Issue |
Genet. Sel. Evol.
Volume 33, Number 6, November-December 2001
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Page(s) | 587 - 603 | |
DOI | https://doi.org/10.1051/gse:2001133 |
Genet. Sel. Evol. 33 (2001) 587-603
A sampling algorithm for segregation analysis
Bruce Tier and John HenshallAnimal Genetics and Breeding Unit, University of New England, Armidale NSW 2351, Australia
(Received 27 June 2000; accepted 12 June 2001)
Abstract
Methods for detecting Quantitative Trait Loci (QTL) without markers
have generally used iterative peeling algorithms for determining
genotype probabilities. These algorithms have considerable
shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC)
method which samples the pedigree of the whole population jointly is
described. Simultaneous sampling of the pedigree was achieved by
sampling descent graphs using the Metropolis-Hastings algorithm. A
descent graph describes the inheritance state of each allele and
provides pedigrees guaranteed to be consistent with Mendelian
sampling. Sampling descent graphs overcomes most, if not all, of the
limitations incurred by iterative peeling algorithms. The algorithm
was able to find the QTL in most of the simulated populations.
However, when the QTL was not modeled or found then its effect was
ascribed to the polygenic component. No QTL were detected when they
were not simulated.
Key words: descent graphs / Monte Carlo Markov chain / quantitative trait loci / Metropolis-Hastings
Correspondence and reprints: Bruce Tier
e-mail: btier@pobox.une.edu.au
© INRA, EDP Sciences 2001