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Course Catalog

340.733.01 Principles of Genetic Epidemiology 3

Department:
Epidemiology
Term:
3rd term
Credits:
3 credits
Academic Year:
2019 - 2020
Location:
East Baltimore
Class Times:
  • Tu Th,  9:00 - 10:20am
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Contact:
Terri Beaty
Course Instructors:
Resources:
Prerequisite:

140.621-622 or 140.651-652; (2 courses in biostatistics and the first 2 courses in Genetic Epidemiology 340.731 & 340.732)

Description:

Brings together the principles of linkage, association and sequence analysis introduced in the first two terms and builds skills in applying and interpreting methods for such studies. Introduces advanced analytical methods in genetic epidemiology and illustrates their application using current software tools for both marker and sequence data.

Learning Objectives:

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

  1. Explain the models for linkage and association analysis to map genes influencing risk to complex diseases and their associated phenotypes in both family and population-based studies
  2. Interpret combined and meta-analysis of genome-wide markers in large-scale consortium studies using summary statistics
  3. Use currently available software to check for structural errors in family data, estimate allele frequencies, check for Mendelian inconsistencies and describe familial aggregation of both qualitative and quantitative phenotypes
  4. Critically read and interpret published articles on genome-wide efforts to map genes controlling both qualitative and quantitative phenotypes using conventional epidemiologic study designs
  5. Explain how variance components models can be used to identify quantitative trait loci (QTL) used to map genes for quantitative phenotypes
  6. Describe various cutting-edge analysis of large-scale genome-wide association studies to inform biology, causality, and prediction
Methods of Assessment:

Computer-based homework assignments 50% and written research project proposal with student presentation 50%

Instructor Consent:

Consent required for some students

Consent Note:

Advanced level genetics knowledge required

For consent, contact:

tbeaty@jhsph.edu

Jointly Offered With: