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Maximum likelihood estimation of individual inbreeding coefficients and null allele frequencies

机译:各个近交系数和无效等位基因频率的最大似然估计

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In this paper, we developed and compared several expectation-maximization (EM) algorithms to find maximum likelihood estimates of individual inbreeding coefficients using molecular marker information. The first method estimates the inbreeding coefficient for a single individual and assumes that allele frequencies are known without error. The second method jointly estimates inbreeding coefficients and allele frequencies for a se: of individuals that have been genotyped at several loci. The third method generalizes the second method to include the case in which null alleles may be present. In particular, it is able to jointly estimate individual inbreeding coefficients and allele frequencies, including the frequencies of null alleles, and accounts for missing data. We compared our methods with several other estimation procedures using simulated data and found that our methods perform well. The maximum likelihood estimators consistently gave among the lowest root-mean-square-error (RMSE) of all the estimators that were compared. Our estimator that accounts for null alleles performed particularly well and was able to tease apart the effects of null alleles, randomly missing genotypes and differing degrees of inbreeding among members of the datasets we analysed. To illustrate the performance of our estimators, we analysed previously published datasets on mice (Mus musculus) and white-tailed deer (Odocoileus virginianus).
机译:在本文中,我们开发并比较了几种期望最大化(EM)算法,以使用分子标记信息找到各个近交系数的最大似然估计。第一种方法估计单个个体的近交系数,并假定等位基因频率是已知的,没有错误。第二种方法联合估计了在几个位点进行基因分型的个体的近亲繁殖系数和等位基因频率。第三种方法概括了第二种方法,以包括可能存在无效等位基因的情况。特别地,它能够联合估计各个近交系数和等位基因频率,包括无效等位基因的频率,并说明缺失的数据。我们使用模拟数据将我们的方法与其他几种估计程序进行了比较,发现我们的方法表现良好。在所有被比较的估计量中,最大似然估计量始终给出最低的均方根误差(RMSE)。我们的估计无效等位基因的估算者表现特别出色,并且能够梳理无效等位基因,随机缺失的基因型和我们分析的数据集成员之间不同近交程度的影响。为了说明估算器的性能,我们分析了先前发表的有关小鼠(小家鼠)和白尾鹿(Odocoileus virginianus)的数据集。

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