome-wide missense variant effect prediction tracks for hg38: -popEVE and -EVE. +EVE and +popEVE. Both are deep generative models that predict variant pathogenicity by learning patterns of natural sequence variation across species, without relying on clinical labels.
-EVE (Evolutionary model of Variant Effect) is a -deep generative model that predicts the pathogenicity of missense variants by learning patterns of -natural sequence variation across thousands of species, without relying on clinical labels. +EVE +(Evolutionary model of Variant Effect) is a deep generative model that +predicts the pathogenicity of missense variants by learning patterns of natural sequence variation +across thousands of species, without relying on clinical labels. Pre-computed scores are provided for all possible missense substitutions across 2,949 disease-associated human proteins.
Scores range from 0 to 1, with higher values indicating a greater predicted likelihood that a variant is disease-relevant. As with any pathogenicity prediction score, EVE is intended as supporting evidence rather than a stand-alone classifier.
Each track entry spans one protein at its genomic locus. The heatmap columns correspond to individual amino acid positions, placed at the codon's genomic coordinate, and the rows correspond to the 20 standard amino acids, ordered by amino acid class. Each cell shows the EVE score for substituting the wildtype amino acid at that position with the row amino acid. Empty cells indicate the wildtype amino acid at a given position, or positions for which no score is available.
EVE missense variant effect scores for the HGF locus (chr7, GRCh38/hg38). Each row is an amino acid substitution; each column is a protein position. Hovering over a cell shows the substitution and EVE score.
Items in this track are colored according to score:
Note: Zoom in to base level to see the full amino-acid heatmap with per-substitution scores on mouseover. At wider zoom levels, the track switches to displaying a density graph.
-popEVE builds on EVE by combining its -evolutionary signal with predictions from the ESM-1v protein language model and human population -variation from the UK Biobank. A key difference is that EVE scores are calibrated separately -within each protein, whereas popEVE scores are calibrated across the entire proteome. That means a -popEVE score in one gene can be compared directly to a popEVE score in a completely different -gene. This is useful when prioritizing which of several candidate variants across different genes -is most likely to be damaging. The track provides popEVE scores for missense substitutions across -roughly 18,000 human proteins. +popEVE builds +on EVE by combining its evolutionary signal with predictions from the ESM-1v protein language +model and human population variation from the UK Biobank. A key difference is that EVE scores are +calibrated separately within each protein, whereas popEVE scores are calibrated across the entire +proteome. That means a popEVE score in one gene can be compared directly to a popEVE score in a +completely different gene. This is useful when prioritizing which of several candidate variants +across different genes is most likely to be damaging. The track provides popEVE scores for +missense substitutions across roughly 18,000 human proteins.
popEVE scores are continuous, with lower, more negative values indicating greater predicted deleteriousness. The authors define approximately −5.056 as a severe, high-confidence deleterious threshold and −4.617 as a moderate threshold. Because the scores are calibrated across the proteome, they can be compared directly between genes.
Each track item represents a protein at its genomic locus and is displayed as a heatmap. Columns correspond to amino acid positions, while rows represent possible amino acid substitutions. Each cell shows the popEVE score for that substitution.
Items are colored according to score:
Colors are interpolated between these values on a single proteome-wide gradient. As with other computational variant-effect predictors, popEVE is intended to provide supporting evidence for variant interpretation rather than serve as a stand-alone clinical classifier.
popEVE missense deleteriousness scores for all possible amino acid substitutions in the SCN10A gene at chr3, GRCh38/hg38, where colors indicate predicted severity from severe (red) to tolerated (blue).
-We would like to thank Mafalda Dias, Jonathan Frazer, Debora S. Marks, Rose Orenbuch, and -colleagues at Harvard Medical School, the Centre for Genomic Regulation, and collaborating -institutions for developing popEVE and making the scores publicly available at -pop.evemodel.org, and Jonathan Frazer, -Pascal Notin, Mafalda Dias, and Debora S. Marks at Harvard Medical School, along with Yarin Gal at -the University of Oxford, for making the EVE scores publicly available at -evemodel.org. Lou Nassar and Max Haeussler -developed these tracks, with QA by Jairo Navarro, Barali Kitiyakara, and Eliza Alde. +We would like to thank Jonathan Frazer, Pascal Notin, Mafalda Dias, and Debora S. Marks at +Harvard Medical School, along with Yarin Gal at the University of Oxford, for making the EVE +scores publicly available at evemodel.org, and +Mafalda Dias, Jonathan Frazer, Debora S. Marks, Rose Orenbuch, and colleagues at Harvard Medical +School, the Centre for Genomic Regulation, and collaborating institutions for developing popEVE +and making the scores publicly available at +pop.evemodel.org. Lou Nassar and Max +Haeussler developed these tracks, with QA by Jairo Navarro, Barali Kitiyakara, and Eliza Alde.
We are excited to announce the updated Genome Aggregation Database (gnomAD) v4.1.1 tracks for human assembly hg38/GRCh38, and new gnomAD Missense Deleteriousness Prediction by Constraint (MPC) tracks, found in the gnomAD superTrack. The tracks are: