Data Sciences Institute

by Sara Elhawash

What are the key skills and qualities required for successful professionals in today’s rapidly evolving data science landscape and how do they inform training? 

To address this important question and understand the needs of organizations, the Data Sciences Institute (DSI) invited industry and non-profit leaders to the Data Science for an Effective Workforce Panel at our Research Day earlier this fall. The panel featured experts from diverse sectors, including Mark Fiume (Co-Founder & CEO, DNA Stack), Ann Meyer (Director, BioInnovation Scientist Program, adMare BioInnovations), Dana Ohab, Associate Partner (Digital & Emerging Technology, EY), and Yves Jaques (Chief, Frontier Data & Tech Unit, UNICEF).  

Engaging with data science leadership is key to our understanding of the essential skills, both soft and hard, that employers are looking for in a data-driven decision-making world. The DSI’s newly launched Data Science and Machine Learning Software Certificates have been shaped by such input from employers. 

During the panel discussions and Q&A from participants, the demands of the industry came to the forefront, with panelists providing valuable insights and a roadmap for data science professionals. It was clear that an understanding of data science and continuous learning are key for a wide range of professional fields.  

“There hasn’t been a more exciting time to be in data and data science. What we are seeing is the expectations of our clients have fundamentally changed, the world we work in today has been moving faster and is more tailored than ever seen before,” stated Dana Ohab. 

Dana also emphasized that building a community of practice and forming strategic partnerships is a blueprint many use for staying relevant in the industry. Her advice underscored the need for continuous learning and networking to remain at the forefront of data science. 

In addition to technical skills, soft skills or job-ready skills are critical. “Data science is a dynamic field that requires more than just technical skills. It’s about effective communication, adaptability, and the ability to bridge the gap between complex technical expertise and real-world business understanding. The Data Science and Machine Learning Certificates at the Data Sciences Institute aim to equip learners with these essential skills, ensuring they are not only data-savvy but also capable of making a meaningful impact in a constantly evolving landscape,” says Ann Meyer. 

Yves Jaques emphasized the value of data science in driving positive change: “We are building capacity globally to identify local solutions and talent. We take a community first response and look at the ethical implications of how data is used globally. We leverage partnerships to bring real time results.” 

Marc Fiume shared the inspirational story of his best friend, Dan, who battled cystic fibrosis due to mutations in his CFTR gene. This story served as the driving force behind DNA Stack’s mission, which aims to “save and improve the lives of people like Dan, by harnessing the collective power of the world’s genomics and health data.” 

He stressed that the future of genomic medicine would be powered by data scientists, signifying the critical role of data science in addressing these healthcare challenges. 

The panel discussion, and continuing input from data science leaders, enable the DSI to serve as a unique and enriching bridge to connect researchers with organizations in order to offer cutting-edge, in-demand training. The certificates offer an exclusive opportunity to learn from industry experts through case study components, providing invaluable insights into the professional world of data science 

To watch the video recording of the panel, click here.   

The DSI Data Science Certificate and Machine Learning Software Foundations Certificate are tailor-made for professionals with no prior technical background who aspire to excel in data science careers. In addition to technical skills courses, participants engage in job-ready skills sessions and networking opportunities to successfully enter, or further their career, in the data sciences. Both continuing education certificates offer an exclusive opportunity to learn from industry experts through case studies. The cost for each certificate is $425.  For information and to apply, click here.  

Researchers from U of T and partner hospitals collaborated with others from across Canada and around the world to identify genetic variants associated with more severe COVID-19 outcomes.

by Tyler Irving

Why do some people have a more severe course of COVID-19 disease than others? A database created by an international collaboration of researchers — including many from the University of Toronto and partner hospitals — may hold the answers to this question, and many more.

In late 2019 and early 2020, reports of a novel form of coronavirus started emerging, first from China, then from many other locations across the globe. Lisa Strug, Senior Scientist at The Hospital for Sick Children (SickKids) and Academic Director of U of T’s Data Sciences Institute, remembers what happened next.

“In my research, I use data science techniques to map the genes responsible for complex traits,” says Strug, who is a Professor in the Departments of Statistical Sciences and Computer Science in the Faculty of Arts & Science at U of T and in the Biostatistics Division of the Dalla Lana School of Public Health. She is also the Associate Director of SickKids’ Centre for Applied Genomics, which is one of three sites across Canada that form CGEn, Canada’s national platform for genome sequencing infrastructure for research.

