Detecting Structural Variations with Illumina, PacBio and Optical Maps Data by Computational Approaches

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dc.contributor.advisorNakhleh, Luayen_US
dc.contributor.committeeMemberChen, Kenen_US
dc.creatorFan, Xianen_US
dc.date.accessioned2019-05-17T14:58:00Zen_US
dc.date.available2019-05-17T14:58:00Zen_US
dc.date.created2018-05en_US
dc.date.issued2018-04-20en_US
dc.date.submittedMay 2018en_US
dc.date.updated2019-05-17T14:58:00Zen_US
dc.description.abstractDetecting structural variations (SV) is important in deciphering variations in human DNA and the cause of genetic disease such as cancer. Computational approaches to detect SVs are made possible by sequencing technologies. As different sequencing technologies render data with different characteristics, computational approaches are designed in a way that is specific to a certain technology. In this thesis I studied three technologies: Illumina, PacBio and Optical Maps. As Illumina and PacBio reads have complementary advantages and disadvantages of read length and error rate, I proposed a new approach, HySA, that combines Illumina and PacBio to detect SV. HySA was able to detect SVs that cannot be detected by the approaches for either only Illumina or only PacBio. However, due to the repetitiveness of the human DNA as well as the existence of complex SVs, it is still challenging for HySA to detect some SVs on the repetitive regions or complex SVs. To overcome that, I proposed a new approach to detect SVs by Optical Maps data, which is advantageous over Illumina and PacBio in read length, despite its lack of sequence and unique error profile. The SVs detected by Optical Maps alone complement those from Illumina and PacBio. In all, the two approaches I proposed help push towards a more complete characterization of SVs in human DNA.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationFan, Xian. "Detecting Structural Variations with Illumina, PacBio and Optical Maps Data by Computational Approaches." (2018) Diss., Rice University. <a href="https://hdl.handle.net/1911/105732">https://hdl.handle.net/1911/105732</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/105732en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectStructural Variationsen_US
dc.subjectDNA sequencingen_US
dc.subjectIlluminaen_US
dc.subjectPacBioen_US
dc.subjectCanceren_US
dc.subjectOptical Mapsen_US
dc.titleDetecting Structural Variations with Illumina, PacBio and Optical Maps Data by Computational Approachesen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentComputer Scienceen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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