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Population genomics & the coalescent

Explore how Ancestral Population Genomics uses a coalescent hidden Markov model to estimate key population parameters.

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Blogger Thomas Mailund is an author on a new paper, Ancestral Population Genomics: The Coalescent Hidden Markov Model Approach:

With incomplete lineage sorting (ILS), the genealogy of closely related species differs along their genomes. The amount of ILS depends on population parameters such as the ancestral effective population sizes and the recombination rate, but also on the number of generations between speciation events. We use a hidden Markov model parametrized according to coalescent theory in order to infer the genealogy along a four-species genome alignment of closely related species, and estimate population parameters. We analyze a basic, panmictic demographic model and study its properties using an extensive set of coalescent simulations. We assess the effect of the model assumptions, and demonstrate that the Markov property provides a good approximation to the ancestral recombination graph. Using a too restricted set of possible genealogies, necessary to reduce the computational load, can bias ...

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