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大规模个体最近祖先起源的估计

Estimation of Recent Ancestral Origins of Individuals on a Large Scale
课程网址: http://videolectures.net/kdd2017_curtis_ancestral_origins/  
主讲教师: Ross E. Curtis
开课单位: 信息不详。欢迎您在右侧留言补充。
开课时间: 2017-10-09
课程语种: 英语
中文简介:
过去十年里,直接面向消费者的基因组学检测呈指数级增长。这些测试的一个受欢迎的特点是对远祖推断档案的报告——一份被测试者祖先可能生活过的世界地区的分类报告。虽然目前的方法和产品通常专注于更遥远的过去(例如,数千年前),但我们最近证明,通过利用网络分析工具,如社区检测,可以识别更近的祖先。然而,在一个可能有数百万个节点的大型网络上使用社区检测这样的网络分析工具,在每天需要处理数百或数千个新基因型的实时生产环境中是不可实现的。在这项研究中,我们描述了一种分类方法,利用网络特征将个体分配到与最近祖先对应的大型网络中的社区。我们将在AncestryDNA上推出这个研究的一个新版本
课程简介: The last ten years have seen an exponential growth of direct-to-consumer genomics tests. One popular feature of these tests is the report of a distant ancestral inference profile—a breakdown of the regions of the world where the test-takers’ ancestors may have lived. While current methods and products generally focus on the more distant past (e.g., thousands of years ago), we have recently demonstrated that by leveraging network analysis tools such as community detection, more recent ancestry can be identified. However, using a network analysis tool like community detection on a large network with potentially millions of nodes is not feasible in a live production environment where hundreds or thousands of new genotypes need to be processed every day. In this study, we describe a classification method that leverages network features to assign individuals to communities in a large network corresponding to recent ancestry. We will be launching a version of this research as a new product feature at AncestryDNA.
关 键 词: 远祖推断; 识别祖先; 网络分析
课程来源: 视频讲座网
数据采集: 2022-11-11:chenxin01
最后编审: 2023-05-18:liyy
阅读次数: 26