HGEN Curriculum
Required Courses for All HGEN Students
Ph.D. students in HGEN are required to complete a minimum of 29 credit hours of formal coursework (combined credits from required and elective courses). Students will take a minimum of 6 hours of didactic classes per semester during their first two years of study. It is expected that, during the second year, at least one semester will exceed this minimum to complete the required courses prior to year 3 of study. The electives will come from an approved list of advanced genetics courses (see below). In individual cases, other courses approved by the Director of Graduate Studies (DGS) and a student’s committee can serve as electives. The choice of these courses will be based on the individual student’s research interests. Other specific needs of students can be met with the electives, or in very rare cases, students with the support of their mentors can petition to replace one required course with another one suited to their research needs. Courses from other relevant programs (ex. Molecular Physiology & Biophysics, Biomedical Informatics, Biostatistics, and Epidemiology) may be taken for credit towards the HGEN PhD program with permission from the HGEN DGS and the course instructor.
Year 1
Fall
Human Genetics I (HGEN 8340) (3 credits): Population genetics and genetics of complex phenotypes. Designed to cover background and latest advances in
human genetics. Topics will include an overview of mutational mechanisms, cytogenetics (detection and description of chromosomal abnormalities), biochemical genetics (gene defects in biochemical pathways), molecular genetics (gene structure, function, and expression). Topics will be discussed with reference to specific human genetic diseases.
Tutorials in Human Genetics I (HGEN 8370) (1 credit): A weekly seminar critically evaluating current and past scientific literature from many areas of genetic research. The focus will be on study methods and analysis.
Genetics Interest Group (HGEN 8335-6) (1 credit): Each graduate student presents a work-in-progress talk annually.
Spring
Human Genetics II (HGEN 8341) (3 credits): This course will cover the statistical, population, and analytical aspects of modern human genetics research. Topics to be covered include human population genetics, quantitative genetics, linkage and association analyses, computational genetics, and evolutionary genetics. Clinical examples, subject ascertainment, and study design will also be emphasized. Students must have a strong understanding of Mendelian genetics and basic biostatistics. This course includes a weekly lab for hands-on analysis.
Tutorials in Human Genetics II (HGEN 8371) (1 credit): Graduate students critically evaluate research publications in areas statistical methods in human genetic analysis and in the area of human population genetics. Also, there are faculty presentations on ancillary science skills, such as oral and poster presentations, and grant and proposal writing.
Fundamentals of Genetic Analysis (HGEN 8395) (1 credit): This course is designed to accomplish three goals: (1) introduce students to critical topics of genetic research, (2) introduce students to important areas of genetic research not covered in first-year course work, and (3) promote an understanding of classical genetic analysis by learning genetics using the original literature. The approach will be to use classic literature that defined significant problems in genetic research. Specific topics will include: genetic analysis (segregation, independent assortment and locus mapping), human pedigree analysis and disease gene mapping, and population/quantitative genetics.
Genetics Interest Group (HGEN 8335-6) (1 credit): Each graduate student presents a work-in-progress talk annually.
Advanced Genetics Course Electives
Biobank Study Design (HGEN 8391) (3 credits) This is a practical course designed to train you to conduct research using the de-identified version of Vanderbilt’s electronic medical record (Synthetic Derivative, SD) and DNA biorepository (BioVU). After completion of this course you will have the skills to independently execute SD/BioVU projects and assist colleagues who wish to utilize the resource. Through a combination of lectures, demonstrations, and hands-on workshops, you will develop competence in all aspects of the BioVU research process, including project design, data extraction and cleaning, and analysis. You will also become familiar with practical aspects of using BioVU, including administrative/regulatory requirements and basic use of bioinformatics tools.
Practical Python Programming and Algorithms for Data Analysis (HGEN 8394) (3 credits) This course is intended for students who are focused on big data analysis in the Python programming language, from large scale epidemiologic datasets, electronic medical records, or next generation sequence data. It will cover basic programming, including strings, arrays, dictionaries, conditional statements, data visualization, external data sources, and algorithms, with a focus on using programing to solve challenges within the students’ own research projects. At the end of the course, students will have an understanding of the foundation of programming in Python. They will understand the importance and use of regular expressions and efficient data search tools and will demonstrate proficiency in algorithms and data visualization.
Additional Training
Activities of the Training Program in Support of our Educational Goals: These Figures illustrate how the major activities of the training program lead to accomplishing our educational goals. To simplify the complex diagrams, we have broken this down into three categories of training program activities: didactic, non-didactic, and RCR and Safety.