9b60e5505dd8218f538ce44ca13bd4bd86df1d38 jnavarr5 Tue Nov 18 13:22:09 2025 -0800 Fixing typos found in code review, refs #36722 diff --git src/hg/makeDb/trackDb/human/varFreqs.html src/hg/makeDb/trackDb/human/varFreqs.html index dadf9f83ab0..278c10300f4 100644 --- src/hg/makeDb/trackDb/human/varFreqs.html +++ src/hg/makeDb/trackDb/human/varFreqs.html @@ -1,436 +1,436 @@

Description

This container track contains annotation tracks with individual level genotypes, usually phased, and tracks where only the variant frequencies, aka allele frequencies, are shown. The tracks were collected from the following projects. Only the projects 1000 Genomes (its own track), HGDP, SGDP, HGDP+1k and MXB provide individual-level genotypes. All others provide only allele frequencies, their genotypes require signing a data access agreement.

Available on hg19 and hg38:

Mexico Biobank (MXB): This track displays phased alleles from the Mexico Biobank Project (MXB), based on array genotyping of 6,011 individuals sampled across all 32 states of Mexico during the 2000 National Health Survey (ENSA 2000) conducted by the National Institute of Public Health (INSP). Frequencies can be plotted onto a map on MexVar. The hg38 track was lifted from hg19. (Publication?)
Simons Genome Diversity Project (SGDP): Funded by the Simons Foundation, the Simons Genome Diversity Project is a large-scale effort that sequenced high-coverage genomes from 300 individuals (279 in this track) representing 142 diverse and often indigenous populations worldwide. Its goal was to capture the full range of human genetic diversity to better understand population history, migration, and adaptation. It is sampling populations in a way that represents as much anthropological, linguistic and cultural diversity as possible, and thus includes many deeply divergent human populations that are not well represented in other datasets. SGDP emphasizes breadth of global representation and population history, whereas HGDP emphasizes continuity and - comparability across major population groups. Not all iits data is + comparability across major population groups. Not all its data is public, so this track contains only 279 genomes. For details, see (Mallick et al, Nature 2016). The hg38 track was lifted from hg19.

Available only on hg38:

