Toolkit for automated and rapid discovery of structural variants

dc.citation.epage7en_US
dc.citation.spage3en_US
dc.citation.volumeNumber129en_US
dc.contributor.authorSoylev, A.en_US
dc.contributor.authorKockan, C.en_US
dc.contributor.authorHormozdiari, F.en_US
dc.contributor.authorAlkan C.en_US
dc.date.accessioned2018-04-12T11:09:51Z
dc.date.available2018-04-12T11:09:51Z
dc.date.issued2017en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractStructural variations (SV) are broadly defined as genomic alterations that affect >50 bp of DNA, which are shown to have significant effect on evolution and disease. The advent of high throughput sequencing (HTS) technologies and the ability to perform whole genome sequencing (WGS), makes it feasible to study these variants in depth. However, discovery of all forms of SV using WGS has proven to be challenging as the short reads produced by the predominant HTS platforms (<200 bp for current technologies) and the fact that most genomes include large amounts of repeats make it very difficult to unambiguously map and accurately characterize such variants. Furthermore, existing tools for SV discovery are primarily developed for only a few of the SV types, which may have conflicting sequence signatures (i.e. read pairs, read depth, split reads) with other, untargeted SV classes. Here we are introduce a new framework, TARDIS, which combines multiple read signatures into a single package to characterize most SV types simultaneously, while preventing such conflicts. TARDIS also has a modular structure that makes it easy to extend for the discovery of additional forms of SV. © 2017 Elsevier Inc.en_US
dc.identifier.doi10.1016/j.ymeth.2017.05.030en_US
dc.identifier.issn1046-2023en_US
dc.identifier.urihttp://hdl.handle.net/11693/37315en_US
dc.language.isoEnglishen_US
dc.publisherAcademic Pressen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.ymeth.2017.05.030en_US
dc.source.titleMethodsen_US
dc.subjectCombinatorial algorithmsen_US
dc.subjectHigh throughput sequencingen_US
dc.subjectStructural variationen_US
dc.titleToolkit for automated and rapid discovery of structural variantsen_US
dc.typeArticleen_US

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