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Conference Paper: Long single-molecule reads can resolve the complexity of the influenza virus composed of rare, closely related mutant variants

TitleLong single-molecule reads can resolve the complexity of the influenza virus composed of rare, closely related mutant variants
Authors
KeywordsRNA viral variants
SMRT reads
Single nucleotide Variation
Issue Date2016
PublisherSpringer.
Citation
20th International Conference on Research in Computational Molecular Biology (RECOMB 2016), Santa Monica, CA, 17-21 April 2016. In Singh, M (Ed.), Research in Computational Molecular Biology: 20th Annual Conference, RECOMB 2016, Santa Monica, CA, USA, April 17-21, 2016, Proceedings, p. 164-175. Cham, Switzerland: Springer, 2016 How to Cite?
Abstract© Springer International Publishing Switzerland 2016. As a result of a high rate of mutations and recombination events, an RNA-virus exists as a heterogeneous “swarm” of mutant variants. The long read length offered by single-molecule sequencing technologies allows each mutant variant to be sequenced in a single pass. However, high error rate limits the ability to reconstruct heterogeneous viral population composed of rare, related mutant variants. In this paper, we present 2SNV, a method able to tolerate the high error-rate of the singlemolecule protocol and reconstruct mutant variants. 2SNV uses linkage between single nucleotide variations to efficiently distinguish them from read errors. To benchmark the sensitivity of 2SNV, we performed a single-molecule sequencing experiment on a sample containing a titrated level of known viral mutant variants. Our method is able to accurately reconstruct clone with frequency of 0.2% and distinguish clones that differed in only two nucleotides distantly located on the genome. 2SNV outperforms existing methods for full-length viral mutant reconstruction. The open source implementation of 2SNV is freely available for download at http://alan.cs.gsu.edu/NGS/?q=content/2snv.
Persistent Identifierhttp://hdl.handle.net/10722/285762
ISBN
ISSN
2023 SCImago Journal Rankings: 0.606
Series/Report no.Lecture Notes in Computer Science book series ; 9649

 

DC FieldValueLanguage
dc.contributor.authorArtyomenko, Alexander-
dc.contributor.authorWu, Nicholas C.-
dc.contributor.authorMangul, Serghei-
dc.contributor.authorEskin, Eleazar-
dc.contributor.authorSun, Ren-
dc.contributor.authorZelikovsky, Alex-
dc.date.accessioned2020-08-18T04:56:34Z-
dc.date.available2020-08-18T04:56:34Z-
dc.date.issued2016-
dc.identifier.citation20th International Conference on Research in Computational Molecular Biology (RECOMB 2016), Santa Monica, CA, 17-21 April 2016. In Singh, M (Ed.), Research in Computational Molecular Biology: 20th Annual Conference, RECOMB 2016, Santa Monica, CA, USA, April 17-21, 2016, Proceedings, p. 164-175. Cham, Switzerland: Springer, 2016-
dc.identifier.isbn9783319319568-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/285762-
dc.description.abstract© Springer International Publishing Switzerland 2016. As a result of a high rate of mutations and recombination events, an RNA-virus exists as a heterogeneous “swarm” of mutant variants. The long read length offered by single-molecule sequencing technologies allows each mutant variant to be sequenced in a single pass. However, high error rate limits the ability to reconstruct heterogeneous viral population composed of rare, related mutant variants. In this paper, we present 2SNV, a method able to tolerate the high error-rate of the singlemolecule protocol and reconstruct mutant variants. 2SNV uses linkage between single nucleotide variations to efficiently distinguish them from read errors. To benchmark the sensitivity of 2SNV, we performed a single-molecule sequencing experiment on a sample containing a titrated level of known viral mutant variants. Our method is able to accurately reconstruct clone with frequency of 0.2% and distinguish clones that differed in only two nucleotides distantly located on the genome. 2SNV outperforms existing methods for full-length viral mutant reconstruction. The open source implementation of 2SNV is freely available for download at http://alan.cs.gsu.edu/NGS/?q=content/2snv.-
dc.languageeng-
dc.publisherSpringer.-
dc.relation.ispartofResearch in Computational Molecular Biology: 20th Annual Conference, RECOMB 2016, Santa Monica, CA, USA, April 17-21, 2016, Proceedings-
dc.relation.ispartofseriesLecture Notes in Computer Science book series ; 9649-
dc.subjectRNA viral variants-
dc.subjectSMRT reads-
dc.subjectSingle nucleotide Variation-
dc.titleLong single-molecule reads can resolve the complexity of the influenza virus composed of rare, closely related mutant variants-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-319-31957-5_12-
dc.identifier.scopuseid_2-s2.0-84964008517-
dc.identifier.spage164-
dc.identifier.epage175-
dc.identifier.eissn1611-3349-
dc.publisher.placeCham, Switzerland-
dc.identifier.issnl0302-9743-

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