798b37017a4e1b95f3ccdf7c8b477dfb5446a324
lrnassar
  Fri Jul 24 15:22:34 2026 -0700
lrSv: QA fixes for cardSv/noyvertSv additions - BND filter, makedoc, link targets. refs #37888

Add BND to filterValues.svType on the longReadVariants supertrack and the merged
lrSvAll track (and the lrSvMergeAll.py generator) so the breakend variants that
noyvertSv contributes are filterable. Correct a stale makedoc comment that said
CARD was not in the lrSvAll merge (it is). Add target="_blank" to the API and
hgdownload links in cardSv.html and noyvertSv.html.

diff --git src/hg/makeDb/trackDb/human/cardSv.html src/hg/makeDb/trackDb/human/cardSv.html
index f479b84cf8e..c0894b35822 100644
--- src/hg/makeDb/trackDb/human/cardSv.html
+++ src/hg/makeDb/trackDb/human/cardSv.html
@@ -1,140 +1,140 @@
 <h2>Description</h2>
 <p>
 This track shows structural variants (SVs) identified by Oxford Nanopore
 long-read sequencing of post-mortem brain tissue (prefrontal cortex) from
 351 individuals, generated by the NIH Center for Alzheimer's and Related
 Dementias (NIH CARD) Long-Read Initiative. Structural variants are genomic
 rearrangements larger than about 50 bp, such as deletions, insertions,
 inversions and duplications; because they alter or move large stretches of
 DNA at once they can have outsized effects on gene dosage, gene regulation
 and DNA methylation compared with single-nucleotide changes.
 </p>
 <p>
 The cohort combines two studies: 205 samples of European ancestry from the
 North American Brain Expression Consortium (NABEC, dbGaP phs001300) and 146
 samples of African and African-admixed ancestry from the NIMH Human Brain
 Collection Core (HBCC, dbGaP phs000979). The track contains more than 228,000 SVs called
 against GRCh38: about 127,000 insertions, 102,000 deletions, 431 inversions
 and one tandem duplication. Each record carries the alternate allele count
 overall and split by cohort (NABEC and HBCC), together with the allele frequency
 reported by the source project. None of these samples are Alzheimer's disease
 cases; the cohorts are population brain-tissue collections.
 </p>
 
 <h2>Display Conventions and Configuration</h2>
 <p>
 Items are colored by SV type, matching the other subtracks of the container:
 <ul>
 <li><span style="color: rgb(200,0,0);">Deletions (DEL)</span> - red</li>
 <li><span style="color: rgb(0,0,200);">Insertions (INS)</span> - blue</li>
 <li><span style="color: rgb(0,160,0);">Duplications (DUP)</span> - green</li>
 <li><span style="color: rgb(230,140,0);">Inversions (INV)</span> - orange</li>
 </ul>
 </p>
 <p>
 Insertions are placed at the insertion site with a width of 1 bp, and the
 length of the inserted sequence is shown as the insertion length; deletions,
 inversions and the duplication span the affected reference interval. The
 mouseover shows the variant name, SV type, reference and insertion lengths,
 allele frequency and the alternate allele count split into the NABEC and
 HBCC cohorts. Filters are available for SV type, SV length, insertion length,
 allele count, allele frequency, and the allele count in each cohort.
 </p>
 
 <h2>Methods</h2>
 <p>
 NABEC samples were sequenced on Oxford Nanopore R9.4.1 and HBCC samples on
 R10.4.1 PromethION flow cells, with a median read N50 of 27 kb and about 40x
 average genome coverage. Structural variants were called both from read
 alignments (minimap2 alignments processed with Sniffles2 v2.3) and from
 de novo assemblies (Shasta v0.11.1 assemblies phased with HapDup v0.12 and
 compared to the reference with Hapdiff). Assembly-based calls were merged
 across samples with Truvari, read-based calls were merged across samples with
 Sniffles2, and the read and assembly sets were then merged together and across
 the two cohorts with Truvari. All processing used the Nanopore Analysis
 Pipeline (NAPU) workflows on the AnVIL/Terra platform; see Kolmogorov et al.
 2023 and Billingsley et al. 2024 for details.
 </p>
 <p>
 The display bigBed <tt>NIH_CARD_longReadSVs.bb</tt> was obtained from the NIH
 CARD browser-track
 <a href="https://github.com/meredith705/card_genome_browserTrack" target="_blank">GitHub
 repository</a>. At UCSC it was converted to the shared long-read SV schema
 (signed lengths made positive, an explicit insertion-length field added, the
 single <tt>DUP:TANDEM</tt> call folded to <tt>DUP</tt>, and colors reassigned to
 the container's shared palette) so it matches the other subtracks. The
 step-by-step commands are recorded in the UCSC makeDoc for this track
 container:
 <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/lrSv.txt" target="_blank">
 doc/hg38/lrSv.txt</a>. The conversion script and autoSql schema live in
 <a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/lrSv" target="_blank">
 makeDb/scripts/lrSv</a>, and the track configuration is in
 <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/trackDb/human/lrSv.ra" target="_blank">trackDb/human/lrSv.ra</a>.
 </p>
 
