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/mavemdMap.html src/hg/makeDb/trackDb/human/hg38/mavemdMap.html index 06f6e3d1288..24445f0410e 100644 --- src/hg/makeDb/trackDb/human/hg38/mavemdMap.html +++ src/hg/makeDb/trackDb/human/hg38/mavemdMap.html @@ -34,32 +34,32 @@ <p> One calibration colors a whole map, so its cells can be compared with each other. Where MaveDB designates no primary calibration for a score set, the one that classifies the most of its variants is used. Cells carry the ACMG/AMP functional evidence code on the same scale as the MaveMD Variants track: </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> @@ -80,31 +80,31 @@ <p> The item name filter takes a regular expression matched against the gene symbol and the MaveDB score set identifier, which is how to narrow the display to one score set. Each item's details carry that score set's assay metadata: what it measured, in what model system, and how its variant library was built. </p> <h2>Methods</h2> <p> MaveMD curates MaveDB score sets for clinical relevance and annotates them with the metadata a laboratory needs to judge whether an assay supports a variant classification (McEwen <em>et al.</em>). A calibration divides a score set's score range into functional classes; where those classes were compared against variants of known clinical significance, the calibration also carries an ACMG/AMP evidence strength derived from the odds of pathogenicity, -following the ClinGen recommendations for the PS3/BS3 criterion (Brnich <em>et al.</em>). +following the ClinGen recommendations for the PS3/BS3 criterion (Brnich <em>et al.</em>, 2019). </p> <p> Data are downloaded from the <a href="https://api.mavedb.org" target="_blank">MaveDB API</a>, one request per score set. Each measurement is placed by resolving its protein accession to a transcript and walking that transcript's coding bases to the requested codon, through RefSeq for RefSeq accessions and GENCODE for Ensembl ones. Columns are ordered by genomic coordinate, so a gene on the minus strand reads from its C terminus to its N terminus, and a codon split across an exon junction is drawn on the longest contiguous run of its bases. </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 in the @@ -138,57 +138,56 @@ <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. The heatmap display was built by Jonathan Casper for the MaveDB track. </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>