Maximum likelihood estimation of natural selection and allele age from time series data of allele frequencies
Maximum likelihood estimation of natural selection and allele age from time series data of allele frequencies
复制标题
根据等位基因频率的时间序列数据进行自然选择和等位基因年龄的最大似然估计
DOI：
10.1101/837310
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
He Z
中科院分区：
文献类型：
--
作者：
He Z
由于古代DNA制备和测序技术的进步，分离等位基因的时间序列样本在祖先群体中变得越来越广泛。这样的时间序列数据可以更准确地推断种群遗传参数，并对自然选择的近期作用进行假设检验。本文提出了一种基于似然的方法，从等位基因频率时间序列数据中估计选择系数和等位基因年龄。我们的方法是建立在隐马尔可夫模型上的，该模型结合了Wright-Fisher扩散，该扩散条件是存活到最近的样本时间，这规避了现有方法中等位基因是由特定小频率突变产生的假设。我们通过数值求解由条件Wright-Fisher扩散产生的Kolmogorov后向方程来计算似然，并通过每个采样时间点的观测发射概率重新加权解，从而减少了对选择系数和等位基因年龄似然面最大值的二维数值搜索。我们通过大量的模拟表明，我们的方法可以产生选择系数和等位基因年龄的无偏估计，即使样本在时间上分布稀疏且大小不均匀。我们通过重新分析与马皮毛颜色相关的古代DNA数据来说明我们的方法在真实数据上的实用性，并表明分组样本可以显著地影响推断结果。
Thanks to advances in ancient DNA preparation and sequencing techniques, time serial samples of segregating alleles are becoming more widely available in ancestral populations. Such time series data allow for more accurate inference of population genetic parameters and hypothesis testing on the recent action of natural selection. Here we develop a likelihood-based method for co-estimating the selection coefficient and the allele age from allele frequency time series data. Our method is built on the hidden Markov model incorporating the Wright-Fisher diffusion conditioned to survive until the time of the most recent sample, which circumvents the assumption required in existing methods that the allele is created by mutation at a certain small frequency. We calculate the likelihood by numerically solving the Kolmogorov backward equation resulting from the conditioned Wright-Fisher diffusion backwards in time and re-weighting the solution by the emission probabilities of the observation at each sampling time point, which allows for a reduction of the two-dimensional numerical search for the maximum of the likelihood surface for the selection coefficient and the allele age. We show through extensive simulations that our approach can produce unbiased estimates of the selection coefficient and the allele age, even if the samples are sparsely distributed in time with small uneven sizes. We illustrate the utility of our method on real data by re-analysing the ancient DNA data associated with horse coat colouration and show that grouping samples can significantly bias the results of inference.
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DOI：
10.1214/14-aoas764
发表时间：
2014-12
期刊：
The annals of applied statistics
影响因子：
--
作者：
Steinrücken M;Bhaskar A;Song YS
通讯作者：
Song YS
需要条件似然来估计古代 DNA 中的选择系数
影响因子：
4.6
作者：
A. Valleriani
通讯作者：
A. Valleriani
Wright-Fisher 扩散的近似马尔可夫模型及其在时间序列数据中的应用
影响因子：
3.3
作者：
A. Ferrer;Christoph Leuenberger;J. Jensen;Daniel Wegmann
通讯作者：
Daniel Wegmann
影响因子：
4.6
作者：
Wutke S;Benecke N;Sandoval-Castellanos E;Döhle HJ;Friederich S;Gonzalez J;Hallsson JH;Hofreiter M;Lõugas L;Magnell O;Morales-Muniz A;Orlando L;Pálsdóttir AH;Reissmann M;Ruttkay M;Trinks A;Ludwig A
通讯作者：
Ludwig A
牛的毛色：对热平衡、行为和生长的影响以及与毛色类型的关系
影响因子：
0.6
作者：
V. Finch;I. L. Bennett;C. Holmes
通讯作者：
C. Holmes