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数据特定的替代模型改善了基于蛋白质的遗传学

João M Brazão¹, Peter G Foster², Cymon J Cox¹

¹Centro de Ciências do Mar, Universidade do Algarve, Faro, Algarve, Portugal.

|August 14, 2023

概括

对蛋白质进行准确,数据特定的氨基酸替代模型的估计对于植物遗传学分析至关重要. 这项研究发现,数据特定模型,特别是来自IQ-TREE和P4 (最大概率) 的模型,比实证模型提供更高的准确性和效率.

科学领域:

计算生物学计算生物学
人类遗传学是一个学科.
生物信息学是一种生物信息学.

背景情况:

估计准确的氨基酸替代模型对于遗传学分析至关重要,但在计算上具有挑战性.
现有的经验模型可能不能充分代表特定的蛋白质数据集,可能导致不准确的进化推断.

研究的目的:

评估五种用于估计特定数据的氨基酸替代模型的计算效率和准确性.
将特定数据模型的性能与常用的实证模型 (cpREV,WAG) 进行比较.
证明使用特定数据模型在已公布数据集的基因分析中的好处.

主要方法:

使用已知的模型和树来生成模拟的蛋白质对齐.
使用五种方法 (Codeml,FastMG,IQ-TREE,P4-ML,P4-贝叶斯) 来估计特定数据模型.
在数据特定和实证模型与模拟模型之间进行了最大概率得分和树拓的比较.

主要成果:

数据特定模型显著优于实证模型,显示更好的匹配和推断更准确的树.
IQ-TREE和P4 (最大概率) 方法产生了与模拟模型在统计学上无法区分的树木.
用IQ-TREE估计模型重新分析已发布的数据集,发现超过一半的案例数据匹配度有所改善,推断树长,拓结构改变.

结论:

数据特定的氨基酸替代模型提供了比实证模型更准确的蛋白质进化表现.
建议使用IQ-TREE和P4 (最大概率),因为它们在估计这些模型中的准确性和效率.
计算负担和软件的可用性不再是为生成先进的数据特定模型进行遗传学分析的重大限制.

关键词:

氨基酸替代模型中的氨基酸替代模型数据特定模型的模型.模型估计模型估计人类遗传学是一个学科.蛋白质进化是如何发生的

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