Human Genome Diversity Project (HGDP): 929 high-coverage genome sequences from 54 diverse human populations, 26 of which are physically phased using linked-read sequencing. The Human Genome Diversity Project (HGDP) was launched in the early 1990s to study the genetic variation and evolutionary history of modern humans across global populations. Its goal was to document the full spectrum of human genetic diversity, particularly in indigenous and geographically isolated groups, to better understand population structure, migration, adaptation, and disease susceptibility.The project collected samples from ~1,000 individuals representing over 50 populations worldwide, including groups from Africa, Europe, Asia, Oceania, and the Americas. These data have become a foundational reference for population genetics and human evolution studies. Data can be downloaded from the Sanger Website. For details, see (Bergström et al, Science 2020).
gnomAD HGDP and 1000 Genomes callset: A reprocessed version by the gnomAD project for the 1000 Genomes and Human Genome Diversity Project (HGDP) data, with 4094 genomes from 80 populations. We already have separate, older tracks for 1000 Genomes on the main hg38 browser and for HGDP, just above. This track combines both datasets, with harmonized data quality. For details, see (Koenig et al, 2024).
Mexico City Prospective Study (MCPS): 9,950 whole genome sequenced individuals and 141,046 exome sequenced and genotyped individuals from the Mexico City Prospective Study (MCPS), a collaboration between the Regeneron Genetics Center, University of Oxford, Universidad Nacional Autónoma de México (UNAM), National Institute of Genomic Medicine in Mexico, Abbvie Inc. and AstraZeneca UK. For details see (Ziyatdinov A, Nature 2023), the reference section.
Regeneron Million Exomes Project (ME): Whole-exomes of 983,578 individuals sequenced by the Regeneron Genetics Center (RGC). These data span dozens of collaborations including large biobanks and health systems. All data were generated by the RGC on a single, harmonized sequencing and informatics protocol. The dataset includes individuals across diverse ancestral populations, encompassing outbred and founder populations and cohorts with high rates of consanguinity. See (Sun et al, Nature 2024) for details.
NHLBI TOPMED Freeze 10: NHLBI TOPMed (Trans-Omics for Precision Medicine) program, launched by the U.S. National Heart, Lung, and Blood Institute, integrates whole-genome sequencing with molecular, clinical, and environmental data from large, well-phenotyped cohorts. Its goal is to uncover the biological mechanisms underlying heart, lung, blood, and sleep disorders to advance precision medicine and improve population health. Freeze 10 contains 868,581,653 variants from 150,899 whole genomes. VCFs were downloaded from BRAVO.
GenomeAsia Pilot (GAsP): Whole-genome sequencing data of 1,739 individuals from 219 population groups across Asia. See (GenomeAsia Consortium, Nature 2019) for details.
ALFA: The NCBI ALlele Frequency Aggregator pipeline computes allele frequencies from approved, unrestricted dbGaP studies and makes them publicly available through dbSNP. Its goal is to release frequency data from over one million dbGaP subjects to aid discoveries involving common and rare variants with biological or disease relevance. The R4 release includes 408,709 subjects and allele frequencies for 15.5 million rs sites, including nearly one million ClinVar variants. Genotype and associated individual-level data are accessible through dbGaP authorized access.
JPN To61k Japan Tohoku University Tohoku Medical Megabank Organization 61k Allele frequency panel (JPN 61k): An allele frequency panel based on short-read WGS analysis of 61,000 Japanese individuals. The project includes other datatypes, such as STRs, long-read SVs and short-read CNVs. Data can be downloaded from the jMorp Website, specifically the Downloads section. For details, see (Tadaka et al, NAR 2023).
Brazil Arquivo Brasileiro Online de Mutaçõ (ABraOM): Genomic variants obtained with whole-genome sequencing from SABE, a census-based sample of elderly individuals from São Paulo, Brazil's largest city. Brazilian population is constituted by ~500 years of admixture between Africans, Europeans, and Native Americans. Additionally, the cohort presents ~3% of individuals with non-admixed Japanese ancestry (early 20th century migration). Coverage 38.6. Data can be downloaded from the AbraOM Website. For details see (Naslavsky et al, Nat Comm 2022).
IndiGenomes: Whole genome sequencing of 1,029 healthy Indian individuals under the pilot phase of the "IndiGen" program. Data can be downloaded from the IndiGen Website. For details see (Jain et al, NAR 2020). Only the allele frequency is available from this project. The website also provides SV call and Alu insertion VCFs.
Korean Variant Archive (KOVA): 1,896 whole genome sequencing and 3,409 whole exome sequencing data from healthy individuals of Korean ethnicity. Most of the samples were originated from normal tissue of cancer patients (40.16 %), healthy parents of rare disease patients (28.4 %), or healthy volunteers (31.44 %). Japanese ancestry is broken down in the INFO field. TSV data can be requested on the KOVA Downloads website. Coverage 100x for WES, 30x for WGS. For details see (Lee et al, Exp Mol Med 2022).

Display Conventions

Most tracks only show the variant and allele frequencies on mouseover or clicks. When zoomed in, tracks display alleles with base-specific coloring. Homozygote data are shown as one letter, while heterozygotes will be displayed with both letters.

Full haplotype display - only for the MXB and HGDP tracks: In "pack" mode, this track sorts the haplotypes. This can be useful for determining the similarity between the samples and inferring inheritance at a particular locus. Each sample's phased and/or homozygous genotypes are split into haplotypes, clustered by similarity around a central variant (in pink), and sorted for display by their position in the clustering tree. Click a variant to center on it. The tree (as space allows) is drawn in the label area next to the track image. Leaf clusters, in which all haplotypes are identical (at least for the variants used in clustering), are colored purple.

