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Applications and Analysis of Epigenetic Data in Public Health Research


East Baltimore
Summer Inst. term
Mental Health
1 credits
Academic Year:
2019 - 2020
Mon 06/03/2019 - Mon 06/03/2019
Class Times:
  • Monday,  8:30am - 4:50pm
Auditors Allowed:
Grading Restriction:
Course Instructor s:
Brion Maher
Frequency Schedule:
One Year Only

This course will describe the rationale for inclusion of epigenetic measurement in public health research. It will then describe molecular measurement options, design choices, and analytic approaches to such data in the study of environmental and genetic epidemiology.

Presents applications of epigenetic measurement in public health research. Begins by providing a rationale for such work, then describing measurement tools, from single-site methylation typing, to array-based methods, and whole-genome sequencing. Study design options, quality control analyses, and association analyses will then be presented. Examples based on both mental and physical health outcomes will be used.

Learning Objectives:

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

  1. Describe the rationale for including epigenetic measurements in public health research
  2. Describe the single-site and genome-scale approaches to epigenetic measurement, appropriate for public health research
  3. Apply quality-control analysis to epigenetic data generated in epidemiologic sample sets
  4. Apply association analyses to identify epigenetic marks associated with genes, exposures, and/or disease outcomes
Methods of Assessment:

This course is evaluated as follows:

  • 20% In-class Exercises
  • 40% Quizzes
  • 40% Written Assignment(s)

Instructor Consent:

No consent required

Special Comments:

This one-day course is offered in partnership with the Department of Epidemiology course 340.833.11 DESIGNS AND ANALYSIS FOR HUMAN GENOMIC SEQUENCING DATA. Participants are encouraged to register for both courses. An optional second day epigenetic computing laboratory (330.990.11) will be offered to teach the software implementation of methods described in the course.