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一种用于准确的变异调用低复制重复的多部位方法,使用全基因组测序

Timofey Prodanov^1,2,3, Vikas Bansal⁴

¹Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA 92093, United States.

Bioinformatics (Oxford, England)

|June 30, 2023

概括

帕拉斯科普VC改善了低复制重复 (LCR) 的变异调用,这对于了解疾病风险至关重要. 这种新方法提供了更高的准确性和回忆这些复杂的基因组区域内的遗传变异.

科学领域:

基因组学就是基因组学.
生物信息学是一种生物信息学.
人类遗传学人类遗传学

背景情况:

低复制重复 (LCR) 或细分重复,占人类基因组的5%以上.
现有的短读变量调用工具由于映射挑战和副本数量变化而在LCR中难以准确.
在LCRs中的变异与150多种人类疾病有关,这凸显了需要改进检测方法的需要.

研究的目的:

开发一种新的短读变异调用方法,专门设计用于在LCR中准确检测变异.
解决当前工具在处理重复DNA段的复杂性方面的局限性.

主要方法:

介绍了ParascopyVC,这是一种执行联合变体调用所有重复副本的方法.
使用独立于映射质量的读取值,并将不同重复副本的映射读取值汇总为多倍变异调用.
采用类似的序列变异来区分重复拷贝,并估计每个拷贝的基因型.

主要成果:

与DeepVariant和GATK等最先进的呼叫器相比,ParascopyVC在模拟数据上表现出更高的精度和回忆.
对HG002基因组的基准测试显示,ParascopyVC在LCR区域实现了高精度 (0.991) 和回忆 (0.909),表现优于FreeBayes,GATK和DeepVariant.
在7个人类基因组中,ParascopyVC始终比竞争方法获得更高的准确性 (平均F1 = 0.947).

结论:

在低拷贝重复区域,ParascopyVC显著提高了变体调用准确性.
该方法为在复杂的基因组结构中识别与疾病相关的变异提供了更可靠的方法.
帕拉斯科普VC是免费可用的,促进其在基因组研究和临床应用中的采用.

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