64a3f9e7813e823cf724ea188c3928a911578286
max
Thu Jun 4 00:32:22 2026 -0700
varFreqs: replace All Databases Combined with two phenotype-split tracks
Replace the single varFreqsAll combined track (and drop the varFreqsDisease
track) with two matched tracks for visual case-vs-background comparison:
varFreqsAffected - variants seen in the affected/case arms of disease
cohorts (SFARI SPARK WES/WGS ASD probands, SCHEMA cases,
GREGoR affected, GA4K); ~130,000 individuals
varFreqsBackground - population reference cohorts + the unaffected/control
arms of disease cohorts ("all other variants");
~1.5 million individuals
A variant seen in both groups appears in both tracks. Genotyping-array cohorts
stay out of both (varFreqsArray unchanged).
vcfToBigBed.py gains --split-affected to emit both tracks in one pass; it reads
phenotype tags (affected/unaffected/unknown) from populations.tsv and
is_disease/disease_role from databases.tsv, and derives the length-filter
ranges from the observed data. TOPMed reclassified as a population cohort.
SPARK WGS display name changed to SFARI SPARK WGS for consistency with the
standalone subtracks. Fixed the trackDb mouseOver $-substitution prefix
collision by wrapping fields in ${}. New description pages for both tracks.
refs #36642
diff --git src/hg/makeDb/trackDb/human/varFreqsDisease.html src/hg/makeDb/trackDb/human/varFreqsDisease.html
deleted file mode 100644
index 010d65019b7..00000000000
--- src/hg/makeDb/trackDb/human/varFreqsDisease.html
+++ /dev/null
@@ -1,198 +0,0 @@
-<h2>Description</h2>
-<p>
-This track merges variants from six disease-focused or clinically-recruited cohorts into a
-single bigBed file with predicted protein consequences and cross-database filtering. It
-contains 932 million variants from SPARK WES (140k autism families), SFARI WGS (12.5k
-autism families), TOPMed (NHLBI heart, lung and blood disease cohorts), SCHEMA
-(schizophrenia case/control), GREGoR (rare-disease families), and GA4K (PacBio long-read
-pediatric rare disease). Where the source dataset provides per-phenotype counts, those are
-exposed as separate AC/AF columns and as filter widgets.
-</p>
-
-<p>
-For a summary of all available variant frequency databases, including the population-scale
-control track and the genotyping-array track, see the
-<a href="hgTrackUi?g=varFreqs">SNV Frequencies</a> supertrack page.
-</p>
-
-<p>
-Each variant is annotated with its predicted consequence on protein-coding genes
-(using <a href="https://samtools.github.io/bcftools/howtos/csq-calling.html"
-target="_blank">bcftools csq</a> with
-<a href="https://www.ensembl.org/info/data/ftp/index.html" target="_blank">Ensembl</a>
-gene models), and colored by severity. Allele counts and frequencies are shown for each
-source database and, where available, broken down by phenotype.
-</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>
- <td style="background-color: rgb(255,0,0); color: white; text-align: center;"><b>Red</b></td>
- <td>Protein-truncating / Loss-of-function</td>
- <td>stop_gained, frameshift, splice_donor, splice_acceptor, stop_lost, start_lost</td>
-</tr>
-<tr>
- <td style="background-color: rgb(31,119,180); color: white; text-align: center;"><b>Blue</b></td>
- <td>Missense / In-frame</td>
- <td>missense, inframe_insertion, inframe_deletion, protein_altering</td>
-</tr>
-<tr>
- <td style="background-color: rgb(0,128,0); color: white; text-align: center;"><b>Green</b></td>
- <td>Synonymous</td>
- <td>synonymous, stop_retained</td>
-</tr>
-<tr>
- <td style="background-color: rgb(128,128,128); color: white; text-align: center;"><b>Grey</b></td>
- <td>Non-coding / Intergenic</td>
- <td>intron, non_coding, intergenic, UTR</td>
-</tr>
-</table>
-
-<h3>Amino Acid Change Notation</h3>
-<p>
-The "AA change" field uses bcftools csq notation: <b>23I>23V</b> means position
-23 changed from Isoleucine (I) to Valine (V) (missense). <b>23I</b> alone (no arrow)
-means position 23 is Isoleucine and unchanged (synonymous). A "*" indicates a
-stop codon (e.g. 45R>45* is a stop_gained).
-</p>
-
-<h2>Filters</h2>
-<p>
-This track supports filtering via the track settings page. Click the track title or use the
-"Configure" button to access filters.
