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dc.contributor.authorSoylev, Arda
dc.contributor.authorLe, Thong Minh
dc.contributor.authorAmini, Hajar
dc.contributor.authorAlkan, Can
dc.contributor.authorHormozdiari, Fereydoun
dc.date.accessioned2021-06-07T07:30:04Z
dc.date.available2021-06-07T07:30:04Z
dc.date.issued2019
dc.identifier.issn1367-4803
dc.identifier.urihttp://dx.doi.org/10.1093/bioinformatics/btz237
dc.identifier.urihttp://hdl.handle.net/11655/24596
dc.description.abstractMotivation: Several algorithms have been developed that use high-throughput sequencing technology to characterize structural variations (SVs). Most of the existing approaches focus on detecting relatively simple types of SVs such as insertions, deletions and short inversions. In fact, complex SVs are of crucial importance and several have been associated with genomic disorders. To better understand the contribution of complex SVs to human disease, we need new algorithms to accurately discover and genotype such variants. Additionally, due to similar sequencing signatures, inverted duplications or gene conversion events that include inverted segmental duplications are often characterized as simple inversions, likewise, duplications and gene conversions in direct orientation may be called as simple deletions. Therefore, there is still a need for accurate algorithms to fully characterize complex SVs and thus improve calling accuracy of more simple variants. Results:We developed novel algorithms to accurately characterize tandem, direct and inverted interspersed segmental duplications using short read whole genome sequencing datasets. We integrated these methods to our TARDIS tool, which is now capable of detecting various types of SVs using multiple sequence signatures such as read pair, read depth and split read. We evaluated the prediction performance of our algorithms through several experiments using both simulated and real datasets. In the simulation experiments, using a 30x coverage TARDIS achieved 96% sensitivity with only 4% false discovery rate. For experiments that involve real data, we used two haploid genomes (CHM1 and CHM13) and one human genome (NA12878) from the Illumina Platinum Genomes set. Comparison of our results with orthogonal PacBio call sets from the same genomes revealed higher accuracy for TARDIS than state-of-the-art methods. Furthermore, we showed a surprisingly low false discovery rate of our approach for discovery of tandem, direct and inverted interspersed segmental duplications prediction on CHM1 (<5% for the top 50 predictions).
dc.language.isoen
dc.relation.isversionof10.1093/bioinformatics/btz237
dc.rightsAttribution 4.0 United States
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleDiscovery Of Tandem And Interspersed Segmental Duplications Using High-Throughput Sequencing
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.relation.journalBioinformatics
dc.contributor.departmentBilgisayar Mühendisliği
dc.identifier.volume35
dc.identifier.issue20
dc.description.indexWoS


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Attribution 4.0 United States
Aksi belirtilmediği sürece bu öğenin lisansı: Attribution 4.0 United States