f57e872b724de4bb82b14f07db837aeed4f5174a
gperez2
  Wed Jun 17 03:55:08 2026 -0700
Fix commas and update wording in varFreqs description pages. refs #37733

diff --git src/hg/makeDb/trackDb/human/varFreqsAffected.html src/hg/makeDb/trackDb/human/varFreqsAffected.html
index cd7631d1313..53bec716f0a 100644
--- src/hg/makeDb/trackDb/human/varFreqsAffected.html
+++ src/hg/makeDb/trackDb/human/varFreqsAffected.html
@@ -3,65 +3,65 @@
 This track shows small variants (SNVs and short indels) that were observed in
 <b>affected or case individuals</b> of disease-study cohorts, annotated with their
 predicted protein consequence and colored by severity. It is one half of a matched pair:
 the companion
 <a href="hgTrackUi?g=varFreqsBackground">Population reference</a> track shows the same
 kind of variants seen in population reference cohorts and in unaffected relatives or
 controls. Displaying the two together lets you compare, for example, how often a
 loss-of-function variant in a gene of interest is seen in affected individuals versus the
 general/unaffected background. For the full list of contributing projects, see the
 <a href="hgTrackUi?g=varFreqs">SNV Frequencies</a> collection page.
 </p>
 <p>
 The affected counts are drawn from the affected or case arm of five disease-study cohorts:
 SFARI SPARK WES and SFARI SPARK WGS (autism spectrum disorder probands), SCHEMA
 (schizophrenia cases), GREGoR (affected rare-disease participants), and GA4K (a pediatric
-rare-disease cohort). For SPARK, SFARI WGS, SCHEMA, and GREGoR the source data carries an
-explicit affected/unaffected (or case/control) label and only the affected arm feeds this
+rare-disease cohort). For SPARK, SFARI WGS, SCHEMA, and GREGoR, the source data carries an
+explicit affected/unaffected (or case/control) label, and only the affected arm feeds this
 track. GA4K reports a single cohort-wide frequency with no per-individual label; because it
-is a rare-disease cohort it is counted as affected here, with the caveat that it enrolls
+is a rare-disease cohort, it is counted as affected here, with the caveat that it enrolls
 parent-child trios, so a minority of its carriers are unaffected parents. Genotyping-array
 cohorts are not included in either track.
 </p>
 
 <h2>Display Conventions</h2>
 <h3>Color by Consequence</h3>
 <p>Variants are colored by their most severe predicted consequence:</p>
 <table class="stdTbl">
 <tr><th>Color</th><th>Consequence class</th><th>Examples</th></tr>
 <tr><th style="background-color:#FF0000;width:2em">&nbsp;</th>
     <td>Protein-truncating / loss-of-function</td>
     <td>stop_gained, frameshift, splice_donor, splice_acceptor, stop_lost, start_lost</td></tr>
 <tr><th style="background-color:#1F77B4;width:2em">&nbsp;</th>
     <td>Missense / in-frame</td>
     <td>missense, inframe_insertion, inframe_deletion, protein_altering</td></tr>
 <tr><th style="background-color:#008000;width:2em">&nbsp;</th>
     <td>Synonymous</td>
     <td>synonymous, stop_retained</td></tr>
 <tr><th style="background-color:#808080;width:2em">&nbsp;</th>
     <td>Non-coding / intergenic</td>
     <td>intron, non_coding, intergenic, UTR</td></tr>
 </table>
 <p>
 The score (used for shading) is the pooled affected/case allele frequency times 1000.
 </p>
 
 <h3>Pooled allele frequency</h3>
 <p>
 <b>Affected AF</b> is the pooled rate across contributing affected arms:
 <code>affectedAF = sum(AC) / sum(AN)</code>, where <b>affectedAC</b> sums the allele counts
-and <b>affectedAN</b> sums the allele numbers across each cohort/arm that ships both AC and
+and <b>affectedAN</b> sums the allele numbers across each cohort/arm that provides both AC and
 AF (the per-arm AN is derived as <code>round(AC / AF)</code>). Cohorts that publish only AF
 contribute via a configured <code>default_an</code> in the build configuration. Cohorts
 that publish only AC and have no <code>default_an</code> set (currently GREGoR's per-arm
 AC_AFFECTED/UNAFFECTED/UNKNOWN) are listed in <b>affectedCohorts</b> but do not contribute
 to the pool numerator or denominator; their carriers are visible in the per-database AC
 column instead. The pooled rate is preferred over a max-across-cohorts statistic so a
 small cohort with a high local AF cannot dominate the displayed frequency.
 </p>
 
 <h3>Finding case-enriched loss-of-function variants</h3>
 <p>
 To look for protein-truncating variants that are common in affected individuals but rare
 in the background, set the Consequence filter to Stop Gained, Frameshift, Splice Donor and
 Splice Acceptor (these appear red), then add an upper limit on the
 <b>Background AF</b> filter. Each variant here carries both its affected frequency and its