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Course Catalog

340.732.81 Principles of Genetic Epidemiology 2


2nd term
3 credits
Academic Year:
2017 - 2018
Auditors Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Terri Beaty
Course Instructor:

Introduction to Online Learning is required prior to participating in any of the School's Internet-based courses. Principles of genetic epidemiology 1(340.731.01) and/or permission of instructor.


Second offering in a four-quarter series of graduate courses in Genetic Epidemiology. Details the concepts of linkage disequilibrium and population genetics, including methods for admixture analysis useful for adjusting for individual variation in genetic ancestry/background. Presents the principles of genetic association analyses for quantitative and qualitative phenotypes for population-based studies. Details the concepts and tools related to confounding due to population stratification, and approaches for genome-wide association studies. Introduces methods for linkage analysis in families and use of high-throughput sequence data (whole exome and whole genome). Selected class sessions are dedicated to computer labs to illustrate the methods covered.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Demonstrate the concepts of linkage disequilibrium and explain haplotype analysis
  2. Discuss the concept of genetic admixture and confounding by ancestry in the context of epidemiology studies
  3. Describe the various design strategies for genetic studies and discuss the advantages and disadvantages of each
  4. Perform genetic association tests in population-based samples, in either prospective or retrospective designs
  5. Apply tools to adjust for confounding by ancestry
  6. Apply the above concepts in the context of genome-wide association studies
  7. Perform and interpret linkage analyses on family data
  8. Explain the difference between genetic association and genetic linkage studies
  9. Explain the advantages and disadvantages of sequencing (whole exome/whole genome) studies compared to candidate gene or genome-wide marker based studies
  10. Describe and evaluate methods for quality control of data from genome-wide marker studies
Methods of Assessment:

25% computer lab; 25% written critique of selected reference; 10% group presentation; 40% final exam.

Instructor Consent:

Consent required for all students

Consent Note:

Consent required for those without 340.731 and all students planning to take the course online instead of in-class.

For consent, contact:

Special Comments:

Designed for online students only.