Posted By: Sarah Ratzel, PhD, Science Editor, AJHG
Each month, the editors of The American Journal of Human Genetics interview an author of a recently published paper. This month, we check in with Amy Williams to discuss her paper, “Rapid, Phase-free Detection of Long Identity-by-Descent Segments Enables Effective Relationship Classification”.
AJHG: What caused you to start working on this project?
Amy: Our past work on relatedness inference showed that methods for inferring identical by descent (IBD) segments were computationally intensive, and we thought there could be a way to speed up the process of finding these segments. The most computationally intensive part of IBD detection in the datasets we examined was phasing, so we thought that avoiding that component could provide a large speed improvement.
AJHG: What about this paper most excites you?
Amy: It’s perhaps unexpected that phasing is not necessary to reliably locate IBD segments. Detecting segments in this way has a trade off of only being able to reliably locate very long segments, and yet, those long segments enable the classification of relatives out to sixth degree (e.g., second cousins once removed). This was surprising to us and exciting to find.
AJHG: Thinking about the bigger picture, what implications do you see from this work for the larger human genetics community?
Amy: This work—along with other methods that target large studies—helps us realize the promise of the massive datasets we now have. We need new algorithms to analyze these datasets, and this algorithm specifically addresses IBD detection. It fits in the context of a number of other methods that have been and are being developed to address many computational problems in human genetics.
AJHG: What advice do you have for trainees/young scientists?
Amy: Find areas of research that are emerging as new avenues of inquiry, or consider older areas that can be uniquely solved with current data. The huge sample sizes now available for human subjects were not as much of a focus a few years ago, so papers on relatedness inference and IBD detection—though prominent then—were not as concerned with the challenges that big datasets bring.
AJHG: And for fun, tell us something about your life outside of the lab.
Amy: It’s so easy to focus on one’s job and neglect opportunities we have to step outside ourselves and help other people. I am privileged to be able to serve in my church and in the community where I live. Many face great challenges, and our research isn’t going to help them get by day to day, so helping others with their most basic needs is important and fulfilling.
Amy Williams, Ph.D., is an Assistant Professor in the Department of Biological Statistics and Computational Biology and the Nancy and Peter Meinig Family Investigator in Life Science and Technology at Cornell University.