“We knew that genes were a factor in the severity of previous SARS infections, so it made sense that COVID-19, which is caused by a closely related virus, would have a genetic component too. Very early on, I started getting messages from several scientists who wanted to set up different studies that would help us find those genes.”

Over the next few months, Strug collaborated with nearly 100 researchers from across U of T and partner hospitals and institutions, as well as other researchers from across Canada to enrol individuals with COVID-19 and sequence their genomes.

Some of the key team members from the Toronto community included:

• Stephen Scherer, Chief of Research at SickKids Research Institute and a University Professor in the Temerty Faculty of Medicine at U of T, as well as Director of the U of T McLaughlin Centre;
• Rayjean Hung, Associate Director of Population Health, Lunenfeld-Tanenbaum Research Institute and a Professor in the Dalla Lana School of Public Health at U of T;
• Angela Cheung, Clinician Scientist at University Health Network, Senior Scientist at Toronto General Hospital Research Institute, and a Professor at Temerty Medicine;
• Upton Allen, Head of the Division of Infectious Diseases at SickKids and a Professor at Temerty Medicine.

Partner hospitals and institutions included:

• The Hospital for Sick Children
• Lunenfeld-Tanenbaum Research Institute
• Mount Sinai Hospital
• St Michael’s Hospital, Unity Health Toronto
• Princess Margaret Cancer Centre
• Ontario Institute for Cancer Research
• University Health Network
• Women’s College Hospital
• Toronto General Hospital
• Baycrest Health Sciences

Together with researchers at other universities, hospitals and research institutions across Canada, the team eventually created what came to be known as CGEn HostSeq — Canadian COVID-19 Human Host Genome Sequencing Databank.

Initiated by Dr. Scherer and CGEn’s Naveed Aziz, with Dr. Strug, a $20M grant was secured from Innovation, Science and Economic Development Canada administered through Genome Canada.

Scherer recalls, “we had to go right to the top to get this project funded fast and our labs and teams worked 7 days a week on the project right through the pandemic”.

Identifying associations between individual genes and complex traits typically requires thousands of genomes, both from those with the trait and those without. Though there was no shortage of cases to choose from, it was critical to gather, sequence DNA and organize the data in a way that would be ethical, efficient and useful to researchers now and in the future.

“One of our key mandates at the Data Sciences Institute is developing techniques and programs that ensure that data remains as open, accessible and as reproduceable as it can be,” says Strug.

“That vision was brought to bear as we assembled the data infrastructure for this project: for example, ensuring that consent forms were as broad as possible, so that this data could be linked with other sources, from electronic medical records to other health databases.”

“We wanted to be sure that even after the COVID-19 pandemic was over, this could be a national whole genome sequencing resource to ask all kinds of questions about health and our genes. The development of the database and its open nature also enabled Canada to collaborate effectively with similar projects in other countries.”

In the end, the project gathered more than 11,000 full genome sequences from across Canada, representing patients with a wide range of health outcomes. Those data were then combined with even more sequences from patients in other countries under what came to be called the COVID-19 Host Genetics Initiative.

It didn’t take long for patterns to start to emerge. A paper published in Nature in 2021 identified 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19.

Since then, even more data have been added, and subsequent analysis has confirmed the significance of existing loci while also identifying new ones. The most recent update to the project, published in Nature earlier this year, brings the total number of distinct, genome-wide significant loci to 51.

“Identification of these loci can help one predict who might be more prone to a severe course of COVID-19 disease,” says Strug.

“When you identify a trait-associated locus, you can also unravel the mechanism by which this genetic region contributes to COVID-19 disease. This potentially identifies therapeutic targets and approaches that a future drug could be designed around.” 

While it will take many more years to fully untangle the effects of the different loci that have been identified, Strug says that the database is already showing its worth in other ways.

“It can be difficult to find datasets with whole genome sequence and approved for linkage with other health information that are this large, and we want people to know that it is open and available for all kinds of research, well beyond COVID, through a completely independent data access committee,” she says.

“For example, several investigators from across Canada have been approved to use these data and we’ve even provided funding to trainees to encourage them to develop new data science methodologies or ask novel health questions using the CGen HostSeq data.”

“This was a humongous effort, where researchers from across Canada came together during the COVID-19 pandemic to recruit, obtain and sequence DNA from more than 11,000 Canadians, in a systematic, cooperative, aligned way to create a made-in-Canada data resource that will hopefully be useful for years to come. I think that was really miraculous.”