Maximum-likelihood and markov chain monte carlo approaches to estimate inbreeding and effective size from allele frequency changes.
Maximum-likelihood and markov chain monte carlo approaches to estimate inbreeding and effective size from allele frequency changes.
复制标题
最大似然和马尔可夫链蒙特卡罗方法根据等位基因频率变化估计近交和有效大小。
作者：
G. Laval;M. Sancristobal;C. Chevalet
最大样子和贝叶斯（MCMC算法）的估计值是Wright-Malécot杂种财务的增加，F（t）在两个临时间隔样本之间的F（t）是从等位基因频率分布（Model MD）的dirichlet近似以及iNdmixture开发的DIRICHLET近似和等位基因丢失的可能性（Model MDL）。 10％或以下。根据MDL模型的最大样品方法是F（t）的最佳估计值，只要在创始人频率中估算出一个有限的创始人动物，只有初始频率。基于MD的估计可以在这种情况下使用。当使用表现出低多态性的标记（例如SNP标记）时，就发现了有关有效人口大小的所有新估计值时，发现此处提出的所有新估计值都比经典的F统计量更好。
Maximum-likelihood and Bayesian (MCMC algorithm) estimates of the increase of the Wright-Malécot inbreeding coefficient, F(t), between two temporally spaced samples, were developed from the Dirichlet approximation of allelic frequency distribution (model MD) and from the admixture of the Dirichlet approximation and the probabilities of fixation and loss of alleles (model MDL). Their accuracy was tested using computer simulations in which F(t) = 10% or less. The maximum-likelihood method based on the model MDL was found to be the best estimate of F(t) provided that initial frequencies are known exactly. When founder frequencies are estimated from a limited set of founder animals, only the estimates based on the model MD can be used for the moment. In this case no method was found to be the best in all situations investigated. The likelihood and Bayesian approaches give better results than the classical F-statistics when markers exhibiting a low polymorphism (such as the SNP markers) are used. Concerning the estimations of the effective population size all the new estimates presented here were found to be better than the F-statistics classically used.
使用最大似然根据等位基因频率的时间变化来估计种群大小。
影响因子：
3.3
作者：
Williamson,EG;Slatkin,M
通讯作者：
Slatkin,M
对时间间隔样本的 N(e) 的可能性进行蒙特卡罗评估。
影响因子：
3.3
作者：
Anderson,EC;Williamson,EG;Thompson,EA
通讯作者：
Thompson,EA