Population Genetics Models with Skewed Fertilities: A Forward and Backward Analysis
Population Genetics Models with Skewed Fertilities: A Forward and Backward Analysis
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生育率倾斜的群体遗传学模型：前向和后向分析
DOI：
10.1080/15326349.2011.593411
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发表时间：
2011
影响因子：
0.7
通讯作者：
M. Möhle
中科院分区：
文献类型：
--
作者：
T. Huillet;M. Möhle
离散人口的遗传学模型与不平等（偏斜）受精被认为是，侧重于倾斜版本的坎宁模型，条件分支过程模型的精神，卡林和麦格雷戈，复合泊松模型。三个特定类别的模型与偏态受精率进行了研究，赖特-费舍尔模型，狄利克雷模型，木村模型。对于每个类的渐近行为的总人口规模N趋于无穷大的幂律肥料和几何肥料。这类模型可以表现出丰富的各种次线性甚至恒定的有效种群大小。因此，模型不一定在金曼聚结剂的吸引域中。对于一个相当大的范围内的参数，离散时间的聚结过程，同时多个碰撞出现的限制。
Discrete population genetics models with unequal (skewed) fertilities are considered, with an emphasis on skewed versions of Cannings models, conditional branching process models in the spirit of Karlin and McGregor, and compound Poisson models. Three particular classes of models with skewed fertilities are investigated, the Wright–Fisher model, the Dirichlet model, and the Kimura model. For each class the asymptotic behavior as the total population size N tends to infinity is investigated for power law fertilities and for geometric fertilities. This class of models can exhibit a rich variety of sub-linear or even constant effective population sizes. Therefore, the models are not necessarily in the domain of attraction of the Kingman coalescent. For a substantial range of the parameters, discrete-time coalescent processes with simultaneous multiple collisions arise in the limit.