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Large-Scale Analysis of Population Structural Variants Using Terabytes of SRA Sequencing Data
Large-Scale Analysis of Population Structural Variants Using Terabytes of SRA Sequencing Data
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211150940
- ISBN
- 9798382605579
- DDC
- 574
- 서명/저자
- Large-Scale Analysis of Population Structural Variants Using Terabytes of SRA Sequencing Data
- 발행사항
- [Sl] : University of California, Davis, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 115 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
- 주기사항
- Advisor: Brown, C. Titus.
- 학위논문주기
- Thesis (Ph.D.)--University of California, Davis, 2024.
- 초록/해제
- 요약Studying structural variants (SV) in populations is crucial since they cause more diversity and have more effects on gene function than small variants. However, population scale studies are challenging since finding SV from inexpensive short-read sequencing(SRS) methods have a high false positive rate. Conversely, long-read sequencing(LRS) are more accurate for SV discovery but are expensive at a population scale. Here, I develop new unbiased techniques to study SV in populations that are more scalable than the state-of-the-art. I show their utility in creating an SV catalog for the cattle breed augmented with their allele frequency.
- 일반주제명
- Bioinformatics
- 일반주제명
- Biology
- 일반주제명
- Genetics
- 키워드
- Genotyping
- 키워드
- Kmer Index
- 키워드
- Long reads
- 키워드
- Pangenomes
- 기타저자
- University of California, Davis Computer Science
- 기본자료저록
- Dissertations Abstracts International. 85-11B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211150940
■006m o d
■007cr#unu||||||||
■020 ▼a9798382605579
■035 ▼a(MiAaPQ)AAI30991701
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a574
■1001 ▼aShokrof, Moustafa.
■24510▼aLarge-Scale Analysis of Population Structural Variants Using Terabytes of SRA Sequencing Data
■260 ▼a[Sl]▼bUniversity of California, Davis▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a115 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-11, Section: B.
■500 ▼aAdvisor: Brown, C. Titus.
■5021 ▼aThesis (Ph.D.)--University of California, Davis, 2024.
■520 ▼aStudying structural variants (SV) in populations is crucial since they cause more diversity and have more effects on gene function than small variants. However, population scale studies are challenging since finding SV from inexpensive short-read sequencing(SRS) methods have a high false positive rate. Conversely, long-read sequencing(LRS) are more accurate for SV discovery but are expensive at a population scale. Here, I develop new unbiased techniques to study SV in populations that are more scalable than the state-of-the-art. I show their utility in creating an SV catalog for the cattle breed augmented with their allele frequency.
■590 ▼aSchool code: 0029.
■650 4▼aBioinformatics
■650 4▼aBiology
■650 4▼aGenetics
■653 ▼aGenotyping
■653 ▼aKmer Index
■653 ▼aLong reads
■653 ▼aPangenomes
■653 ▼aPopulation genomics
■653 ▼aStructural variants
■690 ▼a0715
■690 ▼a0306
■690 ▼a0369
■71020▼aUniversity of California, Davis▼bComputer Science.
■7730 ▼tDissertations Abstracts International▼g85-11B.
■790 ▼a0029
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17160235▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
