New tools for the rapid analysis of Poliovirus genomic surveillance data

用于快速分析脊髓灰质炎病毒基因组监测数据的新工具

• 批准号: 2683235
• 金额: --
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2683235
• 关键词: New; tools; rapid; analysis; Poliovirus

This project aims to apply a range of phylogeographic models to quantify the geographic spread of poliovirus. This analysis aims to produce a protocol which can be implemented downstream of standard sanger sequencing and next generation sequencing methods being trialled within the vaccine epidemiology research group and will include tree construction and visualisation methods. -To improve on current phylogenetic methods used to infer phylogenies for wild poliovirus 10 in Pakistan and Afghanistan. - Analyses based on new epidemiological blocks of transmission with genetically related poliovirus and connected human demography. - Discrete trait analysis fitting to infer geographic location of internal nodes in the phylogeny and determine movement of virus between epidemiological blocks. - Extension of discrete trait methods to quantify the influence of incomplete sampling on the movement rates inferred. - Application of coalescent approximations to better understand the influence of incomplete sampling. This may not be possible on the full data set provided for endemic countries as the number of states and lineages to be considered is too large. - To provide visualisations of genetic data for poliovirus with more coherent and relevant information for policymakers. - Simple workflow from phylogenetic output to visualisation in R. - Inclusion of information deemed to be of importance by policymakers. - Form code in to an R package or code notebook to provide the visualisation functionality for use on other datasets.

该项目旨在应用一系列系统地理学模型来量化脊髓灰质炎病毒的地理传播。该分析旨在制定一项协议，该协议可以在标准桑格测序和疫苗流行病学研究小组正在试验的下一代测序方法的下游实施，并将包括树的构建和可视化方法。-改进目前用于推断巴基斯坦和阿富汗10型野生脊髓灰质炎病毒系统发育的系统发育方法。-根据与遗传相关的脊髓灰质炎病毒传播的新流行病学块和相关的人口统计学进行分析。-离散性状分析拟合，以推断系统发育内部节点的地理位置，并确定病毒在流行病学块之间的运动。-扩展离散特征方法，以量化不完整采样对推断的移动速率的影响。-应用聚结近似来更好地理解不完全抽样的影响。在为流行国家提供的完整数据集上可能无法做到这一点，因为要考虑的州和血统数量太大。-提供脊髓灰质炎病毒遗传数据的可视化，为决策者提供更连贯和相关的信息。-从系统发育输出到r语言可视化的简单工作流程-包含决策者认为重要的信息。-将代码放入R包或代码笔记本中，以提供用于其他数据集的可视化功能。