{"title":"研究基因组结构变异的计算工具。","authors":"Xingyu Chen, Siyu Wei, Chen Sun, Zelin Yi, Zihan Wang, Yingyi Wu, Jing Xu, Junxian Tao, Haiyan Chen, Mingming Zhang, Yongshuai Jiang, Hongchao Lv, Chen Huang","doi":"10.1089/omi.2024.0200","DOIUrl":null,"url":null,"abstract":"<p><p>Structural variation (SV) typically refers to alterations in DNA fragments at least 50 base pairs long in the human genome. It can alter thousands of DNA nucleotides and thus significantly influence human health, disease, and clinical phenotypes. There is a shared and growing recognition that the emergence of effective computational tools and high-throughput technologies such as short-read sequencing and long-read sequencing offers novel insight into SV and, by extension, diseases affecting planetary health. However, numerous available SV tools exist with varying strengths and weaknesses. This is currently hampering the abilities of scholars to select the optimal tools to study SVs. Here, we reviewed 175 tools developed in the past two decades for SV detection, annotation, visualization, and downstream analysis of human genomics. In this expert review, we provide a comprehensive catalog of SV-related tools across different technology platforms and summarize their features, strengths, and limitations with an eye to accelerate systems science and planetary health innovations.</p>","PeriodicalId":19530,"journal":{"name":"Omics A Journal of Integrative Biology","volume":" ","pages":"36-48"},"PeriodicalIF":2.2000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational Tools for Studying Genome Structural Variation.\",\"authors\":\"Xingyu Chen, Siyu Wei, Chen Sun, Zelin Yi, Zihan Wang, Yingyi Wu, Jing Xu, Junxian Tao, Haiyan Chen, Mingming Zhang, Yongshuai Jiang, Hongchao Lv, Chen Huang\",\"doi\":\"10.1089/omi.2024.0200\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Structural variation (SV) typically refers to alterations in DNA fragments at least 50 base pairs long in the human genome. It can alter thousands of DNA nucleotides and thus significantly influence human health, disease, and clinical phenotypes. There is a shared and growing recognition that the emergence of effective computational tools and high-throughput technologies such as short-read sequencing and long-read sequencing offers novel insight into SV and, by extension, diseases affecting planetary health. However, numerous available SV tools exist with varying strengths and weaknesses. This is currently hampering the abilities of scholars to select the optimal tools to study SVs. Here, we reviewed 175 tools developed in the past two decades for SV detection, annotation, visualization, and downstream analysis of human genomics. In this expert review, we provide a comprehensive catalog of SV-related tools across different technology platforms and summarize their features, strengths, and limitations with an eye to accelerate systems science and planetary health innovations.</p>\",\"PeriodicalId\":19530,\"journal\":{\"name\":\"Omics A Journal of Integrative Biology\",\"volume\":\" \",\"pages\":\"36-48\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Omics A Journal of Integrative Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1089/omi.2024.0200\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Omics A Journal of Integrative Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1089/omi.2024.0200","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/5 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
结构变异(SV)通常是指人类基因组中至少 50 个碱基对长的 DNA 片段的改变。它可以改变数千个 DNA 核苷酸,从而对人类健康、疾病和临床表型产生重大影响。越来越多的人共同认识到,有效的计算工具和高通量技术(如短线程测序和长线程测序)的出现为了解 SV 以及影响地球健康的疾病提供了新的视角。然而,现有的许多 SV 工具优缺点各不相同。这阻碍了学者们选择最佳工具研究 SV 的能力。在此,我们回顾了过去二十年中开发的 175 种用于 SV 检测、注释、可视化和人类基因组学下游分析的工具。在这篇专家综述中,我们提供了不同技术平台上 SV 相关工具的综合目录,并总结了这些工具的特点、优势和局限性,以期加快系统科学和行星健康创新的步伐。
Computational Tools for Studying Genome Structural Variation.
Structural variation (SV) typically refers to alterations in DNA fragments at least 50 base pairs long in the human genome. It can alter thousands of DNA nucleotides and thus significantly influence human health, disease, and clinical phenotypes. There is a shared and growing recognition that the emergence of effective computational tools and high-throughput technologies such as short-read sequencing and long-read sequencing offers novel insight into SV and, by extension, diseases affecting planetary health. However, numerous available SV tools exist with varying strengths and weaknesses. This is currently hampering the abilities of scholars to select the optimal tools to study SVs. Here, we reviewed 175 tools developed in the past two decades for SV detection, annotation, visualization, and downstream analysis of human genomics. In this expert review, we provide a comprehensive catalog of SV-related tools across different technology platforms and summarize their features, strengths, and limitations with an eye to accelerate systems science and planetary health innovations.
期刊介绍:
OMICS: A Journal of Integrative Biology is the only peer-reviewed journal covering all trans-disciplinary OMICs-related areas, including data standards and sharing; applications for personalized medicine and public health practice; and social, legal, and ethics analysis. The Journal integrates global high-throughput and systems approaches to 21st century science from “cell to society” – seen from a post-genomics perspective.