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
@@ -1,70 +1,73 @@
 <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 &minus;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 &minus;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 &ldquo;50 bp rule&rdquo;)</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.