Collaborative Research: ABI Innovation: Visualization and Statistics for Spatial Population Genomic Analysis

南加州大学和加州戴维斯大学被授予合作赠款，以创建方法和软件，从基因组数据生成地图，以及解决在地图上放置未知来源的样本的相关问题。 彼此关系更密切的生物体具有更多相似的基因组。 通常，一个生物体和它的亲戚生活在相当近的地方，所以原则上，许多不同生物体之间的基因组相似性可以用来构建当地地理图。 在这张地图中，距离对应于生物体旅行的容易程度;因此地图将显示“生物体所看到的”景观。 具体来说，这里开发的方法将以允许优化几个不同标准的方式构建这些图谱，并将使用随机化算法进行模式识别，以允许对大型基因组数据集进行有效计算。 另一套相关的方法将使用地质统计学的新兴工具，在这些地图上放置其他人，并严格量化不确定性。从基因组数据中描述地理模式，以及未知样本的位置，将有许多应用。 这些工具可用于识别新入侵寄生虫的起源，或识别划分濒危物种范围的关键障碍。它们将对推断祖先感兴趣，并且可能用于定位，例如，一个人的祖父可能在100公里左右的范围内的家。它们还可以用来形象化现代种群之间的关系;例如，人类的现代分布反映了大规模和小规模迁移的复杂历史;或者我们对其他物种的迁移生态学知之甚少。作为该提案的一部分，开发的简单，交互式，动画图形将有助于为研究人员提供一种新的显示信息的方式，并有助于下一代数据可视化领域。为了进一步有效传播遗传学成果，将在地方和国家会议上举办短期讲习班，通过本提案聘用的博士后研究员和/或研究生将发挥主导作用。由此产生的工具将在www.example.com和www.example.com上分发和讨论。

The University of Southern California and the University of California Davis are awarded collaborative grants to create methods and software to generate maps from genomic data, as well as to solve the related problem of placing samples of unknown origin on the map. Organisms that are more closely related to each other have more similar genomes. Often, an organism and its relatives live fairly nearby, so in principle genome similarity between many different organisms can be used to construct a map of the local geography. In this map, distances correspond to how easy it is for the organism to travel; so the map will display the landscape "as the organism sees it". Specifically, the methods developed here will construct these maps in a way to allow optimization of several different criteria, and will use randomized algorithms for pattern identification to allow efficient computation on large genomic datasets. The other, related suite of methods will use emerging tools from geostatistics to place other individuals on these maps, with rigorously quantified uncertainty. The description of geographic patterns from genomic data, and location of unknown samples, will have many applications. These tools could be used to identify the origin of a newly invading parasite, or to identify key barriers dividing the range of an endangered species. They will be of interest for inferring ancestry, and might be used to locate, for instance, the likely home of a person's grandfather to within 100km or so. They can also be used to visualize the relationships between modern populations; for instance, of humans, whose modern distribution reflects a complex history of large- and small-scale migrations; or of other species for which we often know little about their migration ecology. The simple, interactive, animated graphics developed as part of this proposal will help give researchers a new way of displaying informationand contribute to the field of next-generation data visualization. To further enable effective communication of genetic results, short workshops will be offered both locally and at national meetings, with the post-doctoral fellow and/or graduate students hired through this proposal taking a leading role. The resulting tools will be distributed and discussed at http://ralphlab.usc.edu/ and http://gcbias.org/.