Research Experiences in Genomic Applications of Responsible Data Science (REGARDS)

The University of Virginia School of Data Science and Center for Public Health Genomics will
collaborate to establish REGARDS (Research Experiences in Genomics Applications of
Responsible Data Science). Over the next five years, REGARDS will train 45 Masters-level
genomics data scientists through both classroom and research experiences. UVA’s Masters in
Data Science program is ideally suited to this effort because it affords 1) a year-long capstone
experience, 2) space for elective courses which allow students to acquire vital genomics content
knowledge alongside their data science curriculum, and 3) an emphasis on responsible data
science and research ethics that is crucial to the training of the biomedical and informatics
workforce. The School of Data Science has robust supports for student recruitment and mature
relationships with minority-serving institutions (MSIs) to ensure that the students trained in
genomics data science represent the diversity of the patients that will be impacted by their work.
As part of this initiative, the program leaders will revise data science courses (including our
required course on data ethics) to include more genomics and biosciences examples. We will
create three new courses: “Genomics Foundations”, “Foundations of Computational Genomics”
and “Statistical Genetics - Methods and Applications”. REGARDS participants each will complete
a two-semester research capstone as part of their degree. UVA School of Medicine researchers
have contributed projects to engage three student teams each year for five years, representing
the breadth of genomics data science: wet labs, microbiome projects, precision medicine and
bioinformatics. As part of this initiative, we will leverage well-attended data science events (virtual
and in person) to spread awareness about career opportunities and interesting problems in
genomic data science. Through these events and annual competitions, we will broaden public
interest in genomic data science, further expanding the potential workforce in genomic data
science.

Grant Number: 1R25HG012918-01A1
NIH Institute/Center: NIH
Principal Investigator: Donald Brown