A reference panel of 64,976 haplotypes for genotype imputation
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Abstract
We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.
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Imputation reference panels share the same study biases as in GWAS, creating challenges for imputing sites that are rare in European populations but common elsewhere when the catalog of non-European haplotypes is substantially smaller.
“Furthermore, imputation reference panels share the same study biases as in GWAS41, creating challenges for imputing sites that are rare in European populations but common elsewhere when the catalog of non-European haplotypes is substantially smaller.”
From Clinical use of current polygenic risk scores may exacerbate health disparities (2019) · cites this paper as [41]
The Abstract (page not provided) says the HRC panel draws mainly on studies of predominantly European ancestry and proposes increasing its ethnic diversity. It also links larger, more diverse panels to better imputation accuracy. Online Methods > Site filtering (page not provided) notes variants frequent in non-European populations that were called only in 1000 Genomes. The paper does not explicitly establish that reference panels share GWAS study biases or assess the claimed imputation difficulty for variants rare in Europeans but common elsewhere. (LLM, conf=0.82)
Experimental — accuracy not yet measuredIncreased access to exome and whole-genome sequence data has extended discovery to low-frequency and rare alleles previously inaccessible to GWAS, through direct association and imputation.
“Recently, increased access to exome and whole-genome sequence data has, through both direct association analysis45,46 and imputation3,4, extended discovery to low-frequency and rare alleles previously inaccessible to GWAS.”
From A brief history of human disease genetics (2020) · cites this paper as [4]
For common variants underlying the bulk of complex-disease risk, resolution of association mapping is often limited by the haplotype structure of the human genome.
“For the common variants that underlie the bulk of complex-disease risk, the resolution of association mapping is often limited by the haplotype structure of the human genome2–4.”
From A brief history of human disease genetics (2020) · cites this paper as [4]
The principal benefit to date of whole-genome sequence data to genetic discovery has been to bolster array-based access to lower-frequency alleles, directly through inclusion on genotyping platforms or indirectly through imputation from sequence-based reference samples.
“However, the principal benefit to date of whole-genome sequence data to genetic discovery has been to bolster array-based access to lower-frequency alleles, either directly, through their inclusion on genotyping platforms, or indirectly, through imputation from sequence-based reference samples3,4.”
From A brief history of human disease genetics (2020) · cites this paper as [4]
In the 406 GWAS loci, 4% of sentinel variants were nonsynonymous, representing significant enrichment (p=2.5×10−10; 0.4% of variants with MAF>0.1% in the imputation panel were nonsynonymous).
“In the 406 GWAS loci, 4% of sentinel variants were nonsynonymous, representing a significant enrichment (p=2.5×10−10; 0.4% of variants with MAF>0.1% in the imputation panel41 were nonsynonymous).”
From Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use (2019) · cites this paper as [41]
Variants with minor allele frequency less than 0.001 were excluded.
“We also excluded all variants with minor allele frequency less than 0.001, the lower bound of moderate imputation accuracy with the currently best available imputation reference panel41.”
From Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use (2019) · cites this paper as [41]
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Comparing Within- and Between-Family Polygenic Score Prediction
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Host genetic regulation of human gut microbial structural variation
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Insights into the genetic architecture of the human face
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Self-citationCausal associations between modifiable risk factors and the Alzheimer's phenome
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Imprint of assortative mating on the human genome
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Self-citationGenome-wide analysis yields new loci associating with aortic valve stenosis
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Self-citationThe female protective effect against autism spectrum disorder
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The effect of X-linked dosage compensation on complex trait variation
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Sex-specific DNA methylation differences in Alzheimer’s disease pathology
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- Authors
- the Haplotype Reference Consortium
- Venue
- Nature Genetics
- Published
- 2016-08-22
- Volume
- 48
- Issue
- 10
- Pages
- 1279-1283
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC5388176
- OpenAlex
- W2511515754
- Cited by
- 2,836
- References
- 24
- Citations by year
- 2026: 143 · 2025: 219 · 2024: 327 · 2023: 343 · 2022: 389 · 2021: 422 · 2020: 321 · 2019: 288 · 2018: 248 · 2017: 118 · 2016: 16 · 2014: 1
- FWCI
- 180.42
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion)
- VU Research Portal (publishedVersion)
- PubMed Central (acceptedVersion)
- Explore Bristol Research (acceptedVersion, other-oa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Padua Research Archive (University of Padova) (submittedVersion, other-oa)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) (submittedVersion)
- IRIS (submittedVersion)
- UnissResearch (Università degli Studi di Sassari) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by-nc-nd)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Funders
- Wellcome Trust (UK10K, WT 098051, 202802/Z/16/Z, WT097307, WT091310, WT090851)
- National Institute for Health and Care Research (NF-SI-0611-10099, NF-SI-0611-10219)
- British Heart Foundation (SP/04/002)
- Versus Arthritis
- National Institutes of Health (n01ey50007-15-0-1, HHSN268201100004C, n01mh80001-12-0-0, HHSN268201100001C, HHSN268201100002C, 5rc2dk088389-02, HHSN268201100003C)
- Canadian Institutes of Health Research (172013_1)
- Medical Research Council (MR/J00314X/1, MC_PC_15018)
- National Institute on Alcohol Abuse and Alcoholism (R01AA009367)
- National Institute on Aging (HHSN-271-2011-00004C,, U19AG023122)
- National Heart, Lung, and Blood Institute (HHSN268201300050C, R01HL127564, HHSN268201300046C, U01HL117626, HHSN268201300048C, HHSN268201300049C, HHSN268201100046C, R01HL102830, HHSN268201300047C, R01HL117626, R01HL109946)
- National Institute of Mental Health (U01MH105641, R01MH090937, R01MH101820, U01MH105653, R01MH085548, R01MH104964, R01MH094145, N01 MH080001)
- National Institute on Drug Abuse (R01DA037904, R01DA024417, R01DA005147, R01DA036216)
- National Human Genome Research Institute (U01HG005773, R01HG000376, R01HG007022)
- National Eye Institute (N01-EY-5-0007, ZIAEY000546, P30EY001583)
- National Cancer Institute (P50CA127003, R01CA151993, R01CA137178, R01CA059045, U01CA164930, U01CA137088, P01CA055075, UM1CA167552)
- National Institute of General Medical Sciences (T32GM007753)
- National Institute of Diabetes and Digestive and Kidney Diseases (U01DK085526, U01DK085501, R01DK072193, U01DK062370, RC2-DK088389, U01DK085545, R01DK073541, K24DK080140, K99DK092251, R01DK098032, U54DK083912, R01DK093757, P30DK020595)
- FP7 Ideas: European Research Council (617306)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- genotype imputation, haplotype reference panel, whole genome sequencing, European ancestry, phasing, association studies
- MeSH terms
- Alleles, Genetic Techniques, Genotype, Haplotypes, Humans, Reference Values, Internet, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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