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A Unified Approach to Genotype Imputation and Haplotype-Phase Inference for Large Data Sets of Trios and Unrelated Individuals

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Browning, Brian L., Browning, Sharon R.·2009·The American Journal of Human Genetics

DOI 10.1016/j.ajhg.2009.01.005PMC PMC2668004

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Abstract

We present methods for imputing data for ungenotyped markers and for inferring haplotype phase in large data sets of unrelated individuals and parent-offspring trios. Our methods make use of known haplotype phase when it is available, and our methods are computationally efficient so that the full information in large reference panels with thousands of individuals is utilized. We demonstrate that substantial gains in imputation accuracy accrue with increasingly large reference panel sizes, particularly when imputing low-frequency variants, and that unphased reference panels can provide highly accurate genotype imputation. We place our methodology in a unified framework that enables the simultaneous use of unphased and phased data from trios and unrelated individuals in a single analysis. For unrelated individuals, our imputation methods produce well-calibrated posterior genotype probabilities and highly accurate allele-frequency estimates. For trios, our haplotype-inference method is four orders of magnitude faster than the gold-standard PHASE program and has excellent accuracy. Our methods enable genotype imputation to be performed with unphased trio or unrelated reference panels, thus accounting for haplotype-phase uncertainty in the reference panel. We present a useful measure of imputation accuracy, allelic R(2), and show that this measure can be estimated accurately from posterior genotype probabilities. Our methods are implemented in version 3.0 of the BEAGLE software package.

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Authors: Browning, B. L., & Browning, S. R.
Affiliations: University of Auckland (NZ)
Corresponding author: Browning, Brian L.
ORCID: Browning, Brian L.
Browning, Sharon R.
Venue: The American Journal of Human Genetics
Publisher: Elsevier BV
Published: 2009-02
Volume: 84
Issue: 2
Pages: 210-223
ISSN: 0002-9297 (ISSN-L)
DOI: 10.1016/j.ajhg.2009.01.005
PMC: PMC2668004
OpenAlex: W2059542829
Cited by: 1,640
References: 29
Citations by year: 2026: 35 · 2025: 44 · 2024: 62 · 2023: 50 · 2022: 86 · 2021: 99 · 2020: 94 · 2019: 102 · 2018: 98 · 2017: 121 · 2016: 123 · 2015: 161 · 2014: 172 · 2013: 132 · 2012: 120
FWCI: 50.70
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 1663 d)
Locations: The American Journal of Human Genetics (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: Wellcome Trust (076113)
National Institutes of Health
National Institute of General Medical Sciences (R01GM075091)
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, parent-offspring trios, low-frequency variants, allele frequency estimation, imputation accuracy, beagle dogs, phase comparison
MeSH terms: Computer Simulation, Female, Gene Frequency, Genotype, Haplotypes, Humans, Male, Markov Chains, Models, Genetic, Nuclear Family, Reproducibility of Results

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A Unified Approach to Genotype Imputation and Haplotype-Phase Inference for Large Data Sets of Trios and Unrelated Individuals

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