1 resultado para Fiducial marker
em Digital Commons - Michigan Tech
Filtro por publicador
- Aberdeen University (4)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (13)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (2)
- Aquatic Commons (3)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (1)
- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (1)
- Archive of European Integration (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (1)
- Aston University Research Archive (10)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (13)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (4)
- Bioline International (2)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (92)
- Brunel University (1)
- Cambridge University Engineering Department Publications Database (4)
- CentAUR: Central Archive University of Reading - UK (15)
- Center for Jewish History Digital Collections (2)
- Centro Hospitalar do Porto (1)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (23)
- Cochin University of Science & Technology (CUSAT), India (1)
- Collection Of Biostatistics Research Archive (1)
- CORA - Cork Open Research Archive - University College Cork - Ireland (1)
- Dalarna University College Electronic Archive (1)
- Deakin Research Online - Australia (31)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (1)
- Digital Commons - Michigan Tech (1)
- Digital Commons at Florida International University (2)
- Digital Peer Publishing (2)
- DigitalCommons@The Texas Medical Center (9)
- Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland (1)
- DRUM (Digital Repository at the University of Maryland) (1)
- Duke University (2)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (58)
- Glasgow Theses Service (1)
- Helda - Digital Repository of University of Helsinki (38)
- Hospitais da Universidade de Coimbra (1)
- Indian Institute of Science - Bangalore - Índia (15)
- Instituto Politécnico do Porto, Portugal (1)
- National Center for Biotechnology Information - NCBI (19)
- Ohio University (1)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (6)
- Publishing Network for Geoscientific & Environmental Data (37)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (58)
- Queensland University of Technology - ePrints Archive (364)
- Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa) (2)
- Repositório Científico da Universidade de Évora - Portugal (2)
- Repositório Digital da UNIVERSIDADE DA MADEIRA - Portugal (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (56)
- School of Medicine, Washington University, United States (2)
- Universidad de Alicante (1)
- Universidad Politécnica de Madrid (4)
- Universitat de Girona, Spain (1)
- Université de Lausanne, Switzerland (3)
- Université de Montréal, Canada (1)
- University of Connecticut - USA (2)
- University of Michigan (7)
- University of Queensland eSpace - Australia (26)
- Worcester Research and Publications - Worcester Research and Publications - UK (1)
Resumo:
As the development of genotyping and next-generation sequencing technologies, multi-marker testing in genome-wide association study and rare variant association study became active research areas in statistical genetics. This dissertation contains three methodologies for association study by exploring different genetic data features and demonstrates how to use those methods to test genetic association hypothesis. The methods can be categorized into in three scenarios: 1) multi-marker testing for strong Linkage Disequilibrium regions, 2) multi-marker testing for family-based association studies, 3) multi-marker testing for rare variant association study. I also discussed the advantage of using these methods and demonstrated its power by simulation studies and applications to real genetic data.