小柯机器人

嵌合变体调用策略的全面基准和指南
2023-10-14 20:49

韩国延世大学医学院Sangwoo Kim团队近期取得重要的工作进展。他们研究开发了嵌合变体调用策略的全面基准和指南。相关研究成果2023年10月12日在线发表于《自然—方法学》杂志上。

据介绍,测序和分析技术的快速进步使得研究人员能够准确检测各种形式的基因组变异,如杂合、纯合和嵌合突。然而,由于在评估中面临技术和概念上的困难嵌合变体调用的最佳实践仍然杂乱无章。

研究人员提出了11种可行的嵌合变体检测方法的基准,该方法基于系统设计的模拟嵌合样本的全外显子组水平参考标准,得到354258个对照阳性嵌合单核苷酸变体和插入缺失突变以及33111725个对照阴性的支持。研究人员不仅确定了嵌合变体检测的最佳实践方法,还确定了当前方法的条件相关优势和劣势。

此外,特征级评估及其在多个算法中的组合使用为嵌合变体检测的即时到长期改进指明了方向。

总之,这一研究结果将指导研究人员选择合适的调用算法,并为开发人员提出未来的策略。

附:英文原文

Title: Comprehensive benchmarking and guidelines of mosaic variant calling strategies

Author: Ha, Yoo-Jin, Kang, Seungseok, Kim, Jisoo, Kim, Junhan, Jo, Se-Young, Kim, Sangwoo

Issue&Volume: 2023-10-12

Abstract: Rapid advances in sequencing and analysis technologies have enabled the accurate detection of diverse forms of genomic variants represented as heterozygous, homozygous and mosaic mutations. However, the best practices for mosaic variant calling remain disorganized owing to the technical and conceptual difficulties faced in evaluation. Here we present our benchmark of 11 feasible mosaic variant detection approaches based on a systematically designed whole-exome-level reference standard that mimics mosaic samples, supported by 354,258 control positive mosaic single-nucleotide variants and insertion-deletion mutations and 33,111,725 control negatives. We identified not only the best practice for mosaic variant detection but also the condition-dependent strengths and weaknesses of the current methods. Furthermore, feature-level evaluation and their combinatorial usage across multiple algorithms direct the way for immediate to prolonged improvements in mosaic variant detection. Our results will guide researchers in selecting suitable calling algorithms and suggest future strategies for developers.

DOI: 10.1038/s41592-023-02043-2

Source: https://www.nature.com/articles/s41592-023-02043-2

Nature Methods:《自然—方法学》,创刊于2004年。隶属于施普林格·自然出版集团,最新IF:47.99
官方网址:https://www.nature.com/nmeth/
投稿链接:https://mts-nmeth.nature.com/cgi-bin/main.plex


本期文章:《自然—方法学》:Online/在线发表

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