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Mapping complex disease loci in whole-genome association studies

Author

Listed:
  • Christopher S. Carlson

    (University of Washington)

  • Michael A. Eberle

    (Fred Hutchinson Cancer Research Center)

  • Leonid Kruglyak

    (Howard Hughes Medical Institute, Fred Hutchinson Cancer Research Center
    Fred Hutchinson Cancer Research Center)

  • Deborah A. Nickerson

    (University of Washington)

Abstract

Identification of the genetic polymorphisms that contribute to susceptibility for common diseases such as type 2 diabetes and schizophrenia will aid in the development of diagnostics and therapeutics. Previous studies have focused on the technique of genetic linkage, but new technologies and experimental resources make whole-genome association studies more feasible. Association studies of this type have good prospects for dissecting the genetics of common disease, but they currently face a number of challenges, including problems with multiple testing and study design, definition of intermediate phenotypes and interaction between polymorphisms.

Suggested Citation

  • Christopher S. Carlson & Michael A. Eberle & Leonid Kruglyak & Deborah A. Nickerson, 2004. "Mapping complex disease loci in whole-genome association studies," Nature, Nature, vol. 429(6990), pages 446-452, May.
    • Handle: RePEc:nat:nature:v:429:y:2004:i:6990:d:10.1038_nature02623
    DOI: 10.1038/nature02623
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    Cited by:

    1. Junxi Zheng & Juan Zeng & Xinyang Wang & Gang Li & Jiaxian Zhu & Fanghong Wang & Deyu Tang, 2022. "HSIC CR : A Lightweight Scoring Criterion Based on Measuring the Degree of Causality for the Detection of SNP Interactions," Mathematics, MDPI, vol. 10(21), pages 1-17, November.
    2. Marika Plöthner & Martin Frank & J.-Matthias Graf Schulenburg, 2017. "Cost analysis of whole genome sequencing in German clinical practice," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(5), pages 623-633, June.
    3. Xin Li & Lin Zhou & Tao Jia & Ran Peng & Xiongwu Fu & Yuliang Zou, 2020. "Associating COVID-19 Severity with Urban Factors: A Case Study of Wuhan," IJERPH, MDPI, vol. 17(18), pages 1-20, September.
    4. Tomas Drgon & Ping-Wu Zhang & Catherine Johnson & Donna Walther & Judith Hess & Michelle Nino & George R Uhl, 2010. "Genome Wide Association for Addiction: Replicated Results and Comparisons of Two Analytic Approaches," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-13, January.

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