3bf9e1a841206d3bf5902e06791ef5be2dbdbd39 max Fri Jul 17 09:09:47 2026 -0700 lrSv: add Noyvert multi-ancestry long-read SV subtrack (noyvertSv) #Preview2 week - bugs introduced now will need a build patch to fix 888 Oxford Nanopore 1000 Genomes genomes, Sniffles2 v2.0.7, 107,445 SVs with per-superpopulation allele frequencies, imputation-accuracy metrics and UK Biobank SV-WAS associations. Converter approximates AC/AN from AF and the genotype missing rate (source has no allele count), stores BND mate breakends, and follows the shared lrSv svType/svLen/insLen/AC field convention so the container-level filters apply. refs #36258 diff --git src/hg/makeDb/trackDb/human/noyvertSv.html src/hg/makeDb/trackDb/human/noyvertSv.html new file mode 100644 index 00000000000..acb0734d582 --- /dev/null +++ src/hg/makeDb/trackDb/human/noyvertSv.html @@ -0,0 +1,130 @@ +<h2>Description</h2> +<p> +This track shows structural variants (SVs) identified by Oxford Nanopore +long-read sequencing of 888 individuals from the 1000 Genomes Project, +spanning five ancestry groups. Structural variants are genomic rearrangements +larger than about 50 bp, such as deletions, insertions, inversions, +duplications and breakends (rearrangement junctions); because they alter or +move large stretches of DNA at once, they can affect gene dosage and gene +regulation more strongly than single-nucleotide changes, yet they are largely +missed by the short-read data used in most large studies. +</p> +<p> +The panel contains more than 107,000 SVs called against GRCh38: about 60,000 +insertions, 38,000 deletions, 5,700 inversions, 2,700 breakends and 600 +duplications. Each variant carries an overall allele frequency and allele +frequencies for each of the five superpopulations (African, Admixed American, +East Asian, European, South Asian), Sniffles2 quality metrics, Hardy-Weinberg +p-values, and internal (leave-one-out) and UK Biobank imputation accuracy. +The authors used this panel to impute SVs into about 500,000 UK Biobank +participants and to test them for association with disease-relevant traits and +protein levels; where a variant reached genome-wide significance, the +associated traits are listed on its details page. +</p> + +<h2>Display Conventions and Configuration</h2> +<p> +Items are colored by SV type, matching the other subtracks of the container: +</p> +<table class="stdTbl"> + <tr><th style="background-color:#C80000;width:2em"> </th> + <td>Deletion (DEL)</td></tr> + <tr><th style="background-color:#0000C8;width:2em"> </th> + <td>Insertion (INS)</td></tr> + <tr><th style="background-color:#00A000;width:2em"> </th> + <td>Duplication (DUP)</td></tr> + <tr><th style="background-color:#E68C00;width:2em"> </th> + <td>Inversion (INV)</td></tr> + <tr><th style="background-color:#5A5A5A;width:2em"> </th> + <td>Breakend (BND), a single junction of a larger rearrangement</td></tr> +</table> +<p> +Insertions and breakends are drawn at a single reference base; the length of +inserted sequence is reported for insertions, and the mate locus of the +rearrangement junction is reported for breakends. Deletions, inversions and +duplications span the affected reference interval. Because the source table +does not report an allele count, the allele count and allele number shown here +are approximate values derived from the reported allele frequency and the +genotype missing rate (allele number = 2 × 888 × (1 − missing +rate); allele count = allele frequency × allele number). +</p> +<p> +The mouseover shows the variant name, SV type, reference and insertion lengths, +allele frequency, approximate allele count, and the number of UK Biobank trait +associations. Filters are available for SV type, SV length, insertion length, +approximate allele count, overall and per-population allele frequency, the +number of UK Biobank GWAS hits, and the UK Biobank imputation r². +</p> + +<h2>Methods</h2> +<p> +888 individuals from the 1000 Genomes Project (164 European, 144 Admixed +American, 168 East Asian, 171 South Asian and 241 African), out of 906 +sequenced, passed quality control. They were sequenced on the Oxford Nanopore +PromethION P48 platform with R9.4.1 flow cells and the SQK-LSK110 ligation kit, +to a median read length of about 6.2 kb and 15x median coverage. Reads were +aligned to GRCh38 with minimap2 v2.24 and structural variants were jointly +called across all samples with Sniffles2 v2.0.7 using tandem-repeat +annotations. Variants were retained if they were 50 bp to 30 Mb long, present +in at least two individuals and had a genotype missing rate below 20%, yielding +107,445 SVs. This SV panel was merged with about 45 million short variants from +1000 Genomes Phase 3 and phased with Beagle to build a multi-ancestry +imputation reference panel. Leave-one-out cross-validation with Beagle v5.4 +provided per-variant imputation accuracy (r²) and minor-allele +concordance. The panel was then used to impute SVs into 488,130 UK Biobank +participants, and an SV-wide association study (SV-WAS) with Regenie v3 tested +32 disease-relevant phenotypes and 1,463 protein levels in European-ancestry +participants, using a genome-wide significance threshold of p<5×10<sup>-8</sup>. +See Noyvert et al. 2025 for full details. +</p> +<p> +The per-variant summary table (allele frequencies, quality metrics, imputation +accuracy and significant UK Biobank associations for all 107,445 SVs) was +provided by the authors. At UCSC it was converted to the shared long-read SV +schema (signed lengths made positive, an explicit insertion-length field added, +allele count and allele number approximated from allele frequency and missing +rate, and colors assigned from the container's shared palette). 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>noyvertSv</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>noyvert.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 +page</a>. Example: +<tt>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/lrSv/noyvert.bb -chrom=chr21 -start=0 -end=100000000 stdout</tt>. +</p> + +<h2>Credits</h2> +<p> +Thanks to Boris Noyvert and colleagues at Boehringer Ingelheim and the wider +study team for generating this multi-ancestry long-read SV panel and for +sharing the per-variant summary table, and to the 1000 Genomes Project and the +UK Biobank participants whose data made the study possible. +</p> + +<h2>References</h2> +<p> +Noyvert B, Erzurumluoglu AM, Drichel D, Omland S, Andlauer TFM <em>et al</em>. +<a href="https://doi.org/10.7554/eLife.106115.1" target="_blank"> +Imputation of structural variants using a multi-ancestry long-read sequencing panel enables +identification of disease associations</a>. +<em>eLife</em>. 2025. doi:10.7554/eLife.106115.1 +</p>