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phyddle:用于使用深度学习探索家族遗传模型的软件

Michael J Landis¹, Ammon Thompson²

¹Department of Biology, Washington University, St. Louis, MO, 63110, USA.

Systematic biology

|May 14, 2025

概括

遗传学建模现在使用phyddle软件的深度学习,使复杂的进化模型缺乏标准概率函数的分析成为可能. 这种方法准确地估计参数和选择模型,推进进化生物学研究.

科学领域:

进化生物学进化生物学
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:

遗传学模型对于理解生命的多样性和进化历史至关重要.
标准推理方法与缺乏可处理的概率函数的现实类遗传模型作斗争.
需要能够处理复杂的遗传学模型的计算工具.

研究的目的:

介绍phyddle,一个新的软件管道用于使用无概率的深度学习进行遗传学建模.
为了证明phyddle在树木上执行遗传学建模任务的能力.
提供灵活的工具,将深度学习融入进化研究工作流程中.

主要方法:

菲德尔使用了一个管道方法,有五个步骤:模拟,格式,训练,估计和绘图.
该软件使用无概率的深度学习方法来分析遗传学数据.
遗传学数据集从原始输入转化为基于数值和视觉模型的输出.

主要成果:

菲德尔准确地执行了家族遗传推断任务,包括宏观进化参数估计和持续特征进化的模型选择.
该软件成功通过了流行病学模型的覆盖测试,即使是那些具有难以处理的可能性的模型.
基准表明phyddle基于深度学习的推断与传统基于概率的方法之间的准确性相似.

结论:

菲德尔 (Phyddle) 提供了一种强大而灵活的基因模型解决方案,特别是在具有复杂或难以处理的概率函数的模型中.
该软件有助于将先进的深度学习技术集成到进化生物学研究中.
Phyddle增强了从家族遗传树中提取进化见解的能力,即使在具有挑战性的建模场景中也是如此.

关键词:

深度学习是一种深度学习.神经网络的神经网络的神经网络人类遗传学遗传学软件软件软件软件软件在统计模型中使用统计模型.

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