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Testing for Differences in Polygenic Scores in the Presence of Confounding
Testing for Differences in Polygenic Scores in the Presence of Confounding
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211153128
- ISBN
- 9798346875314
- DDC
- 575
- 서명/저자
- Testing for Differences in Polygenic Scores in the Presence of Confounding
- 발행사항
- [Sl] : The University of Chicago, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 150 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-06, Section: B.
- 주기사항
- Advisor: Berg, Jeremy J.
- 학위논문주기
- Thesis (Ph.D.)--The University of Chicago, 2024.
- 초록/해제
- 요약Polygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations and empirical analysis, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Specifically, for any given test, there exists a single axis of population structure in the GWAS panel that needs to be controlled in order to protect the test. Based on this result, we propose a new approach for directly estimating this axis of population structure in the GWAS panel. We then use simulations to compare the performance of this approach to the standard approach in which the principal components of the GWAS panel genotypes are used to control for stratification. Finally, we develop a hybrid approach for empirical data analysis that uses the test panel genotypes to estimate how well protected any given test is by the inclusion of principal components and apply this approach across a diverse set of tests.
- 일반주제명
- Genetics
- 일반주제명
- Statistics
- 일반주제명
- Biology
- 일반주제명
- Bioinformatics
- 키워드
- Polygenic scores
- 키워드
- GWAS panel
- 기타저자
- The University of Chicago Human Genetics
- 기본자료저록
- Dissertations Abstracts International. 86-06B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■006m o d
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■020 ▼a9798346875314
■035 ▼a(MiAaPQ)AAI31766240
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a575
■1001 ▼aBlanc, Jennifer Grace.▼0(orcid)000-0001-7569-018X
■24510▼aTesting for Differences in Polygenic Scores in the Presence of Confounding
■260 ▼a[Sl]▼bThe University of Chicago▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a150 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-06, Section: B.
■500 ▼aAdvisor: Berg, Jeremy J.
■5021 ▼aThesis (Ph.D.)--The University of Chicago, 2024.
■520 ▼aPolygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations and empirical analysis, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Specifically, for any given test, there exists a single axis of population structure in the GWAS panel that needs to be controlled in order to protect the test. Based on this result, we propose a new approach for directly estimating this axis of population structure in the GWAS panel. We then use simulations to compare the performance of this approach to the standard approach in which the principal components of the GWAS panel genotypes are used to control for stratification. Finally, we develop a hybrid approach for empirical data analysis that uses the test panel genotypes to estimate how well protected any given test is by the inclusion of principal components and apply this approach across a diverse set of tests.
■590 ▼aSchool code: 0330.
■650 4▼aGenetics
■650 4▼aStatistics
■650 4▼aBiology
■650 4▼aBioinformatics
■653 ▼aPolygenic scores
■653 ▼aPopulation genetics
■653 ▼aStatistical genetics
■653 ▼aGWAS panel
■690 ▼a0369
■690 ▼a0306
■690 ▼a0715
■690 ▼a0463
■71020▼aThe University of Chicago▼bHuman Genetics.
■7730 ▼tDissertations Abstracts International▼g86-06B.
■790 ▼a0330
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17165136▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
