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散发性疾病队列中种系变异检测工具的性能比较

Performance comparison of germline variant calling tools in sporadic disease cohorts.

作者信息

Song Qiaofeng, Zhai Jinglan, Chen Changshui, Li Haibo, Cao Aihua, Yuan Bo, An Yu

机构信息

Human Phenome Institute, MOE Key Laboratory of Contemporary Anthropology, Zhangjiang Fudan International Innovation Center, Fudan University, 825 Zhangheng Road, Shanghai, 201203, China.

Ningbo Key Laboratory for the Prevention and Treatment of Embryogenic Diseases, The Central Laboratory of Birth Defects Prevention and Control, The Affiliated Women and Children's Hospital of Ningbo University, Ningbo, 315012, China.

出版信息

Mol Genet Genomics. 2025 Sep 6;300(1):90. doi: 10.1007/s00438-025-02292-0.

Abstract

Accurate variant calling is essential for next-generation sequencing (NGS)-based diagnosis of rare diseases, yet most benchmarking studies have focused on standard cell lines or trio-based samples, with limited relevance to sporadic cases. Here, we systematically compared the performance of DeepVariant and GATK HaplotypeCaller in two Chinese cohorts of patients with sporadic epilepsy (EP) and autism spectrum disorder (ASD). DeepVariant exhibited higher precision and sensitivity in detecting single nucleotide variants (SNVs), while GATK showed a distinct advantage in identifying rare variants, which are often key to understanding the genetic basis of rare diseases. Comparative analyses based on disease-related gene panels further highlighted differences in the identification of potentially deleterious variants. These findings reveal important trade-offs between variant callers and emphasize the need to tailor variant-calling strategies to specific research and clinical contexts. Our study provides practical vision for optimizing germline variant detection pipelines in sporadic neurodevelopmental disorders, offering broader insights for precision medicine applications.

摘要

准确的变异检测对于基于下一代测序(NGS)的罕见病诊断至关重要,但大多数基准研究都集中在标准细胞系或基于三联体的样本上,与散发病例的相关性有限。在此,我们系统地比较了DeepVariant和GATK HaplotypeCaller在两个中国散发性癫痫(EP)和自闭症谱系障碍(ASD)患者队列中的性能。DeepVariant在检测单核苷酸变异(SNV)方面表现出更高的精度和灵敏度,而GATK在识别罕见变异方面具有明显优势,这些罕见变异通常是理解罕见病遗传基础的关键。基于疾病相关基因panel的比较分析进一步突出了潜在有害变异识别方面的差异。这些发现揭示了变异检测工具之间重要的权衡,并强调需要根据特定的研究和临床背景调整变异检测策略。我们的研究为优化散发性神经发育障碍中的种系变异检测流程提供了实用的见解,为精准医学应用提供了更广泛的思路。

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