b7b279e5f1240419fb3a408fff5c82a998a36e76
max
  Wed Jun 3 08:17:09 2026 -0700
EVE track QA fixes: fix .as field descriptions, clarify protein count in HTML

- thickStart/thickEnd .as descriptions corrected (whole protein span, not start/stop codon)
- reserved .as description corrected (always 0, not itemRgb)
- HTML Methods section: explain that 2,951 of 3,219 proteins have released VCF scores

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

diff --git src/hg/makeDb/trackDb/human/eve.html src/hg/makeDb/trackDb/human/eve.html
index 1ae02d9f474..294e9ab26c5 100644
--- src/hg/makeDb/trackDb/human/eve.html
+++ src/hg/makeDb/trackDb/human/eve.html
@@ -1,122 +1,123 @@
 <h2>Description</h2>
 <p>
 Missense mutations change a single amino acid in a protein and make up a large fraction
 of the variants observed in human populations. Most have no known clinical significance,
 both because clinical data are limited and because the relationship between sequence change
 and protein function is complex. Computational approaches that model evolutionary
 conservation across species can estimate how much a given position tolerates change, since
 residues critical to function tend to be highly conserved. EVE (Evolutionary model of
 Variant Effect) formalizes this reasoning with a deep generative model trained entirely on
 natural sequence variation, without any reliance on clinical labels. This track shows EVE
 scores for all possible missense substitutions in 2,949 disease-associated proteins.
 </p>
 
 <h2>Display Conventions</h2>
 <p>
 Each entry spans one protein at its genomic locus. The heatmap columns correspond to
 individual amino acid positions in the protein, placed at the codon's genomic coordinate.
 The rows correspond to the 20 standard amino acids (A&ndash;Y, alphabetical). 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 (no
 substitution) or positions for which no score is available.
 </p>
 
 <p>
 Cells are colored on a gradient:
 </p>
 <p>
 <span style="display:inline-block; background-color:#2166ac; width:18px; height:12px; vertical-align:middle;"></span>
 <b>EVE &asymp; 0 &mdash; benign:</b> the substitution is well-tolerated in evolutionary sequence variation<br>
 <span style="display:inline-block; background-color:#f7f7f7; width:18px; height:12px; vertical-align:middle; border:1px solid #ccc;"></span>
 <b>EVE &asymp; 0.5 &mdash; uncertain:</b> the model cannot confidently classify the variant<br>
 <span style="display:inline-block; background-color:#d6604d; width:18px; height:12px; vertical-align:middle;"></span>
 <b>EVE &asymp; 1 &mdash; pathogenic:</b> the substitution is rare or absent across evolutionary sequences
 </p>
 
 <p>
 Hovering over a cell shows the wildtype amino acid, the protein position, the variant amino
 acid, the EVE score, and the Class25 classification (benign, uncertain, or pathogenic using
 a 25% uncertainty threshold).
 </p>
 
 <p>
 For reverse-strand genes, protein positions are displayed left to right in genomic
 order (C-terminus to N-terminus on the screen), consistent with the standard genome
 browser orientation.
 </p>
 
 <h2>Methods</h2>
 <p>
 EVE trains a Bayesian variational autoencoder (VAE) separately for each of 3,219
-disease-associated human proteins. For each protein, a multiple sequence alignment is
+disease-associated human proteins; of these, 2,951 have missense VCF scores in the
+public bulk download (the remainder have sequence alignments but no released scores). For each protein, a multiple sequence alignment is
 retrieved by searching roughly 250 million protein sequences from UniRef, and the VAE
 learns the distribution of amino acid sequences across species, capturing both
 per-position conservation and co-evolutionary dependencies between positions. An
 evolutionary index for each single amino acid variant is then computed as the
 approximate negative log-likelihood ratio of the variant versus the wildtype sequence,
 estimated by sampling from the VAE posterior (ensembled over five independently trained
 models). A global-local mixture of Gaussian mixture models, fit to the index distributions
 across all variants and all proteins, converts this continuous index to an EVE score
 between 0 (benign) and 1 (pathogenic) and assigns each variant to a benign, uncertain, or
 pathogenic class. The uncertainty of each classification reflects the predictive entropy of
 the mixture model, and a threshold on this entropy controls what fraction of variants is
 labeled uncertain. The Class25 field used in the track mouseovers classifies variants using
 a 25% uncertainty threshold, which the authors report yields approximately 90% accuracy on
 known ClinVar labels. See Frazer et al. 2021 for full details.
 </p>
 
