824df26b6320b692d629566c5a10b15004da82ce lrnassar Tue Sep 29 16:09:00 2026 -0700 addProteinSequence in mavemdLib translates each transcript's CDS from hg38.2bit so makeMaveMdVariants can check every projected codon against the reference residue its own HGVS term asserts; the existing comparison against MaveDB's genomic mapping only reaches the 3% of projected items that carry both terms, because 18 of the 40 protein accessions have no genomic-route variants at all. 39 of 40 accessions match at 0.000%; NP_689629.2 (FKRP) has 99 nonsense terms numbered one codon downstream of their own reference residue, which still reach mavemdVar through MaveDB's genomic mapping but are dropped from mavemdMap, which places columns from the protein term and has no fallback. The haplotype test now also reads hgvs_nt, since PTEN 00000054-a-1 states 1,236 haplotypes as c.[1207G>T;1209C>T] with no protein term and they were counted as rejected submissions, making both figures in the makeDoc wrong. assayLine runs the heatmap legend through asciiText because bedField turns the en dash in three MaveDB titles into – and the legend is drawn as raster text; clinGenId links to by_canonicalid rather than /allele, which serves JSON to a browser, matching human/civic.ra; the generated filter fragment no longer emits the blank line after each group that the makeDoc itself warns ends a stanza; and runBuild.sh tails the log on failure instead of dying silently under set -e. Also reworded the grey legend entry, which said no threshold was reached in either direction but covers 6,656 normal and 145 abnormal items, alphabetized the references, and fixed stale counts in the makeDoc. Caught by Claude review of 29af14b, fcf788d and 97c7de5. refs #38407 refs #37800 diff --git src/hg/makeDb/trackDb/human/hg38/mavemdVar.html src/hg/makeDb/trackDb/human/hg38/mavemdVar.html index 6ebb72a78c4..18818fe790d 100644 --- src/hg/makeDb/trackDb/human/hg38/mavemdVar.html +++ src/hg/makeDb/trackDb/human/hg38/mavemdVar.html @@ -1,187 +1,186 @@ <h2>Description</h2> <p> This track is part of the <a href="hgTrackUi?g=mavemd">MaveMD</a> collection. It shows one item per measured variant per score set, so a variant measured in several experiments appears once for each of them. </p> <p> Each item carries the assay score, the functional class that score falls into, and, where the score set has been calibrated against variants of known clinical significance, the ACMG/AMP functional evidence code that follows: PS3 for evidence of a damaging effect, BS3 for evidence of a normal one, at a strength set by the calibration's odds of pathogenicity following the -ClinGen recommendations for the PS3/BS3 criterion (Brnich <em>et al.</em>). ClinVar +ClinGen recommendations for the PS3/BS3 criterion (Brnich <em>et al.</em>, 2019). ClinVar significance, gnomAD allele frequency and the ClinGen allele ID are attached where they exist. </p> <p> Each item also carries the assay metadata: what the assay measured, in what model system, the molecular mechanism assessed, and how the variant library was built. That last field matters clinically. An assay built on an in vitro construct library introduces a synthetic copy of the target sequence, so it cannot detect an effect on splicing or on nonsense-mediated decay and can read falsely normal for such a variant. An assay that edits the endogenous locus can. </p> <p> Two cautions when comparing variants. Many of the evidence codes come from calibrations MaveDB marks research use only; each item names its calibration and flags this. And the functional score has no common scale or direction between score sets, so a higher score does not always mean a more normal protein. Compare by functional class or evidence code, which mean the same thing everywhere. </p> <h2>Display Conventions and Configuration</h2> <p> Items are colored by the ACMG functional evidence code from the calibration named in the item details. Red shades carry evidence toward pathogenic, blue toward benign, darkening with the strength of the evidence. </p> <table class="stdTbl"> <tr><th