Sampling Designs and Statistical Methods for the Analysis of Complex Life History and Genetic Data

用于分析复杂生活史和遗传数据的抽样设计和统计方法

• 批准号: RGPIN-2020-05528
• 负责人: Yilmaz, Yildiz
• 金额: $ 1.31万
• 依托单位: Memorial University of Newfoundland
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=717697
• 关键词: Sampling; Designs; Statistical; Methods; Analysis

The objective of this research program is to develop novel statistical modeling approaches and methods to identify the genetic basis of complex traits. A complex trait is one that is not straightforwardly determined by a single gene but is instead, determined by numerous genetic and environmental factors. It is difficult to isolate how any genetic factor affects the way a trait is expressed. This is because the effect of any factor may be very small, or some factors may be rare genetic variants that are not often observed in the population. Also, these factors may interact with each other and the environment. Development of informative statistical modeling approaches, appropriate and efficient sampling designs and methods of analysis is essential to detect and understand the role of such factors. My program of research, and the plan proposed for the next 5 years is mainly focused on development of novel informative statistical modeling approaches and efficient methods for the analysis of time-to-event complex traits and life history data and evaluation of sampling designs for life history analysis. Providing more informative and powerful analytical tools will enable researchers to better understand the underlying biological mechanisms of complex traits. In addition, this program will enable to train highly qualified personnel in Statistical Sciences.

该研究项目的目标是开发新的统计建模方法和手段，以确定复杂性状的遗传基础。复杂性状不是由单个基因直接决定的，而是由许多遗传和环境因素决定的。很难分离出任何遗传因素如何影响性状的表达方式。这是因为任何因素的影响可能非常小，或者某些因素可能是在人群中不常观察到的罕见遗传变异。此外，这些因素可能会相互作用，并与环境。开发信息丰富的统计建模方法、适当和有效的抽样设计和分析方法对于检测和了解这些因素的作用至关重要。我的研究计划和未来5年的计划主要集中在开发新的信息统计建模方法和有效的方法，用于分析时间到事件的复杂性状和生活史数据，以及评估生活史分析的抽样设计。提供更多信息和强大的分析工具将使研究人员能够更好地了解复杂性状的潜在生物学机制。此外，该计划将能够培养统计科学方面的高素质人才。