Reagan Kesting has a BS in Biochemistry and Mathematics from Baylor University—and he recently added an MPH in Biostatistics from NYU GPH! Reagan's interests are in bioinformatics, statistical genetics, and genomics in the context of precision medicine applications. He’s also interested in the clinical expansion of emergency medicine to better serve those without a primary care physician. As a recent alumnus, Reagan plans to apply to medical school full-time while continuing his research.
Degree Program/Concentration: MPH in Biostatistics
Internship Company: Icahn School of Medicine at Mount Sinai
Internship Location: New York, NY
SECURING THE INTERNSHIP
How did GPH help secure your internship at Mount Sinai?
My biostats professor introduced me to statistical genetics during office hours, sparking my interest in the field. Then my discussion leader for epidemiology recommended that I look outside of NYU for that specific research focus, pointing me toward Cornell, Columbia and Mt. Sinai for statistical genetics.
I was examining those schools and came across Dr. Paul O’Reilly at Mt. Sinai, who not only worked in statistical genetics, but in a specific area called Polygenic Risk Scores (PRS). Essentially, you assign a risk value to an individual or population, given their genetic makeup. I had already been interested in statistical applications in medicine, so his work really stood out to me! We scheduled a meeting, and a few months later I joined his lab as a research assistant for the department of genetics and genomic science.
THE GIG
What were your main responsibilities as an intern?
A typical day started in the Department of Genetics and Genomics, where I would meet with Dr. Alanna Cote, my project advisor. She’d note the progress I was making and answer any questions, and we would discuss different directions to take with the data. Primarily, I worked on the computer all day in a program called GSA-MiXeR, where I was investigating pathway enrichment analysis for various disease traits. Throughout the day Dr. Cote and I would share our thoughts on incorporating my findings into a paper we were collaborating on. At the end of the day, I would submit big job scripts to run overnight, and come in the next day to see if my code had run successfully, or if we had any significant results.
For the first half of the internship my day centered around troubleshooting the software I was using; it was newly documented and published, so there was not much information surrounding its operation, formatting and error lines. But once I learned how to format my data to meet the input standards of the software, the rest of the summer was focused on understanding the concepts around many statistical genetics techniques such as GWAS, pathway enrichment and MAGMA.
What’s been a surprising or unexpected part of the job?
Enjoying it as much as I did! When I started out I thought I would be lost, with all of the big conceptual models and population genetic concepts. But as the summer progressed, I found myself curious about other applications of genetics and genomics, and it started me thinking about how I could take what I learned and apply it to the next phase of my career.
How has your internship allowed you to use current skills and develop new ones?
I found myself leaning heavily on the information and concepts from my Intro to R course and a machine learning course, both with Dr. Yang Feng. A lot of my data management skills were put to use in tidying data, merging various datasets, and formatting data to fit certain input parameters. I also learned new software techniques like MAGMA and GSA-MiXeR that I plan on using for my thesis project.
What was the biggest learning curve?
Both coding and using the new software. While I knew R going into the internship, I had to learn Bash and Python virtually from scratch, since a lot of the input for my program required Python language. I was also using a newly-published software that had vague documentation and data sources scattered throughout a repository, so learning how to troubleshoot the software and format my data accordingly was definitely a challenge.
THE SOCIAL AND CULTURAL EXPERIENCE
How did you connect with other interns and employees?
It was easy to connect with employees at the medical school, since most of our lab members were onsite and shared office space. I also met employees from different departments, especially during lab meetings where some projects overlapped. The best part was getting to know people from the medical school and learning about their mission and their curriculum. Since I hope to attend medical school one day, doing research at a top medical school was a big perk in itself—as well as connecting with various professors.
ADVICE FOR OTHER STUDENTS
What advice do you have for students who want a similar internship?
Don’t be afraid to cold-email professors from other academic institutions; there is power in email to easily be connected to faculty. Even if their project has nothing to do with what you’re interested in, reach out to them anyway. And don’t be afraid to take classes outside of GPH; for instance, I wish I had taken a genomics course before going into my research position. But on the advice of Dr. Rebecca Betensky and my academic advisor, I’ve enrolled in two genomics and bioinformatics courses this semester to further my knowledge in the subject matter. I’ve enjoyed it so much, and I’ll use the knowledge for my thesis and future career goals.
HIGHLIGHTS AND REFLECTIONS
What was your favorite part of the internship?
The best part about this internship has been working on a research project with Dr. Cote, my advisor; it will be published soon. Working with her and the faculty lab leader was a great experience; they were both present and engaged, and they continuously advocated for my contributions to the paper.
Can you describe a memorable moment or a proud accomplishment?
My proudest accomplishment was seeing results from my analysis for the first time after 36 hours of running time. The whole summer I was hitting wall after wall with some of the data analysis, so when I finally got results—significant ones at that—I was so pleased; Dr. Cote and I were basically jumping for joy when the analysis results came back! I felt bad for the other employees in our office, but it was exciting because it took three months to get those results.
How has your APE shaped your future career goals—what's your "dream job" now?
Reflecting on my experience and how much I enjoyed the research, I would say my direction changed course a bit, but I now see a clear path ahead. While I still want to pursue an MD, I’m interested in pursuing both an MD and PhD so I can do statistical genetics and genomics research in precision medicine, while also practicing medicine so I can translate my findings in the clinical setting.