Demographic and evolutionary inferences from large, whole-genome datasets

来自大型全基因组数据集的人口统计和进化推论

• 批准号: DP210102168
• 负责人: Prof David Balding
• 金额: $ 28.56万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2021
• 资助国家: 澳大利亚
• 起止时间: 2021-06-18 至 2025-03-31
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP210102168
• 关键词: Demographic; evolutionary; inferences; large; whole

A new data structure for genome-wide datasets has allowed great improvements in the efficiency of genomic data storage and in population genomics simulations, which are crucial to developing and testing mathematical models of population history and species evolution. We will take these advances in new directions, using efficient data structures to dramatically improve inferences about: the demographic histories of populations, rates of genome change, and phylogenetic networks, and we will develop the first inference methods for the multispecies coalescent with recombination. Outcomes will include advances in understanding the evolutionary histories of humans and other species, including pathogens of importance for global health.

全基因组数据集的新数据结构极大地提高了基因组数据存储和种群基因组学模拟的效率，这对于开发和测试种群历史和物种进化的数学模型至关重要。我们将把这些进步带向新的方向，使用有效的数据结构来显著提高对人口统计历史、基因组变化率和系统发育网络的推断，我们将开发第一个多物种合并重组的推断方法。结果将包括在了解人类和其他物种的进化史方面取得进展，包括对全球健康具有重要意义的病原体。