Genetic Epidemiology Foundations from Coursera

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Syllabus

What is Genetic Epidemiology? Historical Perspective and Introduction

Taught by Dr. Nancy Cox, Vanderbilt University Medical Center. In this module you will better understand genetic epidemiology from its origins to how modern ‘omics is integrated into genetic epidemiology of complex traits. Coverage includes introduction of liability and threshold models, genetic regulation of gene expression, and transcriptome imputation.

Introduction to Population Genetics: Models and Assumptions

Taught by Dr. Bruce Weir, University of Washington. Methods and designs using genetic data are built upon the foundation of population genetics. In this module, you will learn these foundations, including the Hardy Weinberg principle, genetic drift, population structure, inbreeding, and linkage disequilibrium. These principles will be essential to subsequent modules in this course.

Population Structure and Genetic Association Studies

Taught by Dr. Todd Edwards, Vanderbilt University Medical Center. Building from the introduction to population genetics, in this module you will learn processes that lead to genetic differences between populations, methods to characterize these differences, and how to conduct association studies in structured populations. In addition, you will be able to describe how admixture methods can be applied for association mapping.

Basic Quality Control in Genetic Data: Data Structure

Taught by Dr. Gonçalo Abecasis, University of Michigan and Regeneron, Inc. Quality control is an important step for high throughput genotype data. In this module, you will learn a range of different approaches to identify and to deal with quality problems at different stages of the analysis. In addition, genotype imputation is introduced to infer genotypes at markers that were not typed in the study samples.

Population-Based Association Studies

Taught by Dr. Celia Greenwood, McGill University. Population based association studies have played an important role in mapping genes and genomic regions for complex traits by detecting association between alleles and a trait. In this module, you will learn basic measures of association, common modeling strategies, how to adjust for multiple testing and why, how to evaluate association results, and how to increase reproducibility of study results, including the use of meta-analysis and genetic imputation.

Family-Based Designs

Taught by Dr. Joan Bailey Wilson, National Human Genome Research Institute, National Institutes of Health. In this module, you will learn about the various ways in which family-based collections of genetic data are utilized in Genetic Epidemiology. This includes methods that provide support that a genetic component to a trait exists as well as to identify modes of inheritance consistent with a set of data. In addition, linkage methods, which identify large regions of the genome, and association methods, which identify a smaller set of variants, are covered to understand genetic factors affecting a trait.

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Know what's good

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Develops foundational concepts in population genetics, which are core concepts in epidemiology

Examines quality control and imputation, which are important steps in genetic data analysis

Explores advanced topics such as genetic association studies, which are used to identify genetic variants associated with disease

Taught by experienced instructors from top universities and research institutions

Provides comprehensive coverage of genetic epidemiology, including historical perspectives, population genetics, and statistical methods

Includes hands-on labs and interactive materials, which help learners apply the concepts they learn

Reviews summary

Genetic epidemiology fundamentals

According to students, Genetic Epidemiology Fundamentals is a well-rounded introductory course that is appreciated for being well-structured and packed with quality content. However, some new learners have found the course to be difficult to understand and have taken issue with certain content lacking real-world examples and instructor feedback.

Course structure is clear and easy to follow.

"Profound,systematic and logical representation of the main points in genetic epidemiology."

"Excellent introductory lectures."

"I learned alternative ways of presenting this material and corrected some details from self study."

Instructors are not very responsive.

"There is no feedback or response from the creators of the course"

Could use more real-world examples.

"I thought the course spent too much time on formulas without providing the students a way to use those formulas to see the results and how they worked."

Course material is too difficult for beginners.

"its too complex to understnd"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Genetic Epidemiology Foundations with these activities:

Review basic statistics

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Strengthen the foundation for understanding statistical methods in genetic epidemiology.

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Review notes or textbooks
Complete practice problems

Read 'Introduction to Genetic Analysis'

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Review the core principles of genetics to prepare for the course.

View Introduction to Genetic Analysis on Amazon

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Gather required materials
Read and make notes on chapters 1-5
Complete the end of chapter questions

Organize and summarize lecture notes

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Improve retention and understanding of course material.

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Review lecture notes
Summarize key concepts
Organize notes in a logical structure

Five other activities

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Participate in a study group

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Enhance understanding through collaboration and peer support.

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Find or form a study group
Meet regularly to discuss course material
Work together on assignments and projects

Solve genetic problems

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Improve problem-solving skills and apply genetic concepts.

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Find practice problems online or in textbooks
Solve problems independently
Check answers and identify areas for improvement

Complete online tutorials on genetic analysis

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Supplement course material with additional resources.

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Identify relevant tutorials
Watch videos and complete exercises
Apply new knowledge to course assignments

Create a visual representation of genetic data

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Enhance data interpretation and communication skills.

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Choose a dataset and software
Create visual representations (e.g., graphs, charts)
Interpret and present results

Design a research proposal

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Develop a plan for a genetic research project.

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Identify a research question
Review relevant literature
Design a study plan
Write a research proposal

Career center

Learners who complete Genetic Epidemiology Foundations will develop knowledge and skills that may be useful to these careers:

Epidemiologist

Epidemiologists study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems.

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Medical Geneticist

A Medical Geneticist is a physician who interprets genetic tests, counsels patients and families about genetic disorders, and provides treatment recommendations.

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Research Scientist

Research Scientists design, conduct, and analyze research studies. They may work independently or as part of a team.

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Biostatistician

A Biostatistician is a statistician who works in the field of biology, applying statistical methods to the analysis of biological data.

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Data Analyst

A Data Analyst collects, processes, and analyzes data to extract meaningful insights. They use statistical techniques to identify trends and patterns in data.

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Computational Biologist

A Computational Biologist uses computational methods to analyze and interpret biological data, such as DNA and protein sequences.

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Health Educator

A Health Educator is responsible for promoting health and preventing disease by providing information and education to individuals and communities.

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Genetic Counselor

A Genetic Counselor provides information and support to individuals and families affected by genetic disorders.

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Science Writer

A Science Writer communicates complex scientific information to a non-scientific audience.

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Healthcare Administrator

A Healthcare Administrator is responsible for planning, organizing, and directing the delivery of health care.

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Public Health Nurse

A Public Health Nurse provides health care services to individuals and communities, with a focus on prevention and health promotion.

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Teacher

A Teacher is responsible for educating students at all levels, from preschool through college.

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Medical Laboratory Scientist

A Medical Laboratory Scientist performs tests on blood, urine, and other body fluids to help diagnose and treat diseases.

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Pharmacist

A Pharmacist dispenses medications and provides advice on their use to patients.

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Physician Assistant

A Physician Assistant is a healthcare professional who provides medical care under the supervision of a physician.

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Genetic Epidemiology Foundations

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Genetic epidemiology fundamentals

Activities

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