结构变体集成和可视化:一个全面的R包,用于集成来自多个调用者的体细胞结构变体和可视化

Tumor discovery Pub Date : 2023-07-20 DOI:10.36922/td.0894
Lei Yu, Le Zhang, Lili Wang, Zhenyu Jia
{"title":"结构变体集成和可视化:一个全面的R包,用于集成来自多个调用者的体细胞结构变体和可视化","authors":"Lei Yu, Le Zhang, Lili Wang, Zhenyu Jia","doi":"10.36922/td.0894","DOIUrl":null,"url":null,"abstract":"Whole genome sequencing (WGS) emerges as a powerful tool for detecting structural variations (SVs) in genomes. However, different SV callers can produce variable results due to the distinct rationale and sensitivity of pipelines, highlighting the need for effective tools to compare and merge results from multiple callers. Here, we developed an R package, structural variants integration and visualization, to facilitate the integration, classification, and visualization of SV results from multiple callers, allowing for accurate identification of the most reliable SVs. Our package relies on a complex translocation projection and clustering method, enabling the projection of each translation to a point in a Cartesian coordinate system and visualization of SVs at both whole-genome and individual chromosome levels. Thus, our approach provides a valuable framework for analyzing SVs from WGS data, improving the accuracy and efficiency of SV detection, and enhancing the potential of WGS for clinical and research applications.","PeriodicalId":94260,"journal":{"name":"Tumor discovery","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Structural variants integration and visualization: A comprehensive R package for integration of somatic structural variations from multiple callers and visualization\",\"authors\":\"Lei Yu, Le Zhang, Lili Wang, Zhenyu Jia\",\"doi\":\"10.36922/td.0894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Whole genome sequencing (WGS) emerges as a powerful tool for detecting structural variations (SVs) in genomes. However, different SV callers can produce variable results due to the distinct rationale and sensitivity of pipelines, highlighting the need for effective tools to compare and merge results from multiple callers. Here, we developed an R package, structural variants integration and visualization, to facilitate the integration, classification, and visualization of SV results from multiple callers, allowing for accurate identification of the most reliable SVs. Our package relies on a complex translocation projection and clustering method, enabling the projection of each translation to a point in a Cartesian coordinate system and visualization of SVs at both whole-genome and individual chromosome levels. Thus, our approach provides a valuable framework for analyzing SVs from WGS data, improving the accuracy and efficiency of SV detection, and enhancing the potential of WGS for clinical and research applications.\",\"PeriodicalId\":94260,\"journal\":{\"name\":\"Tumor discovery\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tumor discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36922/td.0894\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tumor discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36922/td.0894","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

全基因组测序(WGS)是检测基因组结构变异(SVs)的有力工具。然而,由于管道的原理和敏感性不同,不同的SV调用程序可能产生不同的结果,这就突出了对有效工具的需求,以比较和合并来自多个调用程序的结果。在这里,我们开发了一个R包,结构变量集成和可视化,以促进来自多个调用者的SV结果的集成,分类和可视化,从而允许准确识别最可靠的SV。我们的软件包依赖于复杂的易位投影和聚类方法,能够将每个翻译投影到笛卡尔坐标系中的一个点,并在全基因组和单个染色体水平上可视化sv。因此,我们的方法为从WGS数据中分析SV,提高SV检测的准确性和效率,增强WGS在临床和研究中的应用潜力提供了一个有价值的框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Structural variants integration and visualization: A comprehensive R package for integration of somatic structural variations from multiple callers and visualization
Whole genome sequencing (WGS) emerges as a powerful tool for detecting structural variations (SVs) in genomes. However, different SV callers can produce variable results due to the distinct rationale and sensitivity of pipelines, highlighting the need for effective tools to compare and merge results from multiple callers. Here, we developed an R package, structural variants integration and visualization, to facilitate the integration, classification, and visualization of SV results from multiple callers, allowing for accurate identification of the most reliable SVs. Our package relies on a complex translocation projection and clustering method, enabling the projection of each translation to a point in a Cartesian coordinate system and visualization of SVs at both whole-genome and individual chromosome levels. Thus, our approach provides a valuable framework for analyzing SVs from WGS data, improving the accuracy and efficiency of SV detection, and enhancing the potential of WGS for clinical and research applications.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Matrix metalloproteinase-1 as a potential biomarker for early gastric cancer detection and its effect on gastric cancer cell proliferation and migration Bioinformatics analysis of missense mutations in CXCR1 implicates altered protein stability and function Profiling energy metabolism in normal bladder tissue and non-muscle-invasive bladder cancer cases of different histological grades Odontogenic myxofibroma arising in the mandibular angle of a child with long-term follow-up: A case report Artificial intelligence enabled spatially resolved transcriptomics reveal spatial tissue organization of multiple tumors
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1