Sequential Markov coalescent algorithms for population models with demographic structure

A. Eriksson, B. Mahjani, B. Mehlig

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

We analyse sequential Markov coalescent algorithms for populations with demographic structure: for a bottleneck model, a population-divergence model, and for a two-island model with migration. The sequential Markov coalescent method is an approximation to the coalescent suggested by McVean and Cardin, and by Marjoram and Wall. Within this algorithm we compute, for two individuals randomly sampled from the population, the correlation between times to the most recent common ancestor and the linkage probability corresponding to two different loci with recombination rate R between them. These quantities characterise the linkage between the two loci in question. We find that the sequential Markov coalescent method approximates the coalescent well in general in models with demographic structure. An exception is the case where individuals are sampled from populations separated by reduced gene flow. In this situation, the correlations may be significantly underestimated. We explain why this is the case.

Original languageEnglish
Pages (from-to)84-91
Number of pages8
JournalTheoretical Population Biology
Volume76
Issue number2
DOIs
StatePublished - Sep 2009
Externally publishedYes

Keywords

  • Coalescent
  • Population structure
  • Recombination
  • Sequential Markov coalescent

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