September 3, 2020
Analyzing SARS-CoV-2: A cancer researcher trainee’s perspective
OICR-based PhD Candidate awarded University of Toronto COVID-19 Student Engagement Award
When the COVID-19 pandemic shut down labs across Canada, cancer research trainees looked for ways to help respond to the pandemic. PhD candidates Tom Ouellette and Jim Shaw saw an opportunity to combine their skills and contribute to the cause.
Ouellette and Shaw were recently awarded a University of Toronto COVID-19 Student Engagement Award for their project titled Network and evolutionary analysis of SARS-CoV-2: A vaccine perspective. Together, they will develop new machine learning tools to analyze the SARS-CoV-2 genome and how it evolves.
“We’re two like-minded individuals with complementary skillsets who enjoy coding, math and solving problems, which – fortunately – can be done remotely,” says Ouellette, who is a PhD Candidate in Dr. Philip Awadalla’s lab at OICR. “We saw the opportunity to help with COVID-19 research and we’re happy to apply our skills to help advance research towards new solutions for this pressing problem.”
Ouellette specializes in evolution and population genetics and Shaw specializes in network analysis and algorithm development. Through this award, they will investigate how SARS-CoV-2 is evolving by looking into specific regions of the virus’ genetic code from samples around the world, using mathematical modelling, machine learning, and evolutionary simulations. They are specifically interested in how these changes in the genetic code may alter the virulence, or severity, of the virus.
“Just like cancer, different pressures or stresses can make viruses evolve,” says Shaw, who is a PhD Candidate in mathematics at the University of Toronto. “Understanding these changes can have an impact on how we build vaccines. Furthermore, better understanding of the virus’ evolution may shed light on viral reinfection, which is an important issue as we move into the later stages of the pandemic.”
Ouellette and Shaw plan to publicly release the code that they develop through this initiative for other researchers to build upon.
“SARS-CoV-2 has a much simpler genome than a cancer genome, so it can serve as a simplified model to test out new analytical techniques,” says Ouellette. “Ultimately, I hope to bring the tools and technology we create back into my research on cancer so we can better understand how cancer evolves and becomes resistant to treatment.”
Read more on how OICR researchers are helping understand and overcome COVID-19
January 10, 2020
New open-source software judges accuracy of algorithms that predict tumour evolution
OICR-led international research group develops new open-source software to determine the accuracy of computational methods that can map the genetic history of tumour cells.
A cancer patient’s tumour is often made up of many cells with different genetic traits that can evolve over time. Interest in tumour evolution has grown over the last decade, giving rise to several new computational tools and algorithms that can characterize genetic diversity within a tumour, and infer patterns in how tumours evolve. However, to date there has been no standard way to compare these tools and determine which are most accurate at deciphering these data.
The genetic differences between tumour cells can tell us a lot about a patient’s disease and how it evolves over time – Adriana Salcedo
In a study recently published in Nature Biotechnology, an OICR-led international research group released new open-source software that can be used to judge the accuracy of these novel algorithms.
Continue reading – New open-source software judges accuracy of algorithms that predict tumour evolution
August 3, 2018
Open source in open science: Accelerating cancer research (Part 2)
Find part 1 here: Open source in open science: Accelerating cancer research
OICR researchers have contributed to major open source projects available to the global research community in order to accelerate cancer research. Click the link below to read about more of OICR’s open source software projects.
Continue reading – Open source in open science: Accelerating cancer research (Part 2)
August 1, 2018
Open source in open science: Accelerating cancer research (Part 1)
In the effort to bring better disease prevention and treatment to patients faster, cancer researchers are thinking more creatively about ways to conduct high-quality scientific research. Concerns about the quality, efficiency and reproducibility of research have motivated the open science movement – the growing trend of making data, methods, software and research more accessible to the greater scientific community.
