Molecular Biology and Evolution, Vol 12, 921-927, Copyright © 1995 by Society for Molecular Biology and Evolution
L Excoffier and M Slatkin
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.
ORIGINAL ARTICLE
Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population
Department of Anthropology, University of Geneva, Switzerland.
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