style="background-color:#67001f;width:2em"> </th> <td>PS3, very strong</td></tr> <tr><th style="background-color:#b2182b;width:2em"> </th><td>PS3, strong</td></tr> <tr><th style="background-color:#d6604d;width:2em"> </th><td>PS3, moderate plus</td></tr> <tr><th style="background-color:#f4a582;width:2em"> </th><td>PS3, moderate</td></tr> <tr><th style="background-color:#fddbc7;width:2em"> </th><td>PS3, supporting</td></tr> <tr><th style="background-color:#e8e8e8;width:2em"> </th> - <td>Evidence not met: measured and calibrated, but the score reaches no threshold in - either direction</td></tr> + <td>Calibrated, but no ACMG evidence code applies to this variant's functional + class</td></tr> <tr><th style="background-color:#d1e5f0;width:2em"> </th><td>BS3, supporting</td></tr> <tr><th style="background-color:#92c5de;width:2em"> </th><td>BS3, moderate</td></tr> <tr><th style="background-color:#4393c3;width:2em"> </th><td>BS3, moderate plus</td></tr> <tr><th style="background-color:#2166ac;width:2em"> </th><td>BS3, strong</td></tr> <tr><th style="background-color:#053061;width:2em"> </th><td>BS3, very strong</td></tr> </table> <p> Score sets that classify their variants without assigning an ACMG code are a measurement rather than a clinical claim, and use a separate palette: </p> <table class="stdTbl"> <tr><th style="background-color:#762a83;width:2em"> </th> <td>Abnormal function measured, no ACMG evidence code assigned</td></tr> <tr><th style="background-color:#bdbdbd;width:2em"> </th><td>Indeterminate</td></tr> <tr><th style="background-color:#7fbf7b;width:2em"> </th> <td>Normal function measured, no ACMG evidence code assigned</td></tr> <tr><th style="background-color:#d9d9d9;width:2em"> </th> <td>Measured, but no calibration covers this variant</td></tr> </table> <p> Filters are available on the ACMG evidence code, the functional class, the gene, the ClinVar significance and the assay metadata, and none are applied by default. Because every substitution at a codon is a separate item, a well studied gene stacks deeply and the track falls back to a density graph in all but narrow windows; filtering to one gene or one evidence code makes individual variants readable. Item names, ClinGen allele IDs and MaveDB variant identifiers are searchable from the position box. </p> <h2>Methods</h2> <p> MaveMD curates MaveDB score sets for clinical relevance, integrates them with ClinVar and the ClinGen Allele Registry, and exports evidence structured for ACMG/AMP variant classification -(McEwen <em>et al.</em>). Candidates were drawn from MaveDB, from publications cited in ClinVar +(McEwen <em>et al.</em>, 2025). Candidates were drawn from MaveDB, from publications cited in ClinVar for functional evidence, and from community recommendation, then restricted to genes with a moderate or stronger gene-disease association in ClinGen or GenCC. </p> <p> Data are downloaded from the <a href="https://api.mavedb.org" target="_blank">MaveDB API</a>, one request per score set. MaveDB resolves some score sets to the genome and others only to a protein sequence, so a variant is placed from its genomic term where one exists, otherwise by projecting its protein term onto the corresponding codon through RefSeq or GENCODE, otherwise by converting the submitter's transcript term. Haplotypes, several substitutions measured as a single unit, have no one position and are excluded. </p> <p> The build scripts are in the <a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/mavemd" target="_blank">kent source tree</a>, the steps that run them and the counts for each build in the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/mavemd.txt" target="_blank">makeDoc</a>, and the track configuration in <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/trackDb/human/hg38/mavemd.ra" target="_blank">human/hg38/mavemd.ra</a>. </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-sep tables. From scripts, the data can be accessed through our <a href="https://api.genome.ucsc.edu">API</a>, track=<i>mavemdVar</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/$db/mavemd/" target="_blank">our download