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针对全基因组数据集设计的基因基因年龄估计器在整个外基因组数据集上应用时,只显示了性能中适度的降低

Alyssa Pivirotto¹, Noah Peles¹, Jody Hey¹

¹Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA USA.

bioRxiv : the preprint server for biology

|February 19, 2024

概括

使用全外体数据估计突变年龄是可行的,目前的工具. 相对表现最好,显示可用的等位基因年龄估计,尽管与全基因组数据相比,性能略有下降.

科学领域:

基因组学就是基因组学.
人口遗传学人口遗传学
生物信息学是一种生物信息学.

背景情况:

由于测序成本下降,个性化基因组学正在扩大.
发现罕见变异需要方法来了解它们的功能影响和疾病关联.
估计突变的年龄 (等位基因年龄) 对于表征变异至关重要.

研究的目的:

评估现有的基因基因年龄估计器 (Relate,GEVA,Runtc) 在全外体数据上的性能.
评估这些估计器在不同的人口模型 (中性,扩展,背景选择) 下的表现.

主要方法:

使用了模拟的全外因子测序数据.
测试了三个等位基因年龄估计器 (Relate,GEVA,Runtc).
在中性常数,人口扩张和背景选择模型下评估了表现.

主要成果:

所有测试的估计器都提供了可利用的基因组年龄估计,这些估计来自整个外体的数据.
关联表现最好,具有高的皮尔森相关系数 (分别为中性和扩展模型的0.83和0.73).
与全基因组数据相比,全基因组数据导致相关性略有下降 (12-20%),Relate显示的下降幅度最小.

结论:

目前的等位基因年龄估计方法对于整个外体数据是可行的,其中Relate是表现最好的.
虽然Relate提供了计算效率,但其可扩展性仅限于数千个样本.
需要进一步开发以提高对大规模基因组数据集的等位基因年龄估计的性能和可扩展性.

关键词:

在WES WES中,您可以使用代基因年龄代基因年龄异构体是什么? 异构体是什么?个性化的基因组学整体外基因组测序的测序

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