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PMID: 19200528 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals.

American journal of human genetics ·Vol. 84 ·No. 2 ·2009-02-00 ·Pages 210-23

Browning BL, Browning SR

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.

MeSH Terms
Computer Simulation Female Gene Frequency/genetics Genotype Haplotypes/genetics Humans Male Markov Chains Models, Genetic Nuclear Family Reproducibility of Results
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Browning Brian L
Department of Statistics, University of Auckland, Auckland 1142, New Zealand. b.browning@auckland.ac.nz
Browning Sharon R
References (28)
28 references, click to expand
  1. Optimizing reduced-space sequence analysis.
    Bioinformatics. 2000 Dec;16(12):1082-90 PMID: 11159327
  2. Imputation-based analysis of association studies: candidate regions and quantitative traits.
    PLoS Genet. 2007 Jul;3(7):e114 PMID: 17676998
  3. Cohort profile: 1958 British birth cohort (National Child Development Study).
    Int J Epidemiol. 2006 Feb;35(1):34-41 PMID: 16155052
  4. A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase.
    Am J Hum Genet. 2006 Apr;78(4):629-44 PMID: 16532393
  5. Evaluating and improving power in whole-genome association studies using fixed marker sets.
    Nat Genet. 2006 Jun;38(6):663-7 PMID: 16715096
  6. A comparison of phasing algorithms for trios and unrelated individuals.
    Am J Hum Genet. 2006 Mar;78(3):437-50 PMID: 16465620
  7. Population structure, differential bias and genomic control in a large-scale, case-control association study.
    Nat Genet. 2005 Nov;37(11):1243-6 PMID: 16228001
  8. Reduced space sequence alignment.
    Comput Appl Biosci. 1997 Feb;13(1):45-53 PMID: 9088708
  9. A new multipoint method for genome-wide association studies by imputation of genotypes.
    Nat Genet. 2007 Jul;39(7):906-13 PMID: 17572673
  10. Newly identified loci that influence lipid concentrations and risk of coronary artery disease.
    Nat Genet. 2008 Feb;40(2):161-9 PMID: 18193043
  11. Simple and efficient analysis of disease association with missing genotype data.
    Am J Hum Genet. 2008 Feb;82(2):444-52 PMID: 18252224
  12. A high-resolution recombination map of the human genome.
    Nat Genet. 2002 Jul;31(3):241-7 PMID: 12053178
  13. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering.
    Am J Hum Genet. 2007 Nov;81(5):1084-97 PMID: 17924348
  14. Evaluating the effects of imputation on the power, coverage, and cost efficiency of genome-wide SNP platforms.
    Am J Hum Genet. 2008 Jul;83(1):112-9 PMID: 18589396
  15. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes.
    Nat Genet. 2008 May;40(5):638-45 PMID: 18372903
  16. Multilocus association mapping using variable-length Markov chains.
    Am J Hum Genet. 2006 Jun;78(6):903-13 PMID: 16685642
  17. Missing data imputation and haplotype phase inference for genome-wide association studies.
    Hum Genet. 2008 Dec;124(5):439-50 PMID: 18850115
  18. A new statistical method for haplotype reconstruction from population data.
    Am J Hum Genet. 2001 Apr;68(4):978-89 PMID: 11254454
  19. Testing untyped alleles (TUNA)-applications to genome-wide association studies.
    Genet Epidemiol. 2006 Dec;30(8):718-27 PMID: 16986160
  20. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease.
    Nat Genet. 2008 Aug;40(8):955-62 PMID: 18587394
  21. Identification of ten loci associated with height highlights new biological pathways in human growth.
    Nat Genet. 2008 May;40(5):584-91 PMID: 18391950
  22. Linkage disequilibrium in humans: models and data.
    Am J Hum Genet. 2001 Jul;69(1):1-14 PMID: 11410837
  23. Haplotypic analysis of Wellcome Trust Case Control Consortium data.
    Hum Genet. 2008 Apr;123(3):273-80 PMID: 18224336
  24. Calibrating a coalescent simulation of human genome sequence variation.
    Genome Res. 2005 Nov;15(11):1576-83 PMID: 16251467
  25. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls.
    Nature. 2007 Jun 7;447(7145):661-78 PMID: 17554300
  26. A second generation human haplotype map of over 3.1 million SNPs.
    Nature. 2007 Oct 18;449(7164):851-61 PMID: 17943122
  27. Leveraging the HapMap correlation structure in association studies.
    Am J Hum Genet. 2007 Apr;80(4):683-91 PMID: 17357074
  28. Practical aspects of imputation-driven meta-analysis of genome-wide association studies.
    Hum Mol Genet. 2008 Oct 15;17(R2):R122-8 PMID: 18852200
Article Info
Journal
American journal of human genetics
Abbr.
Am J Hum Genet
ISSN
1537-6605
Published
2009-02-00
Epub
2009-00-05
Pages
210-23
Language
English
Region
United States
NLM ID
0370475
PMCID
PMC2668004
Subset
IM
Grants
NIGMS NIH HHS · R01 GM075091 · United States
NIGMS NIH HHS · 3R01GM075091-02S1 · United States
Wellcome Trust · 076113 · United Kingdom
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