For a full description of how the display works, please see our Haplotype Display help page.

For NCBI ALFA: This track has no single VCF with INFO fields, but uses multiple subtracks instead, one per ancestry.

Data Access

Most of the data in these tracks are not available for download from UCSC. Only individual variants can be browsed on our website. But the data can be downloaded for free from the original projects. Accessing the data usually requires a click-through license on the respectice websites:

MXB: Allele frequencies by geographical state and ancestry are available via the MexVar platform. Raw genotype data are available under controlled access at the EGA (Study: EGAS00001005797; Dataset: EGAD00010002361). For the VCFs, email andres.moreno@cinvestav.mx.

MCPS: VCFs with summarized allele frequencies are available from the MCPS website.

Regeneron one million exomes: VCFs with summarized allele frequencies are available from the RGC ME website.

TOPMED: VCFs with summarized allele frequencies are available from the TOPMED BRAVO website. They require a login.

-GenomeAsia Pilot: VCFs are available from UCSC and also from the +GenomeAsia Pilot: VCFs are available from UCSC and also from the GenomeAsia 100K website. No license nor login.

Methods

MXB: Genotyping was performed with the Illumina Multi-Ethnic Global Array (MEGA, ~1.8M SNPs), optimized for admixed populations and enriched for ancestry-informative and medically relevant variants. Only autosomal, biallelic SNPs passing quality control are included. Samples were selected from 898 recruitment sites, with prioritization of indigenous language speakers. Data processing included GenomeStudio → PLINK conversion, strand alignment, removal of duplicates, update of map positions using dbSNP Build 151 and low-quality variants/individuals, and relatedness filtering.

SGDP: The version used was https://sharehost.hms.harvard.edu/genetics/reich_lab/sgdp/vcf_variants/, merged with bcftools and lifted to hg38 with CrossMap.

-KOVA: V7 of the TSV.gz was obtained from the KOVA staff and converted to VCF. If it not +KOVA: V7 of the TSV.gz was obtained from the KOVA staff and converted to VCF. It is not available for download from our site but can be requested from the KOVA website.

Credits

MXB: We thank the Center for Research and Advanced Studies (Cinvestav) of Mexico for generating and providing the frequency data, the National Institute of Medical Sciences and Nutrition (INCMNSZ) for DNA extraction, and the Ministry of Health together with the National Institute of Public Health (INSP) for the design and implementation of the National Health Survey 2000 (ENSA 2000). We also thank the ENSA-Genomics Consortium for their contributions to sample collection and data processing that made possible the construction of the MXB genomic resource.

MCPS: Data produced by Regeneron RGC and collaborators, which are the University of Oxford, Universidad Nacional Autónoma de México (UNAM) and National Institute of Genomic Medicine in Mexico. The Regeneron Genetics Center, University of Oxford, Universidad Nacional Autónoma de México (UNAM), National Institute of Genomic Medicine in Mexico, Abbvie Inc. and AstraZeneca UK Limited (collectively, the "Collaborators") bear no responsibility for the analyses or interpretations of the data presented here. Any opinions, insights, or conclusions presented herein are those of the authors and not of the Collaborators.

Regeneron Million Exomes: The Regeneron Genetics Center, and its collaborators (collectively, the "Collaborators") bear no responsibility for the analyses or interpretations of the data presented here. Any opinions, insights, or conclusions presented herein are those of the authors and not of the Collaborators. This research has been conducted using the UK Biobank Resource under application number 26041.

SGDP: This project was funded by the Simons Foundation. Thanks to David Reich and Swapan Mallick for help with importing the data.

KOVA: Thanks to Insu Jang and the KOVA director for providing variant frequencies in TSV format.

Thanks to Alex Ioannidis, UCSC, and Andreas Lahner, MGZ, for feedback on this track.

References

Barberena-Jonas, C. et al. (2025). MexVar database: Clinical genetic variation beyond the Hispanic label in the Mexican Biobank. Nature Medicine (in press).

