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Developing a nanopore sequencing data processing pipeline for structure variation identification
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Lin, Timothy. Developing a nanopore sequencing data processing pipeline for structure variation identification. Retrieved from https://doi.org/doi:10.7282/t3-f6me-bg19

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TitleDeveloping a nanopore sequencing data processing pipeline for structure variation identification
NameLin, Timothy (author); Xing, Jinchuan (chair); Shah, Premal (internal member); Ellison, Christopher (internal member); Rutgers University; School of Graduate Studies
Date Created2019
Other Date2019-10 (degree)
SubjectMicrobiology and Molecular Genetics, Nanopores, Nucleotide sequence
Extent1 online resource (vi, 41 pages) : illustrations
DescriptionMany genomic sequencing technologies have been developed since the Human Genome Project. These next-generation sequencing (NGS) technologies from various companies reshaped the genomics field and have improved rapidly. However, NGS has limitations for certain applications due to its short read length. The third generation of sequencing technology uses single molecule real-time sequencer that can generate long reads. Recently Oxford Nanopore entered the market with the release of its MinION sequencer. Oxford Nanopore's unique third generation sequencing technology allows for much longer read length than NGS technologies, potentially addressing some of the limitations of NGS. Due to the novelty of nanopore sequencing technology, the available tools for aligning long read data and detecting structural variants have not been thoroughly evaluated. Here we evaluate the performance of several alignment and structural variation detection tools on long read MinION data.
NoteM.S.
NoteIncludes bibliographical references
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/t3-f6me-bg19
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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