A strong believer in accessible data, statistician Susan Holmes, PhD, specializes in visualization. She is particularly drawn to complicated datasets and has worked on a wide variety of topics, including phylogenetic trees, Congressional voting and human disease.
Holmes often collaborates with non-statistician researchers, mixing their expertise with her skills in data visualization to display findings in meaningful, understandable forms. She's currently working with Stanford microbiologist and immunologist David Relman, MD to understand the vaginal microbiome of pregnant women.
For research published in PNAS in 2015, Holmes was able to take results from 4,013 vaginal, gut, and oral specimens and form them into an intricate yet easy to interpret graph that revealed a substantial finding. It turned out that the microbiomes of women who experienced preterm labor stood out from those of other groups, as Holmes explained recently in a Q&A with the Stanford News Service:
The visualization [fig. 2] shows it all in some sense, because you can also see that in that group the bacteria are of many different types and don’t have a characteristic signature as in other groups. This suggests that we might be able to predict pregnancy outcomes through measuring the microbiota present early in gestation.
That’s what I specialize in, taking a large amount of variables and lots of measurements and all kinds of information and trying to make it so that we can have pictures of the data that point out the underlying structure.
Her work with Relman exemplifies the type of interdisciplinary collaboration that is central to her career — and a practice she's hoping to pass on to her students and colleagues.
Previously: How one statistician is refining clinical trials, Key to collaboration: location, location, location. And coffee. and UseR conference: Fun with statisticians and programmers
Photo by Linda A. Cicero / Stanford News Service