330.690.11 Applications and Analysis of Epigenetic Data in Public Health Research
- Mental Health
- Summer Inst. term
- 1 credits
- Academic Year:
- 2019 - 2020
- East Baltimore
- Mon 06/03/2019 - Mon 06/03/2019
- Class Times:
- Monday, 8:30am - 4:50pm
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:
- Describe the rationale for including epigenetic measurements in public health research
- Describe the single-site and genome-scale approaches to epigenetic measurement, appropriate for public health research
- Apply quality-control analysis to epigenetic data generated in epidemiologic sample sets
- Apply association analyses to identify epigenetic marks associated with genes, exposures, and/or disease outcomes
- Methods of Assessment:
In class exercises 20%; online quiz 40%; short written assignment, due July 3 - 40%. Students will be required to read a set of papers related to epigenetic applications in public health prior to the class session.
- 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.