The present and future of de novo whole-genome assembly
DC Field | Value | Language |
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dc.contributor.author | Sohn, Jang-il | - |
dc.contributor.author | Nam, Jin-Wu | - |
dc.date.accessioned | 2021-08-02T13:54:06Z | - |
dc.date.available | 2021-08-02T13:54:06Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2018-01 | - |
dc.identifier.issn | 1467-5463 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/17883 | - |
dc.description.abstract | As the advent of next-generation sequencing (NGS) technology, various de novo assembly algorithms based on the de Bruijn graph have been developed to construct chromosome-level sequences. However, numerous technical or computational challenges in de novo assembly still remain, although many bright ideas and heuristics have been suggested to tackle the challenges in both experimental and computational settings. In this review, we categorize de novo assemblers on the basis of the type of de Bruijn graphs (Hamiltonian and Eulerian) and discuss the challenges of de novo assembly for short NGS reads regarding computational complexity and assembly ambiguity. Then, we discuss how the limitations of the short reads can be overcome by using a single-molecule sequencing platform that generates long reads of up to several kilobases. In fact, the long read assembly has caused a paradigm shift in whole-genome assembly in terms of algorithms and supporting steps. We also summarize (i) hybrid assemblies using both short and long reads and (ii) overlap-based assemblies for long reads and discuss their challenges and future prospects. This review provides guidelines to determine the optimal approach for a given input data type, computational budget or genome. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | OXFORD UNIV PRESS | - |
dc.title | The present and future of de novo whole-genome assembly | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Nam, Jin-Wu | - |
dc.identifier.doi | 10.1093/bib/bbw096 | - |
dc.identifier.scopusid | 2-s2.0-85041212257 | - |
dc.identifier.wosid | 000423311000003 | - |
dc.identifier.bibliographicCitation | BRIEFINGS IN BIOINFORMATICS, v.19, no.1, pp.23 - 40 | - |
dc.relation.isPartOf | BRIEFINGS IN BIOINFORMATICS | - |
dc.citation.title | BRIEFINGS IN BIOINFORMATICS | - |
dc.citation.volume | 19 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 23 | - |
dc.citation.endPage | 40 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Biochemical Research Methods | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.subject.keywordPlus | HYBRID ERROR-CORRECTION | - |
dc.subject.keywordPlus | GENETIC-VARIATION | - |
dc.subject.keywordPlus | SEQUENCING DATA | - |
dc.subject.keywordPlus | BRUIJN GRAPHS | - |
dc.subject.keywordPlus | SINGLE-CELL | - |
dc.subject.keywordPlus | DNA | - |
dc.subject.keywordPlus | LONG | - |
dc.subject.keywordPlus | EFFICIENT | - |
dc.subject.keywordPlus | QUALITY | - |
dc.subject.keywordPlus | ACCURATE | - |
dc.subject.keywordAuthor | de novo assembly algorithms | - |
dc.subject.keywordAuthor | de Bruijn graph | - |
dc.subject.keywordAuthor | next-generation sequencing | - |
dc.subject.keywordAuthor | single-molecule sequencing | - |
dc.identifier.url | https://academic.oup.com/bib/article/19/1/23/2339783 | - |
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