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Fast and accurate genotype imputation in genome-wide association studies through pre-phasing
Open accessAbstract
The 1000 Genomes Project and disease-specific sequencing efforts are producing large collections of haplotypes that can be used as reference panels for genotype imputation in genome-wide association studies (GWAS). However, imputing from large reference panels with existing methods imposes a high computational burden. We introduce a strategy called 'pre-phasing' that maintains the accuracy of leading methods while reducing computational costs. We first statistically estimate the haplotypes for each individual within the GWAS sample (pre-phasing) and then impute missing genotypes into these estimated haplotypes. This reduces the computational cost because (i) the GWAS samples must be phased only once, whereas standard methods would implicitly repeat phasing with each reference panel update, and (ii) it is much faster to match a phased GWAS haplotype to one reference haplotype than to match two unphased GWAS genotypes to a pair of reference haplotypes. We implemented our approach in the MaCH and IMPUTE2 frameworks, and we tested it on data sets from the Wellcome Trust Case Control Consortium 2 (WTCCC2), the Genetic Association Information Network (GAIN), the Women's Health Initiative (WHI) and the 1000 Genomes Project. This strategy will be particularly valuable for repeated imputation as reference panels evolve.
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Metadata
- Authors
- Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R.
- Affiliations
- University of Chicago (US)
- University of Michigan (US)
- Centre for Human Genetics (GB)
- Corresponding author
- Stephens, Matthew
- Marchini, Jonathan
- Abecasis, Gonçalo R
- Venue
- Nature Genetics
- Published
- 2012-07-22
- Volume
- 44
- Issue
- 8
- Pages
- 955-959
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC3696580
- OpenAlex
- W2111307685
- Cited by
- 1,737
- References
- 26
- Citations by year
- 2026: 40 · 2025: 61 · 2024: 74 · 2023: 88 · 2022: 100 · 2021: 136 · 2020: 145 · 2019: 157 · 2018: 155 · 2017: 175 · 2016: 188 · 2015: 193 · 2014: 141 · 2013: 72 · 2012: 10
- FWCI
- 80.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- University of Michigan
- Norges Teknisk-Naturvitenskapelige Universitet
- Wellcome Trust (085475, 090532, 076113)
- Helse Midt-Norge
- Norges Forskningsråd
- U.S. Public Health Service (HGO2585)
- National Heart, Lung, and Blood Institute (HL109964, R01HL117626)
- National Institute of Mental Health (R01MH084698)
- National Human Genome Research Institute (HG005552, HG005581, R01HG002651, U01HG006513, RC2HG005552, R01HG007022, RC2HG005581)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK0855840)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- genotype imputation, haplotype phasing, genome-wide association study, reference panel, computational complexity reduction, Mach, 1000 Genomes Project, haplotype matching
- MeSH terms
- Genotype, Haplotypes, Humans, Human Genome Project, Computational Biology, Databases, Genetic, Genome-Wide Association Study
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