A Likelihood-Free Estimator of Population Structure Bridging Admixture Models and Principal Components Analysis
A Likelihood-Free Estimator of Population Structure Bridging Admixture Models and Principal Components Analysis
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DOI：
10.1534/genetics.119.302159
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发表时间：
2019-08-01
期刊：
影响因子：
3.3
通讯作者：
Storey, John D.
中科院分区：
文献类型：
--
作者：
Cabreros, Irineo;Storey, John D.
我们介绍了一种简单而高效的方法来拟合遗传种群结构的混合模型，称为ALStructure。ALStructure的策略是首先估计种群混合分量的低维线性子空间，然后在该子空间中搜索与混合模型的自然概率约束一致的模型。这一策略的核心是观察到，属于这个受约束的解空间的所有模型都是风险最小化的，并且具有相等的可能性，使得任何额外的优化都不必要。低维线性子空间通过最近引入的适合于基因型数据的主成分分析方法来估计，从而提供了既具有主成分又具有概率混合解释的解决方案。我们的方法与其他现有的混合估计方法有根本的不同，其他方法的目的是通过寻找最大化似然函数或后验概率的参数来直接拟合混合模型。我们观察到，在大量模拟和真实的人类基因数据集上，ALStructure通常在准确性和计算速度上都优于现有的方法。在这项工作中，我们强调，混合模型是一类更广泛的模型的特例，类似ALStructure的算法可以成功地应用于这些模型。刻画人类的遗传变异是统计遗传学中的一项重要任务，使得在基因组范围的关联研究中绘制疾病基因图谱成为可能，并为人类进化史的研究提供信息。量化遗传变异的一种常见方法是...
We introduce a simple and computationally efficient method for fitting the admixture model of genetic population structure, called ALStructure. The strategy of ALStructure is to first estimate the low-dimensional linear subspace of the population admixture components, and then search for a model within this subspace that is consistent with the admixture model's natural probabilistic constraints. Central to this strategy is the observation that all models belonging to this constrained space of solutions are risk-minimizing and have equal likelihood, rendering any additional optimization unnecessary. The low-dimensional linear subspace is estimated through a recently introduced principal components analysis method that is appropriate for genotype data, thereby providing a solution that has both principal components and probabilistic admixture interpretations. Our approach differs fundamentally from other existing methods for estimating admixture, which aim to fit the admixture model directly by searching for parameters that maximize the likelihood function or the posterior probability. We observe that ALStructure typically outperforms existing methods both in accuracy and computational speed under a wide array of simulated and real human genotype datasets. Throughout this work, we emphasize that the admixture model is a special case of a much broader class of models for which algorithms similar to ALStructure may be successfully employed.Characterizing genetic variation in humans is an important task in statistical genetics, enabling disease-gene mapping in genome-wide association studies (GWAS) and informing studies of human evolutionary history. A common approach to quantifying genetic variation...