31b7d4342181171f8b8271e5ed5b5cdaa22feeb6
max
  Wed Apr 1 07:30:30 2026 -0700
fixing up regfunc docs and tdb

diff --git src/hg/makeDb/trackDb/human/hg38/regfunc.html src/hg/makeDb/trackDb/human/hg38/regfunc.html
index 94f0ba80ca3..940a9f0bb03 100644
--- src/hg/makeDb/trackDb/human/hg38/regfunc.html
+++ src/hg/makeDb/trackDb/human/hg38/regfunc.html
@@ -1,62 +1,65 @@
 <h2>Description</h2>
 <p>
-Massively Parallel Reporter Assays (MPRAs) are high-throughput experimental methods
-that test thousands of DNA sequences or genetic variants for their effects on gene
-regulation. They work by linking candidate regulatory sequences to reporter genes
-and measuring transcriptional output using sequencing.
+Regulatory functional assays are methods that directly test whether specific
+DNA sequences control gene expression - such as by acting as enhancers,
+promoters, silencers, or other regulatory elements — by measuring their effect
+on transcription in cells. Among these, Massively Parallel Reporter Assays
+(MPRAs) are high-throughput experimental methods that test thousands of DNA
+sequences or genetic variants for their effects on gene
+regulation by measuring transcriptional output using sequencing.
 </p>
 <p>
 This track collection brings together results from two MPRA databases, one for the complete sequence fragments, 
 one for the variants in selected fragments:
 </p>
 
 <ul>
 <li><b><a href="hgTrackUi?g=mprabase">MPRA Base</a></b> &mdash;
 41,275 experimentally tested cis-regulatory elements from 51 MPRA, STARR-seq,
 and related reporter assay experiments, curated in the MPRA Base database
 (<a href="https://pubmed.ncbi.nlm.nih.gov/38045264/" target="_blank">Zhao et al., 2023</a>).
 </li>
 <li><b><a href="hgTrackUi?g=mpraVarDb">MPRAVarDB</a></b> &mdash;
 242,818 variants from 18 MPRA studies, tested for effects on transcriptional
 regulatory activity across over 30 cell lines and 30 human diseases and traits
 (<a href="https://pubmed.ncbi.nlm.nih.gov/38617248/" target="_blank">Wang et al., 2024</a>).
 </li>
 </ul>
 
 <h2>Data Access</h2>
 <p>
 See the individual subtrack documentation pages linked above for detailed information
 on how to download and intersect the annotations.
 </p>
 
 <h2>Credits</h2>
 <p>
 Thanks to Tao Wang and colleagues at the University of Florida for
 <a href="https://mpravardb.rc.ufl.edu/" target="_blank">MPRAVarDB</a>,
 and to Varda Singhal and the
 <a href="https://pharm.ucsf.edu/ahituv" target="_blank">Ahituv Lab</a>
 at the University of California San Francisco for
 <a href="http://mprabase.ucsf.edu/app/mprabase" target="_blank">MPRA Base</a>.
 </p>
 
 <h2>References</h2>
 <p>
 Wang T, Matreyek KA, Yang X.
 <a href="https://pubmed.ncbi.nlm.nih.gov/38617248/" target="_blank">
 MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants using MPRA data</a>.
 <em>Bioinformatics</em>. 2024 Apr 15;40(4):btae201.
 PMID: <a href="https://pubmed.ncbi.nlm.nih.gov/38617248/" target="_blank">38617248</a>;
 PMC: <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11014600/" target="_blank">PMC11014600</a>
 </p>
 
 
 <p>
 Zhao J, Baltoumas FA, Konnaris MA, Mouratidis I, Liu Z, Sims J, Agarwal V, Pavlopoulos GA,
 Georgakopoulos-Soares I, Ahituv N.
 <a href="https://doi.org/10.1101/2023.11.19.567742" target="_blank">
 MPRAbase: A Massively Parallel Reporter Assay Database</a>.
 <em>bioRxiv</em>. 2023 Nov 22;.
 PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/38045264" target="_blank">38045264</a>; PMC: <a
 href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10690217/" target="_blank">PMC10690217</a>
 </p>