 <p>
 The data were downloaded as a bulk archive from
 <a href="https://evemodel.org/download/bulk" target="_blank">https://evemodel.org/download/bulk</a>.
 The archive contains one VCF file per protein, each listing every possible missense
 substitution with its EVE score and per-threshold classifications. Multiple VCF records
 encoding different codon changes for the same amino acid substitution carry identical EVE
 scores and were deduplicated to one record per substitution. Records were converted to
 heatmap bigBed format using a custom Python script; full processing instructions are in the
 <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/eve.txt"
 target="_blank">makedoc file</a>, and the conversion script is available in
 <a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/eve"
 target="_blank">our GitHub repository</a>.
 Two proteins (G6PT1, UniProt O43826; and MAFIP, Q8WZ33) were excluded because their
 VCF coordinates mapped to assembly scaffolds (chrCHR_HG2217_PATCH and chrGL000194.1)
 absent from the standard hg38 assembly. The remaining 2,949 proteins covering approximately
 1.7 million amino acid positions are included in this track.
 </p>
 
 <h2>Data Access</h2>
 <p>The data can be explored interactively in table format with the
 <a href="../cgi-bin/hgTables">Table Browser</a> or the
 <a href="../cgi-bin/hgIntegrator">Data Integrator</a> and exported from there to
 spreadsheet or tab-separated tables. From scripts, the data can be accessed through our
-<a href="https://api.genome.ucsc.edu">API</a>, track=<i>eve</i>.</p>
+<a href="https://api.genome.ucsc.edu" target="_blank">API</a>, track=<i>eve</i>.</p>
 <p>For automated download and analysis, the genome annotation is stored in a bigBed file
 that can be downloaded from
 <a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/eve" target="_blank">our download
 server</a>. The file for this track is called <tt>eve.bb</tt>. Individual regions or the
 whole genome annotation can be obtained using our tool <tt>bigBedToBed</tt>, which can be
 compiled from the source code or downloaded as a precompiled binary for your system.
 Instructions for downloading source code and binaries can be found
-<a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads">here</a>.
+<a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads" target="_blank">here</a>.
 The tool can also be used to obtain features within a given range, e.g.
 <tt>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/eve/eve.bb -chrom=chr17
 -start=43000000 -end=43200000 stdout</tt></p>
 <p>The original annotation source data can be downloaded from
 <a href="https://evemodel.org/download/bulk" target="_blank">https://evemodel.org/download/bulk</a>.</p>
 
 <h2>Credits</h2>
 <p>
 Thanks to Jonathan Frazer, Pascal Notin, Mafalda Dias, and Debora S. Marks at Harvard
 Medical School and Yarin Gal at the University of Oxford for making the EVE scores
 publicly available at
 <a href="https://evemodel.org/" target="_blank">evemodel.org</a>.
 </p>
 
 <h2>References</h2>
 <p>
 Frazer J, Notin P, Dias M, Gomez A, Min JK, Brock K, Gal Y, Marks DS.
 <a href="https://doi.org/10.1038/s41586-021-04043-8" target="_blank">
 Disease variant prediction with deep generative models of evolutionary data</a>.
 <em>Nature</em>. 2021 Nov;599(7883):91-95.
 PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/34707284" target="_blank">34707284</a>
 </p>