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Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population.
Open accessAbstract
Molecular techniques allow the survey of a large number of linked polymorphic loci in random samples from diploid populations. However, the gametic phase of haplotypes is usually unknown when diploid individuals are heterozygous at more than one locus. To overcome this difficulty, we implement an expectation-maximization (EM) algorithm leading to maximum-likelihood estimates of molecular haplotype frequencies under the assumption of Hardy-Weinberg proportions. The performance of the algorithm is evaluated for simulated data representing both DNA sequences and highly polymorphic loci with different levels of recombination. As expected, the EM algorithm is found to perform best for large samples, regardless of recombination rates among loci. To ensure finding the global maximum likelihood estimate, the EM algorithm should be started from several initial conditions. The present approach appears to be useful for the analysis of nuclear DNA sequences or highly variable loci. Although the algorithm, in principle, can accommodate an arbitrary number of loci, there are practical limitations because the computing time grows exponentially with the number of polymorphic loci. Although the algorithm, in principle, can accommodate an arbitrary number of loci, there are practical limitations because the computing time grows exponentially with the number of polymorphic loci.
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“Often, genotypes can be resolved into several possible haplotypes, and inferred frequencies of rare haplotypes can be quite wrong10.”
From Linkage disequilibrium--understanding the evolutionary past and mapping the medical future. (2008) · cites this paper as [10]
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Metadata
- Authors
- Excoffier, L., & Slatkin, M.
- Affiliations
- University of Geneva (CH)
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 1995-09
- Volume
- 12
- Issue
- 5
- Pages
- 921-7
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- OpenAlex
- W1891283710
- Cited by
- 1,950
- References
- 14
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 14 · 2023: 19 · 2022: 18 · 2021: 20 · 2020: 32 · 2019: 29 · 2018: 30 · 2017: 20 · 2016: 46 · 2015: 41 · 2014: 52 · 2013: 69 · 2012: 76
- FWCI
- 3.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Molecular Biology and Evolution (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (39847)
- National Institutes of Health
- National Institute of General Medical Sciences (GM-40282, R01GM040282)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- haplotype frequencies, maximum likelihood estimation, expectation-maximization algorithm, Hardy-Weinberg equilibrium, recombination, heterozygosity, diploid populations, multilocus analysis, computational complexity
- MeSH terms
- Algorithms, Animals, Diploidy, Gene Frequency, Haplotypes, Humans, Genetic Linkage, Mathematics, Models, Genetic, Monte Carlo Method, Probability, Regression Analysis, Models, Statistical
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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