III: Small: Computational Methods for Ancestry Inference In Genetics

许多人对自己的祖先很感兴趣。传统上，历史记录是了解一个人祖先的主要信息来源。在基因组学时代，分析一个人的基因组正在成为最流行的祖先测试方式。公司现在为数百万客户提供这样的测试。如今，大量涌入的DNA血统测试不仅让人们对自己有所了解，也让人们对自己的祖先有了更多的了解。人们提出了一些有趣的问题，即一个人能从自己的DNA中了解到多少关于他或她最近的祖先的信息。最近，这位研究人员一直在与一位人口遗传学家合作，开发从个体基因组推断最近祖先的计算方法。想象一下，一个小女孩爱丽丝，既有欧洲血统，也有美洲原住民血统，她想知道一些关于她最近的祖先的事情。现有的商业血统测试提供了对爱丽丝基因组基因组成的估计（例如，爱丽丝dna的百分比或可以追溯到美洲土著血统的长基因组片段）。另一方面，研究者和他的合作者考虑的问题是，从爱丽丝的基因组中推断出最近祖先的基因组成。也就是说，研究者的目的是回答诸如“我只有我自己的基因组，但我想知道我最近的祖先。”我的父母是50%的欧洲人和50%的印第安人吗？或者一个是未混合的欧洲人另一个是未混合的印第安人？我的祖父母呢？”这些问题在以前的文献中没有得到严格的解决，尽管这些问题可能对遗传学家和基因测试的消费者都感兴趣。为了解决这些问题，研究者将研究基于dna的祖先推断的新计算方法。研究者计划以他最近的研究为基础，利用PedMix方法，从焦点个体的基因组中推断出最近的祖先（例如父母和祖父母）的祖先。目前，PedMix是唯一一种公开可用的方法，可以从单个个体的基因组中推断出最近的祖先。在这个项目中，研究者计划对祖先推断的一般主题进行研究。第一个目标是提高PedMix的性能，以获得更准确的推理结果。这可以使PedMix更适用于实际的基因测试。第二个目标是开发祖先推理方法，可以学习更遥远祖先的祖先信息。目前，由于计算难度，PedMix最多只能用于曾祖推理。最后，本项目还旨在研究新的祖先推理公式，这些公式以前没有得到严格的研究。这个项目的关键技术方面是计算效率。本项目研究的成功完成将产生新的高效和准确的算法，这些算法将在实用的软件工具中实现，并能够从大规模基因组学数据中进行新的祖先推断。开发的软件工具将免费提供给多学科研究界，并有望在基于dna的祖先推断中实现新的生物学应用。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Many people are interested in their ancestry. Traditionally, historical records are the main sources of information for knowing one's ancestry. In the age of Genomics, analyzing one's genome is becoming the most popular way of ancestry test. Companies now offer such tests to millions of customers. The influx of DNA ancestry tests now make people know not only something about themselves, but also more about their ancestors. Interesting questions have been raised about how much one can learn about his or her recent ancestors from one's own DNA. Recently, the investigator has been working with a population geneticist on developing computational methods for inferring recent ancestors from an individual's genome. Imagine that a little girl, Alice, has both European and Native American heritage and wants to know something about her recent ancestors. Existing commercial ancestry tests provide estimates of genetic composition on Alice's genome (e.g., percentage of Alice's DNAs or long genomic segments that can be traced to Native American origin). The problem considered by the investigator and his collaborators, on the other hand, concerns the inference of the genetic composition of recent ancestors from Alice's genome. That is, the investigator aims to answer questions such as "I only have my own genome but I want to know about my recent ancestors. Are my parents 50%-50% European and Native American? Or one is unadmixed European and the other is unadmixed Native American? How about my grandparents?" Such questions have not been rigorously addressed in the literature before, even though these questions may be of interests to both geneticists and consumers of genetic tests. To address these questions, the investigator will work on new computational methods for DNA-based ancestry inference. The investigator plans to build on his recent research on this subject, the PedMix approach, which can infer the ancestry of recent ancestors (e.g., parents and grandparents) from a focal individual's genome. At present, PedMix is the only publically available method for inferring recent ancestors from a single individual's genome. In this project, the investigator plans to conduct research on the general subject of ancestry inference. The first objective is to improve the performance of PedMix to obtain more accurate inference results. This can make PedMix more applicable and practical to real genetic tests. The second objective is developing ancestry inference methods which can learn ancestry information for more distant ancestors. At present, due to computational difficulty, PedMix can only work for great grandparental inference at most. Finally, this project also aims to study new ancestry inference formulations which haven't been rigorously studied before. The key technical aspect of this project is computational efficiency. Successful completion of the research in this project will produce new efficient and accurate algorithms that are implemented in practical software tools and enable new ancestry inference from large scale genomics data. Developed software tools will be made available freely to the multidisciplinary research community, and are expected to enable novel biological applications in DNA-based ancestry inference.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.