'The future is very bright': U of T researcher on building a data science community in Ontario

With 15 years of experience doing data-driven research in the field of genomics, the University of Toronto’s Lisa Strug is perfectly placed to be helping researchers throughout the province build their own data science capabilities.

Strug is the director of CANSSI Ontario, the Ontario Regional Centre of the Canadian Statistical Sciences Institute. With U of T’s Faculty of Arts & Science as its academic host, CANSSI Ontario was established as a multidisciplinary unit in July 2019 with a goal to build statistical and data science capabilities throughout the university and the province. 

CANSSI is a national institute launched in 2012 with the mission to support and enhance research and training in data science.

“With the volume of data exploding across all fields, the timing for CANSSI Ontario is fantastic,” says Strug, who is a professor in U of T’s departments of statistical sciences and computer science in the Faculty of Arts & Science and a senior scientist and associate director of the Centre for Applied Genomics at the Hospital for Sick Children. “At CANSSI Ontario, we're developing programs to support multidisciplinary activity that bring researchers together to create new research relationships and solve problems in specific domains.

“Together, we’re learning about the role of data science in public policy, in Indigenous data sovereignty, in biomedical science, in the criminal justice system and more.”

Strug’s research focuses on the development of statistical methods to identify genetic contributors to complex traits in diseases such as cystic fibrosis and epilepsy, and her team is translating genetic discoveries into improved diagnostics and personalized therapies. Earlier this year, she and collaborators began a new research project to identify genetic variation in patients with COVID-19 that might explain why the disease affects people differently.

Chris Sasaki, a writer in the Faculty of Arts & Science, spoke with Strug about CANSSI Ontario and how it can help researchers address some of the world’s biggest global challenges.

Why is CANSSI Ontario’s emphasis on data-driven research so important?

The sheer volume of data – in the humanities, social sciences, sciences – means that new tools need to be developed to handle and optimize the use of this data, or existing tools used in other domains need to be repurposed. We need algorithmic computational techniques and classical statistical techniques. And we need researchers from different disciplines – with their domain-specific knowledge – working together. Tools need to be developed that are tailored to the big global challenges of today and individuals need to be trained in how to use these tools.

How does CANSSI Ontario promote an interdisciplinary and collaborative approach?

One great success story is the Strategic Training for Advanced Genetic Epidemiology program, or STAGE, a successful multidisciplinary training program that has been in existence since 2009. STAGE trains graduate students, post-docs and early-career faculty who want to re-tool and train in the field where genetics, epidemiology and statistics meet. It offers training in the use and development of quantitative tools for genomic data. The program existed before CANSSI, but over the last few years has been unfunded. Now, CANSSI Ontario has adopted it and it’s funded by the Faculty of Arts & Science and is a collaboration with the Dalla Lana School of Public Health.

In fact, STAGE has been used as a model to implement a new multidisciplinary doctoral program that we've implemented in the Faculty of Arts & Science this past year. This is a pilot program with the department of statistical sciences and integrates with any other unit across the university where a doctoral student in statistics is co-trained with a faculty member in another department or field using the STAGE model. And this program goes beyond statistical genetics and genetic epidemiology; our first cohort of students includes co-mentorship between astrophysics and statistics, as well as biomedical science and statistics. It's very exciting to see this new multidisciplinary program evolve, modeled after the successes of STAGE but now open to all domain areas.

What sort of funding support does CANSSI Ontario provide?

One of our mandates is to remove barriers to accessing large, publicly available datasets that could benefit the research of our affiliated faculty and trainees. Several data sources have costs associated with accessing or computing with them, and, in some cases, those costs have become prohibitive. So we started a data-access grant program that removes that barrier by offering to cover those costs.

Funding support also comes in the form of awards. For example, in partnership with the Banting Research Foundation, we have the Banting-CANSSI Ontario Discovery Award in Data Science. It’s a one-year grant of up to $25,000 and it’s designed to encourage new faculty to be engaged in multidisciplinary, data-driven health and biomedical research.

And we’re very proud that in 2020, it was awarded to Dylan Kobsar from McMaster University to develop computational methodologies to analyze human movement, which will in turn have applications in wearable sensors for managing osteoarthritis.

How do you feel about your first year as director of CANSSI Ontario?

I've really enjoyed the role. For the past 15 years, I’ve been focused on data science in genomics, but now I have the opportunity to learn about the data-driven research in other disciplines across the faculty and I’m learning a ton.

I'm enjoying speaking to different communities and understanding what their needs are, so we can then work to develop programs and activities to support them and facilitate the work they are doing to solve some of society’s most challenging problems.

The timing for CANSSI Ontario is right, and the future is very bright. We need this initiative to bring people together to share ideas and to share know-how.