Evolutionary analyses of short-read sequences from pooled samples

合并样本中短读序列的进化分析

• 批准号: DP160103474
• 负责人: Prof Allen Rodrigo
• 金额: $ 34.61万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-06-30 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP160103474
• 关键词: Evolutionary; analyses; short; read; sequences

This project aims to provide biologists with a means of making sound, statistical inferences about evolution by using next-generation data from mixed samples. When biologists make statements about history, they use evolutionary trees, frequently reconstructed from the genetic data of many individuals. Next-generation sequencing provides large amounts of genetic data at low cost, but biologists have difficulty using these data for evolutionary research, particularly when they sample mixtures of DNA from many individuals. The anticipated value of this project is that it allows evolutionary biologists to capitalise on the benefits of next-generation sequencing, without sacrificing their ability to make reliable inferences about history.

该项目旨在为生物学家提供一种方法，通过使用混合样本的下一代数据，对进化进行合理的统计推断。当生物学家陈述历史时，他们使用进化树，经常从许多个体的遗传数据中重建。下一代测序技术以低成本提供了大量的基因数据，但生物学家很难将这些数据用于进化研究，特别是当他们从许多个体中取样混合DNA时。这个项目的预期价值在于，它允许进化生物学家利用下一代测序的好处，而不会牺牲他们对历史做出可靠推断的能力。