This track merges variants from three genotyping-array cohorts into a single bigBed file with predicted protein consequences and cross-database filtering. It contains 14.7 million variants from the Taiwan Precision Medicine Initiative (TPMI Axiom TPM1 chip, -~1 million Han Chinese), the Mexico Biobank (MexBB, 6,011 individuals), and UK Biobank +~1 million Han Chinese), the Mexico Biobank (MexBB, 6,011 individuals), and the UK Biobank (361k unrelated white British, imputed from the Neale Lab Round 2 release).
The array track is kept separate from the sequencing-based combined tracks (Disease cohorts and Population reference) so that sequencing-based and array-based frequencies can be inspected independently. For a summary of all available variant frequency databases, see the SNV Frequencies supertrack page.
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 "AA change" field uses bcftools csq notation: 23I>23V means position 23 changed from Isoleucine (I) to Valine (V) (missense). 23I alone (no arrow) means position 23 is Isoleucine and unchanged (synonymous). A "*" indicates a stop codon (e.g. 45R>45* is a stop_gained).
Allele frequencies from genotyping arrays are not directly comparable to those from whole-genome or whole-exome sequencing. Two limitations to keep in mind:
NGS_concordance value (chip-vs-sequencing concordance from
its own validation) in the source VCF; high-AF claims with low concordance are
- common. MexBB ships only AN/AF/AC with no FILTER column and no per-site QC at all.
+ common. MexBB provides only AN/AF/AC with no FILTER column and no per-site QC.
For both arrays, high-AF rare-disease candidates should be cross-checked against the
sequencing-based
Population reference track before
drawing conclusions.This track supports filtering via the track settings page. Click the track title or use the "Configure" button to access filters.
The Source Database filter restricts the display to variants present in specific databases. It uses OR logic.
The same merge-and-annotate pipeline used for the sequencing-based combined tracks
(Disease cohorts and
Population reference) was run on the
array-cohort subset of source VCFs. Each VCF was stripped of its INFO fields, normalized
with bcftools norm (splitting multi-allelic sites), and merged with
bcftools merge. The merged VCF was then annotated with predicted protein
consequences using bcftools csq with the
Ensembl
GRCh38 release 115 gene annotation (GFF3).
The track's makeDoc file documents how each source VCF was converted. Scripts are available from Github.
The data can be explored interactively with the Table Browser or the Data Integrator. For programmatic access, our REST API can be used; the track name is varFreqsArray.
Because the merged callset includes data from multiple sources whose redistribution licenses differ, the combined bigBed is not available for download from our download server. The combined track can be reconstructed from the individual source VCFs using the conversion scripts on GitHub together with the build documentation.
This track is only possible thanks to the participants in TPMI, the Mexico Biobank, and UK Biobank, who donated samples and provided health information. Click on the individual TPMI, MexBB, or UK Biobank subtracks in the SNV Frequencies supertrack for full project credits. Thanks to Alex Ioannidis, UCSC, for the motivation for this track family and to Andreas Lahner, MGZ, for feedback.
For primary citations of each source dataset, see the References section on the SNV Frequencies supertrack page. The merged-track build itself 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
McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F. The Ensembl Variant Effect Predictor. Genome Biol. 2016 Jun 6;17(1):122. PMID: 27268795; PMC: PMC4893825