 <h2>Data Access</h2>
 <p>
 The data can be explored interactively in table format with the
 <a href="../cgi-bin/hgTables">Table Browser</a> or the
 <a href="../cgi-bin/hgIntegrator">Data Integrator</a> and exported from there
 to spreadsheet or tab-sep tables. From scripts, the data can be accessed
-through our <a href="https://api.genome.ucsc.edu">API</a>, track=<i>cardSv</i>.
+through our <a href="https://api.genome.ucsc.edu" target="_blank">API</a>, track=<i>cardSv</i>.
 </p>
 <p>
 The annotation is stored as a bigBed file that can be downloaded from
 <a href="http://hgdownload.soe.ucsc.edu/gbdb/hg38/lrSv/" target="_blank">our
 download server</a> as <tt>card.bb</tt>. Individual regions or the whole
 annotation can be obtained with the <tt>bigBedToBed</tt> utility, available
 from our
-<a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads">utilities
+<a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads" target="_blank">utilities
 page</a>. Example:
 <tt>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/lrSv/card.bb -chrom=chr21 -start=0 -end=100000000 stdout</tt>.
 </p>
 <p>
 The underlying genotype-level calls in VCF format are available under
 controlled access through dbGaP (NABEC phs001300, substudy phs003181; HBCC
 phs000979) and can be requested through the AnVIL Data Explorer for the
 <a href="https://explore.anvilproject.org/datasets/0b740f36-28d6-4e02-8165-ad0e9674bbf6" target="_blank">NABEC</a>
 and
 <a href="https://explore.anvilproject.org/datasets/a4e936d1-d81a-475d-95be-b5cd41de921d" target="_blank">HBCC</a>
 datasets.
 </p>
 
 <h2>Credits</h2>
 <p>
 Thanks to the North American Brain Expression Consortium (NABEC), the NIMH
 Human Brain Collection Core (HBCC), the Banner Sun Health Research Institute
 Brain and Body Donation Program, and the NIH CARD Long-Read Initiative for
 generating and sharing this dataset, and to Melissa Meredith for preparing the
 browser track. This work was supported by the Intramural Research Programs of
 the NIA, NINDS, NCI, NHGRI and NIMH, and used the NIH STRIDES Initiative and
 the NIH HPC Biowulf cluster.
 </p>
 
 <h2>References</h2>
 
 
 <p>
 Billingsley KJ, Meredith M, Daida K, Jerez PA, Negi S, Malik L, Genner RM, Moller A, Zheng X, Gibson
 SB <em>et al</em>.
 <a href="https://doi.org/10.1101/2024.12.16.628723" target="_blank">
 Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural
 variation on gene expression and DNA methylation</a>.
 <em>bioRxiv</em>. 2024 Dec 17;.
 PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/39764002" target="_blank">39764002</a>; PMC: <a
 href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11702628/" target="_blank">PMC11702628</a>
 </p>
 
 
 
 <p>
 Kolmogorov M, Billingsley KJ, Mastoras M, Meredith M, Monlong J, Lorig-Roach R, Asri M, Alvarez
 Jerez P, Malik L, Dewan R <em>et al</em>.
 <a href="https://doi.org/10.1038/s41592-023-01993-x" target="_blank">
 Scalable Nanopore sequencing of human genomes provides a comprehensive view of haplotype-resolved
 variation and methylation</a>.
 <em>Nat Methods</em>. 2023 Oct;20(10):1483-1492.
 PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/37710018" target="_blank">37710018</a>; PMC: <a
 href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222905/" target="_blank">PMC11222905</a>
 </p>