server</a>. The file for this track is called <tt>mavemdVar.bb</tt>. Individual regions or the whole genome annotation can be obtained using our tool <tt>bigBedToBed</tt>, which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found <a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads">here</a>. The tool can also be used to obtain features within a given range, e.g. <tt>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/$db/mavemd/mavemdVar.bb -chrom=chr17 -start=7668402 -end=7687550 stdout</tt></p> <p>The original annotation source data can be downloaded from the MaveDB API at <a href="https://api.mavedb.org" target="_blank">https://api.mavedb.org</a>.</p> <h2>Credits</h2> <p> Thanks to Alan Rubin, Benjamin Capodanno and Jeremy Stone of the MaveDB team for curating the MaveMD collection and for advice on retrieving it, and to the many groups whose experiments make up the underlying score sets. </p> <h2>References</h2> -<p> -McEwen AE, Stone J, Tejura M, Gupta P, Capodanno BJ, Da EY, Grindstaff SB, Moore N, Reinhart D, -Snyder AE <em>et al</em>. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/41332838" target="_blank"> -MaveMD: A functional data resource for genomic medicine</a>. -<em>medRxiv</em>. 2025 Nov 19;. -PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/41332838" target="_blank">41332838</a>; PMC: <a -href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12668102/" target="_blank">PMC12668102</a> -</p> - -<p> -Rubin AF, Stone J, Bianchi AH, Capodanno BJ, Da EY, Dias M, Esposito D, Frazer J, Fu Y, Grindstaff -SB <em>et al</em>. -<a href="https://www.ncbi.nlm.nih.gov/pubmed/39838450" target="_blank"> -MaveDB 2024: a curated community database with over seven million variant effects from multiplexed -functional assays</a>. -<em>Genome Biol</em>. 2025 Jan 21;26(1):13. -PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/39838450" target="_blank">39838450</a>; PMC: <a -href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753097/" target="_blank">PMC11753097</a> -</p> - <p> Arbesfeld JA, Da EY, Stevenson JS, Kuzma K, Paul A, Farris T, Capodanno BJ, Grindstaff SB, Riehle K, Saraiva-Agostinho N <em>et al</em>. <a href="https://www.ncbi.nlm.nih.gov/pubmed/40563119" target="_blank"> Mapping MAVE data for use in human genomics applications</a>. <em>Genome Biol</em>. 2025 Jun 25;26(1):179. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/40563119" target="_blank">40563119</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188674/" target="_blank">PMC12188674</a> </p> <p> Brnich SE, Abou Tayoun AN, Couch FJ, Cutting GR, Greenblatt MS, Heinen CD, Kanavy DM, Luo X, McNulty SM, Starita LM <em>et al</em>. <a href="https://www.ncbi.nlm.nih.gov/pubmed/31892348" target="_blank"> Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework</a>. <em>Genome Med</em>. 2019 Dec 31;12(1):3. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/31892348" target="_blank">31892348</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6938631/" target="_blank">PMC6938631</a> </p> +<p> +McEwen AE, Stone J, Tejura M, Gupta P, Capodanno BJ, Da EY, Grindstaff SB, Moore N, Reinhart D, +Snyder AE <em>et al</em>. +<a href="https://www.ncbi.nlm.nih.gov/pubmed/41332838" target="_blank"> +MaveMD: A functional data resource for genomic medicine</a>. +<em>medRxiv</em>. 2025 Nov 19;. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/41332838" target="_blank">41332838</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12668102/" target="_blank">PMC12668102</a> +</p> + +<p> +Rubin AF, Stone J, Bianchi AH, Capodanno BJ, Da EY, Dias M, Esposito D, Frazer J, Fu Y, Grindstaff +SB <em>et al</em>. +<a href="https://www.ncbi.nlm.nih.gov/pubmed/39838450" target="_blank"> +MaveDB 2024: a curated community database with over seven million variant effects from multiplexed +functional assays</a>. +<em>Genome Biol</em>. 2025 Jan 21;26(1):13. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/39838450" target="_blank">39838450</a>; PMC: <a +href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753097/" target="_blank">PMC11753097</a> +</p>