• Tier 1 Canada Research Chair in Genome Data Sciences
• Professor of Statistical Sciences, Computer Science and Biostatistics, University of Toronto
• Senior Scientist, Program in Genetics and Genome Biology, The Hospital for Sick Children
• Director, CANSSI Ontario
• Associate Director, The Centre for Applied Genomics
T-CAIREM member Lisa Strug is a Professor of Statistical Sciences, Computer Science and Biostatistics and a Senior Scientist with the Genetics and Genome Biology program at the Hospital for Sick Children. She leads a team that explores novel statistical methodology to unravel the complex underpinnings of genetic disease such as Cystic Fibrosis as well as the genetic contributors of childhood onset Epilepsy.
What inspired you to pursue a career researching genome data sciences?
My PhD dissertation work was in the Foundations of Statistical Evidence, and in particular pure likelihood theory approaches to providing alternatives to measures such as p-values. At the time, the field of genetics was very open to this new theory and there were some interesting applications. So I went to Columbia University in New York to do a post-doctoral fellowship in the Genetics of Complex Disease Gene Mapping where I was immediately fascinated by the potential of advanced statistical modeling in genetics and genomics.
What’s your proudest professional accomplishment?
I have spent the last 15 years working with talented graduate students and a cross-disciplinary team of scientists building a set of statistical tools and applying them to map modifier genes for Cystic Fibrosis (CF). Modifier genes are other genetic factors that contribute to disease variation in the presence of a known major causal gene. The genes we have identified have significantly advanced our understanding of the multi-organ impact of CF and are now being translated to clinical tools for early intervention and drug targets for medicines. I am so proud of the hard work, commitment, successes and collegiality of the team!
What do you see as the biggest challenge to the field of genome data science right now?
Technological advancement is leading to the generation of genomic data at unprecedented scale and resolution. This is both a challenge and an opportunity. But the conventional statistical tools used for analysis are not designed for the size and complexity of the data. Significant methodological development is needed to take full advantage of the data.
What do you like to do when you aren’t working?
I really enjoy hiking, reading, playing tennis and spending lots of outdoor time with my three kids and husband.
What projects are you currently working on that you’re really excited about?
At the SickKids’ Genome Centre, The Centre for Applied Genomics, we are leading a national project to build a databank of whole genome sequence and clinical data from 10,000 individuals who tested positive for SARS-CoV-2 infection. These data are accessible to researchers across the country and internationally. We hope that the T-CAIREM research community will use the databank to support their research interests.
