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DoBSeqWF:一个用于在聚合测序数据中敏感检测个体遗传变异的框架

Mads Cort Nielsen^1,2, Christian Munch Hagen³, Ulrik Kristoffer Stoltze⁴

¹Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, KBH N, 2200, Denmark.

NAR genomics and bioinformatics

|February 18, 2026

概括

双批次测序 (DoBSeq) 提供了具有成本效益的罕见遗传疾病查. 一个新的工作流程,DoBSeqWF,有效地分析复杂的聚合测序数据,以准确检测罕见变种,从而实现更广泛的遗传查程序.

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.
遗传医学是一种遗传医学.

背景情况:

对罕见遗传疾病进行人口查可以改善早期诊断和治疗.
下一代测序的高成本阻碍了广泛实施.
双批次测序 (DoBSeq) 是使用聚合测序数据进行罕见变异检测的一种具有成本效益的方法.

研究的目的:

开发和验证专门的生物信息工作流程,用于分析复杂的DoBSeq数据.
从整基因组测序数据中实现高效,敏感和可复制的罕见变异检测.

主要方法:

开发DoBSeqWF,这是一个基于Nextflow的管道,用于处理DoBSeq数据,从对齐到变体赋值.
使用儿童癌症队列 (200人) 创建培训和验证数据集.
变种调用者的基准测试和机器学习过器的实施,以加强罕见变种检测.

主要成果:

在聚合的测序数据中,DoBSeqWF证明了精确且可扩展的罕见变异检测.
机器学习过器提高了罕见变种检测灵敏度.
工作流提供了一个强大的方法来分析复杂的DoBSeq数据.

结论:

使用DoBSeq.WF,DoBSeq.WF是一个有效的管道,用于检测罕见的变种.
这个工作流程支持扩大成本效益高的罕见疾病遗传查计划.

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