-</p>
-
-<h3>Variant Type and Consequence</h3>
-<ul>
- <li><b>Variant Type</b>: SNV, Insertion, Deletion, or MNV.</li>
- <li><b>Consequence</b>: Missense, Synonymous, Stop Gained, Frameshift, Splice Donor,
- Splice Acceptor, Intron, 3' UTR, 5' UTR, Non-coding, Intergenic, or Other. The filter
- uses OR logic across the comma-separated consequence tokens on each variant. See the
- <a href="hgTrackUi?g=varFreqsAll">All Databases Combined</a> description page for a
- complete description of the "Other" bucket.</li>
-</ul>
-
-<h3>Frequency and Count Filters</h3>
-<ul>
- <li><b>Max Allele Frequency</b>: Filter by the maximum allele frequency observed across
- the six disease cohorts. Useful for finding rare variants enriched in cases.</li>
- <li><b>Total Allele Count</b>: Filter by the sum of allele counts across all six
- databases.</li>
- <li><b>Per-database AF and AC</b>: Filter by allele frequency or count in any specific
- source. For example, restrict to variants with SCHEMA case AF > 0.001.</li>
-</ul>
-
-<h3>Phenotype-stratified Filters</h3>
-<p>
-Four of the six sources publish counts split by phenotype, which lets you compare allele
-frequencies between affected and unaffected groups within the same cohort:
-</p>
-<ul>
- <li><b>SPARK WES</b> and <b>SFARI WGS</b>: ASD proband counts versus non-ASD family
- members (mostly parents and unaffected siblings). The split is from the SPARK
- individuals_registration <code>asd</code> column.</li>
- <li><b>SCHEMA</b>: Schizophrenia case counts versus controls, summed across the 39
- analysis cohorts in the original meta-analysis.</li>
- <li><b>GREGoR</b>: Affected, Unaffected, and Unknown disease-status counts.</li>
-</ul>
-
-<h3>Source Database</h3>
-<p>
-The <b>Source Database</b> filter restricts the display to variants present in specific
-databases. It uses OR logic: selecting multiple databases shows variants found in any of
-the selected sources.
-</p>
-
-<h3>Length Filters</h3>
-<ul>
- <li><b>Reference/Alternate Length</b>: Filter by the length of the reference or alternate allele.</li>
- <li><b>Length Change</b>: Filter by the size difference between alternate and reference
- (positive = insertion, negative = deletion, zero = SNV or MNV).</li>
-</ul>
-
-<h2>Methods</h2>
-<p>
-The same merge-and-annotate pipeline used for the
-<a href="hgTrackUi?g=varFreqsAll">All Databases Combined</a> track was run on the
-disease-cohort subset of source VCFs. Each VCF was stripped of its INFO fields,
-normalized with <code>bcftools norm</code> (splitting multi-allelic sites), and merged with
-<code>bcftools merge</code>. The merged VCF was then annotated with predicted protein
-consequences using <code>bcftools csq</code> with the
-<a href="https://www.ensembl.org/info/data/ftp/index.html" target="_blank">Ensembl</a>
-GRCh38 release 115 gene annotation (GFF3).
-</p>
-
-<p>
-The SPARK WES and WGS sites VCFs were rebuilt for this track so each variant carries
-phenotype-stratified counts in addition to overall AC/AN/AF. The split uses the
-<code>asd</code> column of the SPARK <code>individuals_registration</code> TSV via
-<code>bcftools +fill-tags -S</code>, producing AC_AUT / AN_AUT / AF_AUT and
-AC_NON_AUT / AN_NON_AUT / AF_NON_AUT. SCHEMA was processed the same way, summing
-AC_CASE/AN_CASE/AF_CASE and AC_CTRL/AN_CTRL/AF_CTRL across its 39 analysis cohorts.
-GREGoR ships AC/AN/AF triples for affected, unaffected and unknown disease status
-directly in its release.
-</p>
-
-<p>
-The track's
-<a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/varFreqs.txt"
-target="_blank">makeDoc file</a> documents how each source VCF was converted. Scripts are
-available from
-<a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/varFreqs"
-target="_blank">Github</a>.
-</p>
-
-<h2>Data Access</h2>
-<p>
-The data can be explored interactively with the
-<a href="../cgi-bin/hgTables">Table Browser</a> or the
-<a href="../cgi-bin/hgIntegrator">Data Integrator</a>. For programmatic access, our
-<a href="https://api.genome.ucsc.edu" target="_blank">REST API</a> can be used; the track
-name is <em>varFreqsDisease</em>.
-</p>
-<p>
-Because the merged callset includes data from multiple sources whose redistribution
-licenses differ, the combined bigBed is <b>not available for download</b> from our download
-server. The combined track can be reconstructed from the individual source VCFs using the
-<a href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/scripts/varFreqs"
-target="_blank">conversion scripts on GitHub</a> together with the
-<a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/varFreqs.txt"
-target="_blank">build documentation</a>.
-</p>
-
-<h2>Credits</h2>
-<p>
-This track is only possible thanks to the data from millions of volunteers around the
-world, who donated blood, signed consent forms and provided health information about
-themselves and sometimes their families. Click on any of the individual tracks in the
-<a href="hgTrackUi?g=varFreqs">SNV Frequencies</a> supertrack to see the specific credits
-for each project. Thanks to Alex Ioannidis, UCSC, for the motivation for this track and
-to Andreas Lahner, MGZ, for feedback.
-</p>
-
-<h2>References</h2>
-<p>
-For primary citations of each source dataset, see the References section on the
-<a href="hgTrackUi?g=varFreqs">SNV Frequencies</a> supertrack page. The merged-track
-build itself uses the following tools:
-</p>
-<p>
-Danecek P, McCarthy SA.
-<a href="https://doi.org/10.1093/bioinformatics/btx100" target="_blank">
-BCFtools/csq: haplotype-aware variant consequences</a>.
-<em>Bioinformatics</em>. 2017 Jul 1;33(13):2037-2039.
-PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/28205675" target="_blank">28205675</a>; PMC: <a
-href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870570/" target="_blank">PMC5870570</a>
-</p>
-<p>
-McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F.
-<a href="https://doi.org/10.1186/s13059-016-0974-4" target="_blank">
-The Ensembl Variant Effect Predictor</a>.
-<em>Genome Biol</em>. 2016 Jun 6;17(1):122.
-PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/27268795" target="_blank">27268795</a>; PMC: <a
-href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893825/" target="_blank">PMC4893825</a>
-</p>