Large structural variation discovery using long reads with several degrees of error

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buir.advisorAlkan, Can
dc.contributor.authorEbren, Ezgi
dc.date.accessioned2021-02-03T13:05:41Z
dc.date.available2021-02-03T13:05:41Z
dc.date.copyright2020-12
dc.date.issued2020-12
dc.date.submitted2021-02-01
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (M.S.): Bilkent University, Department of Computer Engineering, İhsan Doğramacı Bilkent University, 2020.en_US
dc.descriptionIncludes bibliographical references (leaves 36-45).en_US
dc.description.abstractGenomic structural variations (SVs) are briefly defined as large-scale alterations of DNA content, copy, and organization. Although significant progress has been made since the introduction of high throughput sequencing (HTS) in character-izing SVs, accurate detection of complex SVs and balanced rearrangements still remains elusive due to the sequence complexity at the breakpoints. Until very recently, the difficulty of read mapping in such regions when the reads were short and the high error rates of long read platforms kept the problem challenging. However, with the introduction of the Pacific Biosciences’ High Fidelity (HiFi) sequencing methodology, powerful SV detection and breakpoint resolution be-came possible as a result of its capability to produce highly accurate (> 99%) long reads (10 − 20 kbps). Here, we introduce DALEK, a novel algorithm that aims to use long-read tech-nologies to discover large structural variations with high break-point resolution. DALEK uses split read and read depth signatures from long read data to dis-cover large (≥ 10 kbps) deletions, inversions and segmental duplications. We also develop methods to detect large SVs in existing high-error Oxford Nanopore Technologies data.en_US
dc.description.degreeM.S.en_US
dc.description.provenanceSubmitted by Betül Özen (ozen@bilkent.edu.tr) on 2021-02-03T13:05:41Z No. of bitstreams: 1 10377737.pdf: 1133300 bytes, checksum: 6abd15b670556584d5be4c4343e70784 (MD5)en
dc.description.provenanceMade available in DSpace on 2021-02-03T13:05:41Z (GMT). No. of bitstreams: 1 10377737.pdf: 1133300 bytes, checksum: 6abd15b670556584d5be4c4343e70784 (MD5) Previous issue date: 2021-01en
dc.description.statementofresponsibilityby Ezgi Ebrenen_US
dc.embargo.release2021-07-28
dc.format.extentxi, 47 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB155544
dc.identifier.urihttp://hdl.handle.net/11693/54977
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectStructural variationen_US
dc.subjectDeletionen_US
dc.subjectInversionen_US
dc.subjectSegmental duplicationen_US
dc.subjectHiFi readsen_US
dc.subjectLong readsen_US
dc.titleLarge structural variation discovery using long reads with several degrees of erroren_US
dc.title.alternativeFarklı hata oranlarına sahip uzun okumalar ile büyük yapısal varyasyon tespitien_US
dc.typeThesisen_US

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