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Mon Nov 10 17:18:01 2025 -0800
Making each list item less than 100 character. Fixing special characters using HTML entiites. Adding a missing URL. Removing duplicate entires, refs #36642
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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.
-
- 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.
+ 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):
+
-
+ 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
public, so this track contains only 279 genomes. For details, see
(Mallick et al, Nature 2016). The hg38 track was lifted from hg19.
- - Human Genome Diversity Project (HGDP):
+
-
+ 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).
+ Data can be downloaded from the
+ Sanger Website. For details, see (Bergström et al, Science 2020).
- - gnomAD HGDP and 1000 Genomes callset:
+
-
+ 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).
+ 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.
+ 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.
- -
- 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).
+ target="_blank">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.
+ cohorts with high rates of consanguinity. See (Sun et al, Nature 2024) for details.
+
+
-
- NHLBI TOPMED
- Freeze 10: NHLBI TOPMed (Trans-Omics for Precision
+ 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.
- - 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:
+ target="_blank">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.
+ 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) :
+
-
+ 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).
+ 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 Mutações (ABraOM):
+
-
+ 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
+ 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).
-
-
- - Brazil Arquivo Brasileiro Online de Mutações (ABraOM):
- Genomic variants obtained with whole-genome sequencing from SABE, a
- census-based sample of 1,117 elderly individuals from São Paulo, Brazil's
- largest city. The 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).
+ target="_blank">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.
+
-
+ 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
+ target="_blank">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.
+
-
+ 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).
+ 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.
For a full description of how the display works, please see our
Haplotype Display help page.
Briefly, 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 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
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 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-Cortés 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
+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