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Lisa Strug

Title: Senior Scientist, Genetics & Genome Biology
Designations: ScM, PhD
Phone: 416-813-7654 ext. 301762
External Email:
Alternate Contact Name: Natalie Sun
Alternate Phone: 416-813-7654 ext. 309032
Alternate Email:
U of T Positions: Professor, Statistical Sciences, Computer Science and Biostatistics
Chair Positions: Canada Research Chair – Tier I in Genome Data Sciences
Other Positions: Vector Faculty Affiliate

Research Positions

Associate Director, The Centre for Applied Genomics

U of T Positions

Director, Data Sciences Institute (DSI)
Director, Canadian Statistical Sciences Institute, Ontario Region


Dr. Strug is Professor in the Departments of Statistical Sciences, Computer Science and cross-appointed in Biostatistics at the University of Toronto and is a Senior Scientist in the Program in Genetics and Genome Biology at The Hospital for Sick Children (SickKids). Dr. Strug is the inaugural Director of the Data Sciences Institute (DSI), a tri-campus, multi-divisional, multi-institutional, multi-disciplinary hub for data science activity at the University of Toronto and affiliated Research Institutes. The DSI’s goal is to accelerate the impact of data sciences across the disciplines to address pressing societal questions and drive positive social change. Dr. Strug holds several other leadership positions at the University of Toronto including the Director of the Canadian Statistical Sciences Institute Ontario Region (CANSSI Ontario), and at SickKids as Associate Director of the Centre for Applied Genomics and the Lead of the Canadian Cystic Fibrosis Gene Modifier Consortium and the Biology of Juvenile Myoclonic Epilepsy International Consortium. She is a statistical geneticist and her research focuses on the development of novel statistical approaches to analyze and integrate multi-omics data to identify genetic contributors to complex human disease. She has received several honours including the Tier 1 Canada Research Chair in Genome Data Science.

Education and experience

  • 2003–2005: Postdoctoral Fellowship in Statistical Genetics as part of the Genetics of Complex Diseases Training Program, Departments of Biostatistics and Psychiatry, Mailman School of Public Health, Columbia University, New York, NY, USA. Supervisor: Dr. Susan E. Hodge
  • 2001–2003: PhD, Biostatistics, Public Health Sciences, University of Toronto, Toronto, ON, Canada. Supervisors: Dr. Charles Rohde (Johns Hopkins University) and Dr. Paul N. Corey (University of Toronto)
  • 1998–2001: ScM, Biostatistics, School of Public Health, Johns Hopkins University, Baltimore, MD, USA. Supervisor: Dr. Charles Rohde
  • 1996–1998: BS, Statistics, Faculty of Arts and Science, University of Toronto, Toronto, ON, Canada
  • 1993–1996: BA in Psychology, University of Western Ontario, London, ON, Canada


  • 2023: Cystic Fibrosis Canada Senior Scientist Research Award
  • 2019: Top Downloaded Article 2017-2018, Wiley. Article: Strug, 2018. “The evidential statistical paradigm in genetics” has been recognized as a top 20 most read papers published in Genetic Epidemiology.
  • 2018–2025: Canada Research Chair, Tier I in Genome Data Sciences
  • 2017: Associate Editor with npj Genomic Medicine
  • 2016: Senior Scientist Research Training Award, Cystic Fibrosis Canada
  • 2009: Robbie Award for most promising research grant, Canadian Cystic Fibrosis Foundation, Canada
  • 2009: Early Research Career Award, Ontario Ministry of Research and Innovation, Ontario Provincial Government, Canada


  1. Wang F, Panjwani N, Wang C, Sun L and Strug LJ. A flexible summary-based colocalization method with application to the mucin Cystic Fibrosis lung disease modifier locusThe American Journal of Human Genetics. 109(1):1-17. 21 January 2022.
  2. Sun L, Rommens JM, Corvol H, Li W, Li X, Chiang TA, Lin F, Dorfman R, Busson PF, Parekh RV, Zelenika D, Blackman SM, Corey M, Doshi VK, Henderson L, Naughton KM, O'Neal WK, Pace RG, Stonebraker JR, Wood SD, Wright FA, Zielenski J, Clement A, Drumm ML, Boëlle PY, Cutting GR, Knowles MR, Durie PR, Strug LJ.  2012. Multiple apical plasma membrane constituents are associated with susceptibility to meconium ileus in individuals with cystic fibrosis. Nat Genet. 44(5):562-9.  
  3. Panjwani N, Wang F, Mastromatteo S, Bao A, Wang C, He G, Gong J, Rommens JM, Sun L, Strug LJ. LocusFocus: Web-based colocalization for the annotation and functional follow-up of GWASPLOS Computational Biology. 16(1): e1008336. 22 October 2020.
  4. Gong J, Wang F, Xiao B, Panjwani N, Lin F, Keenan K, Avolio J, Esmaeili M, Zhang L, He G, Soave D, Mastromatteo S, Baskurt Z, Kim S, O’Neal WK, Polineni D, Blackman SM, Corvol H, Cutting GR, Drumm M, Knowles MR, Rommens JM, Sun L, Strug, LJGenetic association and transcriptome integration identifies contributing genes and tissues at cystic fibrosis modifier loci. PLOS Genetics 15(2): e1008007. February 26, 2019.
  5. Corvol, H, Blackman, SM, Boelle, PY, Gallins, PJ. Pace, RG, Stonebraker, JR, Accurso, FJ, Clement, A, Collaco, JM, Dang, H, Dang, AT, Franca, A, Gong, J, Guillot, L, Keenan, K, Li, W, Lin, F, Patrone, MV, Raraigh, KS, Sun, L, Zhou, Y, O’Neal, WK, Sontag, MK, Levy, H, Durie, PR, Rommens, JM, Drumm, ML, Wright, FA, Strug, LJ*, Cutting, GR*, Knowles, MR*.  Genome-wide association meta-analysis identifies five modifier loci of lung disease severity in cystic fibrosis. Nature Communications. 6:8382. 2015.  *Co-SRA. 

See a full list of Dr. Strug's publications on PubMed or Google Scholar.

Related pages

Strug Lab

The Strug Lab focuses on the identification of genetic modifiers in Mendelian disease such as Cystic Fibrosis, and on identifying genetic contributors to neurodevelopmental correlates of childhood onset Epilepsy.


CANSSI Ontario is the Ontario Regional Centre of the Canadian Statistical Sciences Institute.

Data Science Institute

The Data Sciences Institute (DSI) is a multi-divisional, tri-campus, multidisciplinary hub for data science activity at the University of Toronto (U of T)

Cystic Fibrosis Centre

Driving research discovery and new therapies, care, and education for cystic fibrosis to benefit children worldwide.


CGEn is a federally funded national platform for genome sequencing and analysis.

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