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Principles of Genetic Epidemiology 2


Summer Inst. term
3 credits
Academic Year:
2017 - 2018
Auditors Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor :
Ayesha Khan

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, and student presentations of published studies drawn from the recent scientific literature.

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 sample, 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 some students

Consent Note:

Consent required for those without 340.731.

For consent, contact: