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	Identifying micro-inversions using high-throughput sequencing reads
	He, Feifei ; Li, Yang ; Tang, Yu-Hang ; Ma, Jian ; Zhu, Huaiqiu
	2016
关键词	Micro-inversion Next-generation sequencing Structural variation HYPOTONIA-CYSTINURIA SYNDROME STRUCTURAL VARIATION HUMAN GENOME ENCODE PROJECT PAIRED-END ALIGNMENT DELETION MICROINVERSIONS ARCHITECTURE RESOLUTION
英文摘要	Background: The identification of inversions of DNA segments shorter than read length (e.g., 100 bp), defined as micro-inversions (MIs), remains challenging for next-generation sequencing reads. It is acknowledged that MIs are important genomic variation and may play roles in causing genetic disease. However, current alignment methods are generally insensitive to detect MIs. Here we develop a novel tool, MID (Micro-Inversion Detector), to identify MIs in human genomes using next-generation sequencing reads. Results: The algorithm of MID is designed based on a dynamic programming path-finding approach. What makes MID different from other variant detection tools is that MID can handle small MIs and multiple breakpoints within an unmapped read. Moreover, MID improves reliability in low coverage data by integrating multiple samples. Our evaluation demonstrated that MID outperforms Gustaf, which can currently detect inversions from 30 bp to 500 bp. Conclusions: To our knowledge, MID is the first method that can efficiently and reliably identify MIs from unmapped short next-generation sequencing reads. MID is reliable on low coverage data, which is suitable for large-scale projects such as the 1000 Genomes Project (1KGP). MID identified previously unknown MIs from the 1KGP that overlap with genes and regulatory elements in the human genome. We also identified MIs in cancer cell lines from Cancer Cell Line Encyclopedia (CCLE). Therefore our tool is expected to be useful to improve the study of MIs as a type of genetic variant in the human genome. The source code can be downloaded from: http://cqb.pku.edu.cn/ZhuLab/MID.; NCI NIH HHS [CA182360, R33 CA182360]; NHGRI NIH HHS [HG007352, R01 HG007352]; SCI(E); CPCI-S(ISTP); jianma@illinois.edu; hqzhu@pku.edu.cn; 17
语种	英语
出处	14th Asia Pacific Bioinformatics Conference (APBC) - Genomics
DOI标识	10.1186/s12864-015-2305-7
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/492565]
专题	生命科学学院 工学院
推荐引用方式 GB/T 7714	He, Feifei,Li, Yang,Tang, Yu-Hang,et al. Identifying micro-inversions using high-throughput sequencing reads. 2016-01-01.

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