Designing Geneticists: Study Design Issues in Population-based Genetics and Genomics Research

National Human Genome Research Institute

National Institutes of Health
U.S. Department of Health and Human Services


Designing Geneticists: Study Design Issues in Population-Based
Genetics and Genomics Research

American Society of Human Genetics 2007

San Diego, Calif.
October 23-27, 2007
Moderator: Emily L. Harris

National Human Genome Research Institute
Bethesda, Md.

Study design is a critical aspect of any research project. The study's purpose drives study design, influenced by practical issues. Genetic/genomic research increasingly uses population-based designs, such as case-control, genome-wide association studies, to study genetic susceptibility to common conditions and genetic influences on quantitative traits. Epidemiologic studies of such conditions now commonly include DNA collection and genetic information as part of the analyses. To effectively design and interpret such studies, knowledge of basic study design is critical as is an understanding of complications that genetic data introduce into such studies.

Crucial design decisions include case or outcome definition, control or comparison group definition, measurement methods and statistical analysis approach. Internal validity is imperative, and methods for assessing potential biases desirable. These presentations discuss basic study design choices and rationale; designs to maximize internal validity and external validity; gene-environment interaction; and how to look for and minimize bias.

Presentation Slides
Presentation PowerPoints
Introduction
Emily L. Harris, Ph.D., M.P.H.
Population Genomics
National Human Genome Research Institute
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Case-Control and Cohort Study Designs
Moyses Szklo, M.D., M.P.H., Dr.P.H.
Department of Epidemiology
Bloomberg School of Public Health
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Maximizing Internal and External Validity in Epidemiology Studies
Robert Hoover, M.D., Sc.D.
Division of Cancer Epidemiology and Genetics
National Cancer Institute
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Evaluating Potential Bias in and Interpreting Results from Epidemiologic Designs
Teri Manolio, M.D., Ph.D.
Population Genomics
National Human Genome Research Institute
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Evaluating Potential Bias in and Interpreting Results from Epidemiologic Designs
Ellen Wijsman, Ph.D.
Division of Medical Genetics and Department of Biostatistics
University of Washington
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Questions and Answers
Emily L. Harris, Ph.D., M.P.H.
Population Genomics
National Human Genome Research Institute
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Last Reviewed: June 18, 2010