Special Issue on Models and Inference in Population Genetics
Simulation of stochastic models of structured population in population genetics under neutrality
[Simulation de modèles stochastiques de populations structurées en génétique des populations sous neutralité]
Journal de la société française de statistique, Tome 159 (2018) no. 3, pp. 126-141.

Cet article décrit quelques modèles de génétique des populations sous neutralité, incluant dérive génétique et mutations. À partir du coalescent de Kingman, nous montrons comment on peut modéliser des populations structurées. Nous détaillons ces modèles en montrant comment il est possible d’écrire des algorithmes de simulations. En particulier, nous mettons en avant l’ensemble des processus latents qui rendent le calcul de la fonction de vraisemblance sur un jeu de données difficile, voire impossible.

This paper describes some population genetic models under neutrality, involving genetic drift and mutations. Starting with Kingman’s coalescent we show how structured populations can be modeled. We detail these models by showing how simulation algorithms can be written. In particular we highlight the latent processes than rule out the explicit computation of the likelihood function on a dataset.

Keywords: population genetics, Kingman coalescent process, intractable likelihood
Mot clés : génétique des populations, processus de coalescence de Kingman, vraisemblance intraitable 
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Pudlo, Pierre; Sedki, Mohammed. Simulation of stochastic models of structured population in population genetics under neutrality. Journal de la société française de statistique, Tome 159 (2018) no. 3, pp. 126-141. http://archive.numdam.org/item/JSFS_2018__159_3_126_0/

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