Model inference, comparison, and averaging for genetically structured populations

遗传结构群体的模型推理、比较和平均

• 批准号: 1145999
• 负责人: Peter Beerli
• 金额: $ 32.7万
• 依托单位: Florida State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1145999&HistoricalAwards=false
• 关键词: Model; inference; comparison; averaging; genetically

Researchers collect genetic data to assess variability of animal and plant populations and their ancestral relationships. For such datasets, thousands of different relationships can be specified. For example, are polar bear populations isolated from each other and if not what is the pattern of relationships of polar bears from different populations? This research will develop new methods to calculate the likelihood of different patterns of relationships using Bayesian inference. These methods will be coded into freely available software that will be able to evaluate large data sets. This will achieve accurate ranking of alternative hypotheses using genomic data sets considering complexities such as recombination and data collection artifacts.This study will provide freely available software along with a user manual for the research community. The new methods will facilitate many types of studies, including disease epidemics, and the studies of the effect of changes in climate onto the distribution and maintenance of genetic variability in crop-related and other species. The software will be disseminated through online tutorials and workshops aimed at senior researchers. There will also be two workshops on computer literacy for individuals ranging from high-school science teachers, to undergraduates, and graduate students.

研究人员收集遗传数据，以评估动物和植物种群的变异性及其祖先关系。对于这样的数据集，可以指定数千种不同的关系。例如，北极熊种群是否彼此隔离，如果不是，不同种群的北极熊之间的关系模式是什么？这项研究将开发新的方法来计算不同模式的关系使用贝叶斯推理的可能性。这些方法将编入免费提供的软件，以便能够评估大型数据集。这将使用基因组数据集实现替代假设的准确排名，考虑到重组和数据收集artifacts.This study will provide freely available software沿着a user manual for the research community。这些新方法将促进许多类型的研究，包括疾病流行，以及研究气候变化对作物相关物种和其他物种遗传变异的分布和维持的影响。该软件将通过针对高级研究人员的在线教程和讲习班传播。还将举办两个关于计算机知识的讲习班，对象包括高中科学教师、本科生和研究生。