Sohail M, Moreno-Estrada A. The Mexican Biobank Project promotes genetic discovery, inclusive science and local capacity building. Dis Model Mech. 2024 Jan 1;17(1). PMID: 38299665; PMC: PMC10855211

Sohail M, Palma-Martínez MJ, Chong AY, Quinto-Corés CD, Barberena-Jonas C, Medina-Muñoz SG, Ragsdale A, Delgado-Sánchez G, Cruz-Hervert LP, Ferreyra-Reyes L et al. Mexican Biobank advances population and medical genomics of diverse ancestries. Nature. 2023 Oct;622(7984):775-783. PMID: 37821706; PMC: PMC10600006

Ziyatdinov A, Torres J, Alegre-Díaz J, Backman J, Mbatchou J, Turner M, Gaynor SM, Joseph T, Zou Y, Liu D et al. Genotyping, sequencing and analysis of 140,000 adults from Mexico City. Nature. 2023 Oct;622(7984):784-793. PMID: 37821707; PMC: PMC10600010

GenomeAsia100K Consortium. The GenomeAsia 100K Project enables genetic discoveries across Asia. Nature. 2019 Dec;576(7785):106-111. PMID: 31802016; PMC: PMC7054211

Sun KY, Bai X, Chen S, Bao S, Zhang C, Kapoor M, Backman J, Joseph T, Maxwell E, Mitra G et al. A deep catalogue of protein-coding variation in 983,578 individuals. Nature. 2024 Jul;631(8021):583-592. PMID: 38768635; PMC: PMC11254753

Tadaka S, Kawashima J, Hishinuma E, Saito S, Okamura Y, Otsuki A, Kojima K, Komaki S, Aoki Y, Kanno T et al. jMorp: Japanese Multi-Omics Reference Panel update report 2023. Nucleic Acids Res. 2024 Jan 5;52(D1):D622-D632. PMID: 37930845; PMC: PMC10767895

Naslavsky MS, Scliar MO, Yamamoto GL, Wang JYT, Zverinova S, Karp T, Nunes K, Ceroni JRM, de Carvalho DL, da Silva Simões CE et al. Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil. Nat Commun. 2022 Mar 4;13(1):1004. PMID: 35246524; PMC: PMC8897431

Jain A, Bhoyar RC, Pandhare K, Mishra A, Sharma D, Imran M, Senthivel V, Divakar MK, Rophina M, Jolly B et al. IndiGenomes: a comprehensive resource of genetic variants from over 1000 Indian genomes. Nucleic Acids Res. 2021 Jan 8;49(D1):D1225-D1232. PMID: 33095885; PMC: PMC7778947

Bergström A, McCarthy SA, Hui R, Almarri MA, Ayub Q, Danecek P, Chen Y, Felkel S, Hallast P, Kamm J et al. Insights into human genetic variation and population history from 929 diverse genomes. Science. 2020 Mar 20;367(6484). PMID: 32193295; PMC: PMC7115999

Koenig Z, Yohannes MT, Nkambule LL, Zhao X, Goodrich JK, Kim HA, Wilson MW, Tiao G, Hao SP, Sahakian N et al. A harmonized public resource of deeply sequenced diverse human genomes. Genome Res. 2024 Jun 25;34(5):796-809. PMID: 38749656; PMC: PMC11216312

Mallick S, Li H, Lipson M, Mathieson I, Gymrek M, Racimo F, Zhao M, Chennagiri N, Nordenfelt S, Tandon A et al. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations. Nature. 2016 Oct 13;538(7624):201-206. PMID: 27654912; PMC: PMC5161557

Lee J, Lee J, Jeon S, Lee J, Jang I, Yang JO, Park S, Lee B, Choi J, Choi BO et al. A database of 5305 healthy Korean individuals reveals genetic and clinical implications for an East Asian population. Exp Mol Med. 2022 Nov;54(11):1862-1871. PMID: 36323850; PMC: PMC9628380