Methods for inference of complex demography and selection from genomic data

描述（由申请人提供）：测序技术的最新进展从根本上改变了群体遗传学。利用全基因组DNA序列数据，种群遗传学家现在希望在涉及多个种群的复杂进化模型中共同估计许多感兴趣的参数。然而，许多可用于群体遗传分析的统计方法不能扩展到全基因组水平。这里提出的研究的主要目标是开发一套数学、统计和计算方法，使研究人员能够更充分地利用基因组数据的可用性。考虑到链接信息的基于似然的方法比基于汇总统计的方法利用数据中的更多信息，因此在统计上应该更有效。然而，它们往往需要密集的计算，从而限制了它们的适用性。目标1将开发一种新的全似然推断的统计方法，可以应用于基因组规模，使用比以前可能的更多的序列。共享遗传相似性片段的分布，即根据血统确定身份的片段或根据国家确定身份的片段，包含了关于过去人口统计学和选择的重要信息。目标2和3，将得出关于这些信息的新的理论结果，并将它们应用于开发新的统计方法来解决具有挑战性的问题，如估计混合比例和混合时间，以及混合DNA束的推断。近年来，利用等位基因频谱来估计复杂人口统计模型的参数受到了广泛的关注。目标4将开发基于聚结理论的有效方法，以计算比以前考虑的更多种群的预期联合等位基因频谱。Wright-Fisher扩散的使用在群体遗传学中是无处不在的，它是一个大群体中等位基因频率的时间动态模型。在一些群体遗传学应用中，研究相关的扩散桥是很自然的。目标5将研究模拟扩散桥的方法

DESCRIPTION (provided by applicant): Recent advances in sequencing technology has fundamentally transformed population genetics. Using whole-genome DNA sequence data, population geneticists now hope to estimate jointly many parameters of interest in complex models of evolution involving multiple populations. However, many of the statistical methods available for population genetic analyses are not scalable to the whole genome level. The main objective of the research proposed here is to develop a suite of mathematical, statistical, and computational methods that will allow researchers to more fully take advantage of the availability of genomic data. Likelihood-based approaches that take linkage information into account utilize more information in the data than do methods based on summary statistics and should therefore be more statistically efficient. However, they tend to require intensive computation, thus limiting their applicability. Aim 1 will develop a new statistical approach to ful-likelihood inference that can be applied at the genomic scale using many more sequences than previously possible. The distribution of segments of shared genetic similarity, i.e., segments of identity-by-descent or identity-by-state, contain important information about past demography and selection. Aims 2 and 3,will derive new theoretical results concerning such information and apply them to develop new statistical methods to tackle challenging problems such as the estimation of admixture proportions and admixture times, and inference of admixed DNA tracts. Recently, there has been much interest in using allele frequency spectra to estimate parameters in complex demography models. Aim 4 will develop efficient methods based on coalescent theory to compute the expected joint allele frequency spectra for more populations than could be previously considered. The use of the Wright-Fisher diffusion is ubiquitous in population genetics as a model for the forwards-in-time dynamics of the frequency of an allele in a large population. There are several population genetic applications in which it is natural to study the associated diffusion bridge. Aim 5 will investigate methods for simulating diffusion bridges in the presence of selection and obtain analytic results on the distribution of important functionals of the bridge path.