Stanford scientist Manuel Rivas describes how his mentors shaped his approach to research and training in his own lab
A data scientist and former student researcher shares how the Broad Institute helped guide his career
Manuel Rivas is a biomedical data scientist and an assistant professor at Stanford University who builds statistical models and computational tools to uncover the roots of disease. But back in the summer of 2003, he was a high school student learning basic concepts of genomics that are now essential to his research. That summer, Rivas joined other rising high school seniors in the Minority Introduction to Engineering and Science (MITES) program at MIT, through which he participated in the Broad’s genomics elective course with guidance from Broad scientist Carrie Cibulskis.
The following summer, before his freshman year at MIT, he participated in the inaugural Broad Summer Research Program (BSRP), an intensive nine-week summer research opportunity designed for undergraduates. With help from his Broad mentors, Emily Walsh and John Rioux, he characterized genetic variation in the human leukocyte antigen (HLA) region of the genome.
The BSRP, run by the Broad’s Diversity, Education, and Outreach Office, aims to increase the number of students, especially those from underrepresented backgrounds, entering and succeeding in STEM careers. The office is focused on developing and implementing innovative programming to enhance student understanding and access to STEM careers. Since 2003, 148 undergraduates have participated in the BSRP. The Broad has also hosted 87 high school students in its Broad Summer Scholars Program (BSSP) since 2013, in addition to 247 high school seniors who, like Rivas, have completed the Broad’s genomics elective course through the MITES program since 2003.
Due to the COVID-19 pandemic, student researchers this summer are participating in the programs remotely and focusing on computational research. For the BSSP, running June 29 through August 7, twelve high school scholars are working in teams of two with one Broad scientist-mentor to conduct research in areas such as infectious disease, imaging, cancer, and psychiatric disease. For the BSRP, running June 8 through July 31, ten undergraduates are learning a programming language and completing group projects remotely with input from several Broad scientists. Four of the undergraduates, who have experience in computational methods, are working on independent research projects. Other events, including career panels, scientific talks, social events, and presentations, are occurring via video conference.
In the second of a short series of articles featuring alumni of these summer programs, we spoke with Rivas, who graduated from MIT in 2008 with a bachelor’s degree in mathematics and then joined the Broad as a staff scientist At the Broad, Rivas discovered his passion for developing statistical techniques and computational tools for biomedical data analysis. He went on to complete graduate studies in human genetics at Oxford University, and then returned to the Broad, where he led an effort to identify genetic and environmental risk factors for inflammatory bowel disease, before starting his lab at Stanford in 2016.
In this Q&A, Rivas shared with us how his mentors helped him grow as a researcher and how they’ve helped shape his own scientific values and philosophy.
Q: How did your experience at the Broad help guide your career path to biomedical research?
A: I was a very impressionable high school student [in the MITES program], and I thought the Broad was really remarkable. It was amazing to me that somebody like Eric Lander would take the time out of his schedule to meet us kids and give a passionate talk about his work. I found it fascinating that somebody who loves mathematics moved into the field of genetics, and that there were many applications to use some of those skill sets. I loved his story and I loved the passion.
I really believe in the message that genetics and genomics can help you understand disease and identify leads that can potentially lead to therapeutics. That’s what drove me to continue pursuing research opportunities. During the MITES program, I heard that the Broad would be starting a research program for undergraduates, and I was fortunate to be accepted and participate in the BSRP the following summer.
Q: What did you learn from your BSRP mentors?
A: During my summer with the MITES program, my mentor Carrie [Cibulskis] taught me a lot about lab experimental procedures. I discovered that I enjoyed looking at the data more than generating it, but it seemed almost like magic to me that someone with skilled hands and an instrument can generate such beautiful data. I always think of “wet lab” folks to be kind of wizards. I cherish that experience and it’s why I have high praise for folks that work in the lab.
When I was in the BSRP, it was so cool being part of the meetings between scientists at the Broad and seeing how passionate these people were. That’s when I met [Broad institute member] Mark Daly and [Broad founding member] David Altshuler who, along with my mentors Emily and John, were building the first stages of the Haplotype Map Project aimed at characterizing variation in the human genome.
Emily [Walsh] taught me about the genome and the clinical relevance of some of the work I was doing. She helped me realize that even though this is so important, no one in the world has done this research before. Being the first one to look at data and make sense of it became a really cool challenge. And John Rioux, the principal investigator, in addition to teaching me about the HLA region that we studied, also spent time telling me about his experiences in Latin America. My mentors were so friendly, and yet, so rigorous about their research.
I also worked closely with Todd Green, who sadly passed away recently. Todd was a kind and generous person, and a phenomenal, hands-on mentor. I was supposed to have computational skills coming into the program, but I pulled Todd to the side and admitted that while I could do mathematics, I couldn’t, for the life of me, print out “Hello, World!” in a computer program. Todd had tremendous patience and started teaching me about programming, databases, and managing and analyzing data. I ended up taking more classes in programming at MIT, but Todd helped first nurture my interest.
Q: How did your mentors help shape how you advise trainees in your lab?
A: I’ve learned that I can be a generous and personable mentor, while being scientifically rigorous. We want to be extremely confident with the science we put out into the world. With a mission to develop insights that could one day help treat and even cure human disease, the bar is so high and it’s so important that we need to make sure we put our best data and results out there.
Q: What experiences at the Broad have stuck with you since then?
A: It impressed me to hear researchers admit what they don’t know, and say, “We really don’t understand what’s going on in this data.” You’d think some of these people would have everything figured out, but then they’d ask me to take a look. The consistent challenging of ideas and assumptions back and forth between myself and my mentors was a phenomenally rewarding experience.>
At the Broad, I learned that the data-generating process is quite messy, and extracting signal from the noise is messy. To make sure you’re confident in your results, you have to exhaust every possible approach. If more data comes in, we follow where the data takes us. That’s how, at the end of the day, you end up getting the truth.
I’ve put some of those lessons into practice in my own lab today, and tried to instill these values in my trainees, but it takes time. You can develop really fancy methods, but you also have to understand your data, play with your data, and get messy with your data.
Q: What advice do you have for aspiring scientists who are pursuing a student research position?
A: Maybe there’s some data that no one has had the time or ability to interpret yet, but even as a student, you can take that as a challenge. Even in a summer program, it’s actually enough time to make a real contribution to understanding the data. Instead of focusing on publishing a paper, I’d suggest that you try to learn a skill set that you can use for the rest of your life.