An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments

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cg.creator.identifierJorge Duitama: 0000-0002-9105-6266en_US
cg.creator.identifierJoe Tohme: 0000-0003-2765-7101en_US
cg.identifier.doihttps://doi.org/10.1093/nar/gkt1381en_US
cg.isijournalISI Journalen_US
cg.issn0305-1048en_US
cg.issue6en_US
cg.journalNucleic Acids Researchen_US
cg.subject.ciatPLANT BREEDINGen_US
cg.subject.ciatRICEen_US
cg.subject.ciatGENETIC RESOURCESen_US
cg.volume42en_US
dc.contributor.authorDuitama, Jorgeen_US
dc.contributor.authorQuintero, Juan Camiloen_US
dc.contributor.authorCruz, Daniel Felipeen_US
dc.contributor.authorQuintero, Constanzaen_US
dc.contributor.authorHubmann, Georgen_US
dc.contributor.authorFoulquié Moreno, Maria R.en_US
dc.contributor.authorVerstrepen, Kevin J.en_US
dc.contributor.authorTrevelein, Johan Men_US
dc.contributor.authorTohme, Joseph M.en_US
dc.date.accessioned2014-08-06T06:55:02Zen_US
dc.date.available2014-08-06T06:55:02Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/41897en_US
dc.titleAn integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experimentsen_US
dcterms.abstractRecent advances in high-throughput sequencing (HTS) technologies and computing capacity have produced unprecedented amounts of genomic data that have unraveled the genetics of phenotypic variability in several species. However, operating and integrating current software tools for data analysis still require important investments in highly skilled personnel. Developing accurate, efficient and user-friendly software packages for HTS data analysis will lead to a more rapid discovery of genomic elements relevant to medical, agricultural and industrial applications. We therefore developed Next-Generation Sequencing Eclipse Plug-in (NGSEP), a new software tool for integrated, efficient and user-friendly detection of single nucleotide variants (SNVs), indels and copy number variants (CNVs). NGSEP includes modules for read alignment, sorting, merging, functional annotation of variants, filtering and quality statistics. Analysis of sequencing experiments in yeast, rice and human samples shows that NGSEP has superior accuracy and efficiency, compared with currently available packages for variants detection. We also show that only a comprehensive and accurate identification of repeat regions and CNVs allows researchers to properly separate SNVs from differences between copies of repeat elements. We expect that NGSEP will become a strong support tool to empower the analysis of sequencing data in a wide range of research projects on different species.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.audienceScientistsen_US
dcterms.available2014-01-11en_US
dcterms.bibliographicCitationDuitama J, Quintero JC, Cruz DF, Quintero C, Hubmann G, Foulquié-Moreno MR, Verstrepen KJ, Thevelein JM, and Tohme J. 2014. An integrated framework for discovery and genotyping of genomic variants from high-throughput sequencing experiments. Nucleic Acids Research. 42 (6): e44en_US
dcterms.extentpp. e44-e44en_US
dcterms.issued2014-04-01en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-3.0en_US
dcterms.publisherOxford University Pressen_US
dcterms.subjectriceen_US
dcterms.subjectarrozen_US
dcterms.subjectgenotypesen_US
dcterms.subjectgenotiposen_US
dcterms.typeJournal Articleen_US

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