b86eab362ce697c350764ffe438ccdba8829e0f3 gperez2 Mon Jul 20 17:37:35 2026 -0700 Fixing the NMDetective-A/B score-range text (0 to 1, not -1 to +1), updating the citation to Lindeboom et al. 2019, and changing viewLimits to -0.3:1.5 on all four NMDetective subtracks. refs #37843 diff --git src/hg/makeDb/trackDb/human/hg38/nmdDetective.html src/hg/makeDb/trackDb/human/hg38/nmdDetective.html index 10bcc67b28a..d98aa28f542 100644 --- src/hg/makeDb/trackDb/human/hg38/nmdDetective.html +++ src/hg/makeDb/trackDb/human/hg38/nmdDetective.html @@ -1,124 +1,127 @@ <h2>Description</h2> <p> The <b>NMDetective</b> tracks display genome-wide predictions of nonsense-mediated mRNA -decay (NMD) efficiency from +decay (NMD) efficiency using the NMDetective-A and NMDetective-B models from +<a href="https://www.ncbi.nlm.nih.gov/pubmed/31659324" target="_blank">Lindeboom et al. 2019</a>, +trained on the NMD efficiency measure from <a href="https://www.ncbi.nlm.nih.gov/pubmed/27618451" target="_blank">Lindeboom et al. 2016</a>. NMDetective scores predict whether a premature termination codon (PTC) at a given position will trigger NMD and mRNA degradation, or whether the transcript will escape NMD and potentially produce a truncated protein. </p> <p> -Scores range from approximately −1 to +1. Positive values indicate that a PTC at -that position is predicted to trigger NMD (the mRNA is degraded). Negative values indicate +Scores range from 0 to 1. Values near 1 indicate that a PTC at +that position is predicted to trigger NMD (the mRNA is degraded). Values near 0 indicate that the PTC is predicted to escape NMD (the truncated mRNA may be translated into an -aberrant protein). Values near zero indicate intermediate or uncertain NMD efficiency. +aberrant protein). Values in between indicate intermediate NMD efficiency. </p> <h3>Subtracks</h3> <table class="descTbl"> <tr><th>Track</th><th>Description</th></tr> <tr><td><b>NMDetective-A</b></td> <td>Random forest model predicting NMD efficiency for all possible PTCs introduced by single-nucleotide variants. Explains ~71% of systematic variance in NMD efficiency.</td></tr> <tr><td><b>NMDetective-B</b></td> <td>Simplified decision tree model for all possible PTCs. Slightly lower accuracy (~68% variance explained) but more interpretable, making it suitable for clinical applications.</td></tr> <tr><td><b>NMDetective-A PTC</b></td> <td>Random forest model predicting NMD efficiency specifically for the first out-of-frame PTC introduced by frameshifting indel mutations.</td></tr> <tr><td><b>NMDetective-B PTC</b></td> <td>Decision tree model for the first out-of-frame PTC from frameshifting indels.</td></tr> </table> <h2>Display Conventions and Configuration</h2> <p> -Each subtrack is displayed as a signal (bigWig) track. By default, the vertical axis -ranges from −1 to +1. Regions with positive values (predicted NMD-triggering) are -shown above the baseline; regions with negative values (predicted NMD escape) are shown -below. +Each subtrack is displayed as a signal (bigWig) track. Values closer to 1 indicate +predicted NMD-triggering, while values closer to 0 indicate predicted NMD escape. </p> <ul> <li><font color="#0080FF"><b>Blue tracks</b></font> (NMDetective-A and -B): predictions for all possible PTCs from single-nucleotide nonsense variants.</li> <li><font color="#009966"><b>Green tracks</b></font> (NMDetective-A PTC and -B PTC): predictions for the first out-of-frame PTC from frameshifting indels.</li> </ul> <h2>Methods</h2> <p> -The NMDetective models were trained on somatic nonsense mutation data from 9,769 cancer -patients and validated with frameshift mutations and germline variants -(<a href="https://www.ncbi.nlm.nih.gov/pubmed/31659324" target="_blank">Lindeboom et al. 2019</a>). +<b>NMDetective-A</b> and <b>NMDetective-B</b> were introduced in +<a href="https://www.ncbi.nlm.nih.gov/pubmed/31659324" target="_blank">Lindeboom et al. 2019</a>, +trained on NMD efficiency scores derived from somatic nonsense mutation data from 9,769 cancer +patients +(<a href="https://www.ncbi.nlm.nih.gov/pubmed/27618451" target="_blank">Lindeboom et al. 2016</a>), +and tested on an independent set of frameshift mutations. The models incorporate the following features to predict NMD efficiency: </p> <ul> <li>Whether the PTC falls in the last exon</li> <li>Distance to the last 50 nt of the penultimate exon (the EJC-based “50 bp rule”)</li> <li>Distance from the coding start (start-proximal NMD insensitivity)</li> <li>Exon length</li> <li>mRNA half-life</li> <li>Distance to the downstream exon-junction complex</li> <li>Distance to the wild-type stop codon</li> </ul> <p> <b>NMDetective-A</b> (random forest regression) captures non-linear interactions among these features and achieves the highest predictive accuracy. <b>NMDetective-B</b> (decision tree) applies a simpler rule-based classification that is more transparent, with a modest reduction in accuracy. </p> <p> The predictions were generated for every possible PTC-introducing single-nucleotide variant and for the first out-of-frame PTC from every possible single-nucleotide frameshifting indel across all human protein-coding transcripts. The original bedGraph custom track files were downloaded from the <a href="https://figshare.com/articles/dataset/NMDetective/7803398" target="_blank">NMDetective Figshare page</a> resource and converted to bigWig format at UCSC. </p> <h2>Data Access</h2> <p> The data underlying these tracks can be explored interactively with the <a href="../cgi-bin/hgTables">Table Browser</a> or the <a href="../cgi-bin/hgIntegrator">Data Integrator</a>. For automated analysis, the data may be queried from our <a href="/goldenPath/help/api.html">REST API</a>. Please refer to our <a href="https://groups.google.com/a/soe.ucsc.edu/forum/#!forum/genome" target="_blank">mailing list archives</a> for questions, or our <a href="../FAQ/FAQdownloads.html#download36">Data Access FAQ</a> for more information. </p> <h2>Credits</h2> <p> Thanks to Rik Lindeboom for providing custom tracks and the original NMDetective data on <a href="https://figshare.com/articles/dataset/NMDetective/7803398" target="_blank">Figshare</a>. </p> <h2>References</h2> <p> Lindeboom RG, Supek F, Lehner B. <a href="https://doi.org/10.1038/ng.3664" target="_blank"> The rules and impact of nonsense-mediated mRNA decay in human cancers</a>. <em>Nat Genet</em>. 2016 Oct;48(10):1112-8. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/27618451" target="_blank">27618451</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5045715/" target="_blank">PMC5045715</a> </p> <p> Lindeboom RGH, Vermeulen M, Lehner B, Supek F. <a href="https://doi.org/10.1038/s41588-019-0517-5" target="_blank"> The impact of nonsense-mediated mRNA decay on genetic disease, gene editing and cancer immunotherapy</a>. <em>Nat Genet</em>. 2019 Nov;51(11):1645-1651. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/31659324" target="_blank">31659324</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858879/" target="_blank">PMC6858879</a> </p>