This track shows small variants (SNVs and short indels) seen in population reference cohorts and in unaffected or control individuals of disease-study cohorts, annotated with their predicted protein consequence and colored by severity. It is the background half of a matched pair: the companion Disease cohorts track shows the same kind of variants seen in affected or case individuals. Displaying the two together lets you see how common a variant is in the general/unaffected population compared with affected individuals. For the full list of contributing projects, see the SNV Frequencies collection page.
The background combines two kinds of data: the population/biobank reference cohorts (such as gnomAD HGDP+1kG, TOPMed, ALFA, HRC and the many national WGS projects), and the unaffected/control or unknown-phenotype arms of the disease-study cohorts (non-ASD family members in SFARI SPARK WES/WGS, SCHEMA controls, and GREGoR unaffected/unknown participants). Genotyping-array cohorts are not included. A variant that also appears in affected individuals is shown in both this track and the Disease cohorts track.
Variants are colored by their most severe predicted consequence:
| Color | Consequence class | Examples |
|---|---|---|
| Protein-truncating / loss-of-function | stop_gained, frameshift, splice_donor, splice_acceptor, stop_lost, start_lost | |
| Missense / in-frame | missense, inframe_insertion, inframe_deletion, protein_altering | |
| Synonymous | synonymous, stop_retained | |
| Non-coding / intergenic | intron, non_coding, intergenic, UTR |
The score (used for shading) is the pooled background allele frequency times 1000.
Background AF is the pooled rate across contributing population cohorts and
unaffected/control arms: backgroundAF = sum(AC) / sum(AN), where
backgroundAC sums the allele counts and backgroundAN sums the allele
numbers across each cohort/arm that provides both AC and AF (the per-arm AN is derived as
round(AC / AF)). Two cohorts that publish only AF (ABraOM, ALFA) are still
pooled by assigning them an assumed allele number, set as a default_an in the
build configuration; their per-arm AC is then derived as round(AF × default_an).
Cohorts that publish
only AC with no default_an set (currently MGRB and the GREGoR unaffected and
unknown arms), and cohorts that contribute only through per-population AC/AF (currently
AllOfUs), are listed in backgroundSources but do not contribute to the pool
numerator or denominator; their data remain visible in the per-database and per-population
AC/AF columns. The pooled rate is preferred over a max-across-cohorts statistic so a small
cohort with a high local AF (for example AllOfUs Oceanian) cannot dominate the displayed
frequency.
The pooled rate also inherits a shared-sample bias: several source cohorts overlap in the individuals they include. For example, 1000 Genomes samples appear in both gnomAD HGDP+1kG and HRC; HGDP and SGDP overlap; AllOfUs and TOPMed share participants; ALFA aggregates dbGaP studies used elsewhere in the pool. Where a variant sits in a shared sample, both its AC and AN are counted more than once, so pooled AN is inflated and pooled AF is skewed toward the frequency in the shared subset. Treat the pooled rate as a cross-cohort summary rather than an unbiased population estimate; the per-cohort AC/AF/AN fields on each variant give the single-cohort numbers.
Alongside the pooled rate, the mouseover lists the top 3 contributing
background sources ranked by their own per-source AF, formatted as
Source (AF). This surfaces population cohorts where a variant
is specifically enriched, even when the pooled rate is small; the
East-Asian founder allele
rs4986893,
for example, ranks ToMMo Japan and KOVA Korea at the top while the pooled
rate across all contributing sources sits much lower. For disease cohorts
that ship a phenotype split (SPARK, SFARI WGS, SCHEMA, GREGoR), the
displayed AF is the unaffected-arm AF and the label includes the arm (for
example SPARK non-ASD, SCHEMA ctrl); for
population cohorts, the label is the cohort name and the AF is the unified
cohort AF. Per-population sub-ancestries of a cohort (such as gnomAD
HGDP+1kG continental groups) are deliberately excluded from this ranking so
sub-population frequencies do not crowd out actual project-level signals.
Two source cohorts are also excluded from the Top-3 ranking: SGDP
and SVatalog. Their VCFs encode allele counts per genotyped site
rather than per population (each variant in a single individual produces
AC=1, AN=2, AF=0.5), so the per-source AF is not a population
frequency and would always sit near the top of the ranking with a
meaningless value. Both cohorts still appear in backgroundSources
and still contribute their (small) AC and AN to the pooled
backgroundAF; they are only suppressed from the Top-3 list.
Variant-frequency VCFs from the contributing cohorts were stripped of unneeded INFO fields,
normalized with bcftools norm (splitting multi-allelic sites), and merged with
bcftools merge. The merged callset was annotated with predicted protein
consequences using bcftools csq against the
Ensembl
GRCh38 release 115 gene models.
A custom Python script (vcfToBigBed.py) then read the per-cohort allele
counts and frequencies and, for each variant, pooled the allele counts and allele numbers
across the population cohorts and unaffected/control subgroups to produce this track, and
across the affected arms to produce the companion
Disease cohorts track. A variant seen
in both groups appears in both tracks. The build is documented in the
makeDoc, and the scripts are on
GitHub.
Because the merged callset combines cohorts whose redistribution licenses differ, this track is not available for download and is not in the Table Browser. It can be reconstructed from the individual source VCFs using the conversion scripts and the build documentation. The per-project subtracks on the SNV Frequencies collection page document how to obtain each source dataset.
This track is only possible thanks to the data from millions of volunteers around the world who contributed to the population reference projects and to the unaffected/control arms of the disease cohorts. Click the individual project subtracks on the SNV Frequencies collection page for the specific credits and citations of each cohort. Thanks to Alex Ioannidis, UCSC, for the inspiration for this track and to Andreas Lahner, MGZ, for feedback.
For the primary citation of each source cohort, see the References section on the SNV Frequencies collection page. The merged-track build uses the following tools:
Danecek P, McCarthy SA. BCFtools/csq: haplotype-aware variant consequences. Bioinformatics. 2017 Jul 1;33(13):2037-2039. PMID: 28205675; PMC: PMC5870570