Please use this identifier to cite or link to this item: https://doi.org/10.1089/cmb.2011.0170
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dc.titleOpera: Reconstructing optimal genomic scaffolds with high-throughput paired-end sequences
dc.contributor.authorGao, S.
dc.contributor.authorSung, W.-K.
dc.contributor.authorNagarajan, N.
dc.date.accessioned2013-07-04T07:31:42Z
dc.date.available2013-07-04T07:31:42Z
dc.date.issued2011
dc.identifier.citationGao, S., Sung, W.-K., Nagarajan, N. (2011). Opera: Reconstructing optimal genomic scaffolds with high-throughput paired-end sequences. Journal of Computational Biology 18 (11) : 1681-1691. ScholarBank@NUS Repository. https://doi.org/10.1089/cmb.2011.0170
dc.identifier.issn10665277
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39000
dc.description.abstractScaffolding, the problem of ordering and orienting contigs, typically using paired-end reads, is a crucial step in the assembly of high-quality draft genomes. Even as sequencing technologies and mate-pair protocols have improved significantly, scaffolding programs still rely on heuristics, with no guarantees on the quality of the solution. In this work, we explored the feasibility of an exact solution for scaffolding and present a first tractable solution for this problem (Opera). We also describe a graph contraction procedure that allows the solution to scale to large scaffolding problems and demonstrate this by scaffolding several large real and synthetic datasets. In comparisons with existing scaffolders, Opera simultaneously produced longer and more accurate scaffolds demonstrating the utility of an exact approach. Opera also incorporates an exact quadratic programming formulation to precisely compute gap sizes (Availability: http://sourceforge.net/projects/operasf/). © Copyright 2011, Mary Ann Liebert, Inc.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1089/cmb.2011.0170
dc.sourceScopus
dc.subjectgenome assembly
dc.subjectparametric complexity
dc.subjectquadratic programming
dc.subjectscaffolding
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1089/cmb.2011.0170
dc.description.sourcetitleJournal of Computational Biology
dc.description.volume18
dc.description.issue11
dc.description.page1681-1691
dc.description.codenJCOBE
dc.identifier.isiut000296891100023
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