SVLR: Genome Structural Variant Detection Using Long-Read Sequencing Data

doi:10.1089/cmb.2021.0048

	SVLR: Genome Structural Variant Detection Using Long-Read Sequencing Data
	Gu, Wenyan 1; Zhou, Aizhong 1; Wang, Lusheng 2; Sun, Shiwei 3; Cui, Xuefeng 1; Zhu, Daming 1
	2021-05-10
发表期刊	JOURNAL OF COMPUTATIONAL BIOLOGY
ISSN	1066-5277
页码	15
摘要	Genome structural variants (SVs) have great impacts on human phenotype and diversity, and have been linked to numerous diseases. Long-read sequencing technologies arise to make it possible to find SVs of as long as 10,000 nucleotides. Thus, long read-based SV detection has been drawing attention of many recent research projects, and many tools have been developed for long reads to detect SVs recently. In this article, we present a new method, called SVLR, to detect SVs based on long-read sequencing data. Comparing with existing methods, SVLR can detect three new kinds of SVs: block replacements, block interchanges, and translocations. Although these new SVs are structurally more complicated, SVLR achieves accuracies that are comparable with those of the classic SVs. Moreover, for the classic SVs that can be detected by state-of-the-art methods (e.g., SVIM and Sniffles), our experiments demonstrate recall improvements of up to 38% without harming the precisions (i.e., >78%). We also point out three directions to further improve SV detection in the future. Source codes: https://github.com/GWYSDU/SVLR
关键词	genome structural variant genome structural variant detection long-read sequencing and single-molecule sequencing third-generation sequencing
DOI	10.1089/cmb.2021.0048
收录类别	SCI
语种	英语
资助项目	National Science Foundation of China[61732009] ; National Science Foundation of China[61761136017] ; National Science Foundation of China[62072283]
WOS研究方向	Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics
WOS类目	Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology ; Statistics & Probability
WOS记录号	WOS:000649049200001
出版者	MARY ANN LIEBERT, INC
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/17843
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Cui, Xuefeng; Zhu, Daming
作者单位	1.Shandong Univ, Sch Comp Sci & Technol, Qingdao 266237, Peoples R China 2.City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Gu, Wenyan,Zhou, Aizhong,Wang, Lusheng,et al. SVLR: Genome Structural Variant Detection Using Long-Read Sequencing Data[J]. JOURNAL OF COMPUTATIONAL BIOLOGY,2021:15.
APA	Gu, Wenyan,Zhou, Aizhong,Wang, Lusheng,Sun, Shiwei,Cui, Xuefeng,&Zhu, Daming.(2021).SVLR: Genome Structural Variant Detection Using Long-Read Sequencing Data.JOURNAL OF COMPUTATIONAL BIOLOGY,15.
MLA	Gu, Wenyan,et al."SVLR: Genome Structural Variant Detection Using Long-Read Sequencing Data".JOURNAL OF COMPUTATIONAL BIOLOGY (2021):15.