383da828477aad2b3c6053880a64fdbfc2a00cd9
max
  Thu Mar 19 02:30:41 2026 -0700
Fix varFreqs HTML issues and trexplorer citation, from AI code review 2026-03-19, refs #36642

Fix broken $db download URLs to hg38 in 14 HTML files, correct "Japanese"
to "Korean" in kova.html, fix "area" typo in schema.html, fix "Finnland"
to "Finland" in varFreqs.ra, normalize GREGoR capitalization, fix grammar,
quote all target=_blank attributes, capitalize GitHub consistently, and
fix bioRxiv citation formatting in trexplorer.html.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

diff --git src/hg/makeDb/trackDb/human/swefreq.html src/hg/makeDb/trackDb/human/swefreq.html
index 637bf7c416d..965b6219283 100644
--- src/hg/makeDb/trackDb/human/swefreq.html
+++ src/hg/makeDb/trackDb/human/swefreq.html
@@ -31,32 +31,32 @@
 indexed with samtools v0.1.19 and assessed with qualimap v2.2.20; per-sample alignments from
 multiple lanes and flow cells were merged using Picard MergeSamFiles v1.120. Processing followed
 GATK best practices with GATK v3.3, including indel realignment (RealignerTargetCreator,
 IndelRealigner), duplicate marking (Picard MarkDuplicates v1.120), and base quality score
 recalibration (BaseRecalibrator), producing one finalized BAM per sample. Per-sample gVCFs were
 generated with GATK HaplotypeCaller v3.3 using reference files from the GATK v2.8 resource bundle,
 with all steps coordinated via Piper v1.4.0. Joint genotyping of 1,000 samples was performed by
 merging gVCFs in five batches of 200 using GATK CombineGVCFs, followed by cohort genotyping with
 GATK GenotypeGVCFs and variant quality score recalibration for SNVs and indels using
 VariantRecalibrator and ApplyRecalibration.
 </p>
 <p>
 At UCSC, the hg38 VCF was downloaded from
 <a href="https://swefreq.nbis.se/dataset/SweGen/download" target="_blank">SweFreq</a> and loaded as-is.
 The file that we use is swegen_frequencies_fixploidy_GRCh38_20190204.vcf.gz.
-We provide documentation that indicates how all source files of the varFreqs track were converted in the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/varFreqs.txt" target=_blank>makeDoc file</a> of the track.
-For some tracks, python scripts were necessary and are also available from <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/scripts/varFreqs" target=_blank>Github</a>.
+We provide documentation that indicates how all source files of the varFreqs track were converted in the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/varFreqs.txt" target="_blank">makeDoc file</a> of the track.
+For some tracks, python scripts were necessary and are also available from <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/scripts/varFreqs" target="_blank">GitHub</a>.
 </p>
 
 <h2>Credits</h2>
 <p>
 The SweGen allele frequency data was generated by Science for Life Laboratory. 
 Any redistributed data derived from the SweGen data set must follow the SweGen terms and conditions.
 The data may not be used to attempt to identify any individual in this or other studies.
 Thanks to the SweGen patients and SciLifeLab for making the data available.
 </p>
 
 <h2>References</h2>
 <p>
 Ameur A, Dahlberg J, Olason P, Vezzi F, Karlsson R, Martin M, Viklund J, K&auml;h&auml;ri AK,
 Lundin P, Che H <em>et al</em>.
 <a href="https://doi.org/10.1038/ejhg.2017.130" target="_blank">