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Autors principals: Eriksson, A., Mahjani, B., Mehlig, B.
Format: Preprint
Publicat: 2009
Matèries:
Accés en línia:https://arxiv.org/abs/0901.2867
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author Eriksson, A.
Mahjani, B.
Mehlig, B.
author_facet Eriksson, A.
Mahjani, B.
Mehlig, B.
contents 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 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. 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 gene-history correlations may be significantly underestimated. We explain why this is the case.
format Preprint
id arxiv_https___arxiv_org_abs_0901_2867
institution arXiv
publishDate 2009
record_format arxiv
spellingShingle Sequential Markov coalescent algorithms for population models with demographic structure
Eriksson, A.
Mahjani, B.
Mehlig, B.
Populations and Evolution
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 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. 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 gene-history correlations may be significantly underestimated. We explain why this is the case.
title Sequential Markov coalescent algorithms for population models with demographic structure
topic Populations and Evolution
url https://arxiv.org/abs/0901.2867