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Genome Assembly and Variant Detection Using Emerging Sequencing Technologies and Graph Based Methods

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서명/저자사항Genome Assembly and Variant Detection Using Emerging Sequencing Technologies and Graph Based Methods.
개인저자Ghurye, Jay.
단체저자명University of Maryland, College Park. Computer Science.
발행사항[S.l.]: University of Maryland, College Park., 2018.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2018.
형태사항182 p.
기본자료 저록Dissertations Abstracts International 81-02A.
Dissertation Abstract International
ISBN9781085582889
학위논문주기Thesis (Ph.D.)--University of Maryland, College Park, 2018.
일반주기 Source: Dissertations Abstracts International, Volume: 81-02, Section: A.
Advisor: Pop, Mihai.
이용제한사항This item is not available from ProQuest Dissertations & Theses.This item must not be sold to any third party vendors.
요약The increased availability of genomic data and the increased ease and lower costs of DNA sequencing have revolutionized biomedical research. One of the critical steps in most bioinformatics analyses is the assembly of the genome sequence of an organism using the data generated from the sequencing machines. Despite the long length of sequences generated by third-generation sequencing technologies (tens of thousands of basepairs), the automated reconstruction of entire genomes continues to be a formidable computational task. Although long read technologies help in resolving highly repetitive regions, the contigs generated from long read assembly do not always span a complete chromosome or even an arm of the chromosome. Recently, new genomic technologies have been developed that can ''bridge" across repeats or other genomic regions that are difficult to sequence or assemble and improve genome assemblies by ''scaffolding" together large segments of the genome. The problem of scaffolding is vital in the context of both single genome assembly of large eukaryotic genomes and in metagenomics where the goal is to assemble multiple bacterial genomes in a sample simultaneously.First, we describe SALSA2, a method we developed to use interaction frequency between any two loci in the genome obtained using Hi-C technology to scaffold fragmented eukaryotic genome assemblies into chromosomes. SALSA2 can be used with either short or long read assembly to generate highly contiguous and accurate chromosome level assemblies. Hi-C data are known to introduce small inversion errors in the assembly, so we included the assembly graph in the scaffolding process and used the sequence overlap information to correct the orientation errors.Next, we present our contributions to metagenomics. We developed a scaffolding and variant detection method MetaCarvel for metagenomic datasets. Several factors such as the presence of inter-genomic repeats, coverage ambiguities, and polymorphic regions in the genomes complicate the task of scaffolding metagenomes. Variant detection is also tricky in metagenomes because the different genomes within these complex samples are not known beforehand. We showed that MetaCarvel was able to generate accurate scaffolds and find genome-wide variations de novo in metagenomic datasets.Finally, we present EDIT, a tool for clustering millions of DNA sequence fragments originating from the highly conserved 16s rRNA gene in bacteria. We extended classical Four Russians' speed up to banded sequence alignment and showed that our method clusters highly similar sequences efficiently. This method can also be used to remove duplicates or near duplicate sequences from a dataset.With the increasing data being generated in different genomic and metagenomic studies using emerging sequencing technologies, our software tools and algorithms are well timed with the need of the community.
일반주제명Computer science.
Genetics.
Physiology.
Microbiology.
Bioinformatics.
Artificial intelligence.
Public health.
Information science.
언어영어
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