一个对祖先重组图的一般和高效表示
Yan Wong1, Anastasia Ignatieva2,3, Jere Koskela4,5
1Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK.
bioRxiv : the preprint server for biology
|November 14, 2023
概括
祖先重组图 (ARG) 模型遗传遗传. 一种新的形式主义通过基因组和继承间隔来定义ARG,将古典和现代方法统一为更广泛的应用.
科学领域:
- 遗传学 遗传学是一种遗传学.
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 由于重组,遗传序列表现出不同的遗传路径.
- 祖先重组图 (ARG) 传统上通过凝聚和重组事件来建模这些路径.
- 现代方法越来越偏离基于事件的ARG推断.
研究的目的:
- 为祖先重组图 (ARG) 呈现一种新的,通用的形式主义.
- 展示这种形式主义是如何整合古典和当代ARG推理方法的.
- 在ARG分析中建立一个潜在软件标准的基础.
主要方法:
- 根据特定的基因组及其遗传遗传间隔来定义ARG.
- 将拟议的形式主义与经典基于事件的ARG模型进行比较.
- 评估形式主义与最近ARG推断方法的输出相容性.
主要成果:
- 新的形式主义为理解ARG提供了一个统一的框架.
- 它包括传统的基于事件的模型和现代基于序列的方法.
- 概括结构突出了古典形式主义中没有明显的细微差别.
结论:
- 基于基因组和间隔的ARG定义提供了更全面的视角.
- 这种通用形式主义适用于统一各种ARG推理方法.
- 它为开发计算遗传学的标准化软件框架提供了坚实的基础.
关键词:
祖先重组图表的图表.相关概念视频
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