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dc.contributor.authorCheng, Ji-Hongen_US
dc.contributor.authorLiu, Wen-Chunen_US
dc.contributor.authorChang, Ting-Tsungen_US
dc.contributor.authorHsieh, Sun-Yuanen_US
dc.contributor.authorTseng, Vincent S.en_US
dc.date.accessioned2018-08-21T05:52:49Z-
dc.date.available2018-08-21T05:52:49Z-
dc.date.issued2017-10-01en_US
dc.identifier.issn1046-2023en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.ymeth.2017.08.005en_US
dc.identifier.urihttp://hdl.handle.net/11536/143972-
dc.description.abstractMany studies have suggested that deletions of Hepatitis B Viral (HBV) are associated with the development of progressive liver diseases, even ultimately resulting in hepatocellular carcinoma (HCC). Among the methods for detecting deletions from next-generation sequencing (NGS) data, few methods considered the characteristics of virus, such as high evolution rates and high divergence among the different HBV genomes. Sequencing high divergence HBV genome sequences using the NGS technology outputs millions of reads. Thus, detecting exact breakpoints of deletions from these big and complex data incurs very high computational cost. We proposed a novel analytical method named VirDelect (Virus Deletion Detect), which uses split read alignment base to detect exact breakpoint and diversity variable to consider high divergence in single-end reads data, such that the computational cost can be reduced without losing accuracy. We use four simulated reads datasets and two real pair-end reads datasets of HBV genome sequence to verify VirDelect accuracy by score functions. The experimental results show that VirDelect outperforms the state-of-the-art method Pindel in terms of accuracy score for all simulated datasets and VirDelect had only two base errors even in real datasets. VirDelect is also shown to deliver high accuracy in analyzing the single-end read data as well as pair-end data. VirDelect can serve as an effective and efficient bioinformatics tool for physiologists with high accuracy and efficient performance and applicable to further analysis with characteristics similar to HBV on genome length and high divergence. The software program of VirDelect can be downloaded at https://sourceforge.net/projects/virdelect/. (C) 2017 Published by Elsevier Inc.en_US
dc.language.isoen_USen_US
dc.subjectData miningen_US
dc.subjectMachine learningen_US
dc.subjectBreakpointen_US
dc.subjectDeletion detectionen_US
dc.subjectHepatitis B virusen_US
dc.subjectNext-generation sequencingen_US
dc.titleDetecting exact breakpoints of deletions with diversity in hepatitis B viral genomic DNA from next-generation sequencing dataen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.ymeth.2017.08.005en_US
dc.identifier.journalMETHODSen_US
dc.citation.volume129en_US
dc.citation.spage24en_US
dc.citation.epage32en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000413613500005en_US
Appears in Collections:Articles