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Statistical Methods for High-dimensional Genetic and Genomic Data
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Statistical Methods for High-dimensional Genetic and Genomic Data. |
| 개인저자 | Wu, Chong. |
| 단체저자명 | University of Minnesota. Biostatistics. |
| 발행사항 | [S.l.]: University of Minnesota., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 123 p. |
| 기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
| ISBN | 9780438350939 |
| 학위논문주기 | Thesis (Ph.D.)--University of Minnesota, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Advisers: Weihua Guan |
| 요약 | Modern genetics research constantly creates new types of high-dimensional genetic and genomic data and imposes new challenges in analyzing these data. This thesis deals with several important problems in analyzing high-dimensional genetic and ge |
| 요약 | First, we introduce a site selection and multiple imputation method to impute missing data in covariates in epigenome-wide analysis of DNA methylation data, which can help us adjust potential confounders, such as cell type composition. Second, t |
| 일반주제명 | Statistics. Genetics. Bioinformatics. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