Open source software (OSS), a major component of open science, enables research groups to reduce redundant efforts in software engineering by sharing software code and methods. In addition to improving efficiency, OSS promotes high-quality research by enabling collaboration, and helps make research easier to reproduce by making it more transparent.
Continue reading – Open source in open science: Accelerating cancer research (Part 1)
May 23, 2018
OICR’s Cancer Genome Collaboratory wins 2018 OpenStack Superuser award for contributions to the cancer research community
Based on popular vote and review by the Superuser Editorial Advisory Board, OICR’s Cancer Genome Collaboratory team has won the 2018 OpenStack Vancouver Summit Superuser Award. The Award recognizes OICR’s use of OpenStack, an open-source software platform for cloud computing, to enable cancer research worldwide. Previous winners of the Superuser Award include AT&T, CERN and Comcast.
“We’re proud to be recognized by the greater research community that we support,” Vincent Ferretti, Director and Senior Principal Investigator, Genome Informatics at OICR, says. “OpenStack has helped us contribute to the cancer research community in Ontario, across Canada and internationally.”
November 2, 2017
Novel approach yields four robust biomarkers for breast cancer drug response
Biomarkers that can help predict a patient’s response to a given drug are central to testing new therapies in clinical trials as well as selecting which drugs to use in the clinic. Some of the biomarkers in use today rely on the overall expression of a given gene to predict if a drug will be of benefit. While these types of biomarkers have aided cancer research and treatment, a group led by Dr. Benjamin Haibe-Kains recently published research that is ushering in a new class of biomarkers – those based on gene isoforms (the different expression of the same gene within an individual). This work opens the door to more precise biomarkers.
Continue reading – Novel approach yields four robust biomarkers for breast cancer drug response
October 4, 2017
New software uses machine learning to identify mutations in tumours without reference tissue samples
One of the main steps in analyzing cancer genomic data is to find somatic mutations, which are non-hereditary changes in DNA that may give rise to cancer. To identify these mutations, researchers will often sequence the genome of a patient’s tumour as well as the genome of their normal tissue and compare the results. But what if normal tissue samples aren’t available?
February 13, 2017
International collaboration cooks up powerful new software: MISO
Keeping track of samples and organizing their associated data is a crucial part of the research process. Like many labs around the world, those at OICR were using a commercially available Laboratory Information Management System (LIMS) to perform this task. However, the researchers using it found that this tool placed far too many constraints on their work. So what did they do? They built their own in partnership with the Earlham Institute (EI) in the U.K. This collaboration has resulted in powerful, flexible and open source software called MISO (Managing Information for Sequencing Operations).
Continue reading – International collaboration cooks up powerful new software: MISO
October 18, 2016
Reactome releases 10,000th annotated human protein, a major milestone that will benefit research community
Open source tools like Wikipedia and Google Maps help us get things done faster in our daily lives. In the same way, researchers rely on a variety of open source tools to help them make discoveries faster. Reactome (www.reactome.org) is one such tool. Researchers use it because it relates human genes, proteins and other biomolecules to the biological pathways and processes in which they participate, helping to facilitate new cancer research breakthroughs. Earlier this month Reactome reached a major milestone when it released its 10,000th annotated human protein to the research community. We spoke to OICR’s Dr. Robin Haw, who is Project Manager and Outreach Coordinator at Reactome, about the history of the project, the importance of this particular milestone and where the project is headed next.
February 12, 2016
Open source cancer research
Doing things differently: The story behind the promising chemical probe developed by OICR and the Structural Genomics Consortium
A recent collaboration between researchers at OICR and the Structural Genomics Consortium (SGC) used a new open-source approach to early stage drug discovery to develop and share without restrictions a drug-like molecule (or chemical probe) called OICR-9429 in an effort to crowd-source cancer research. OICR-9429 specifically inhibits a protein called WDR5 and can be used to investigate its function in a cell.
“Testing a new cancer treatment takes significant time and resources and unfortunately many attempts fail late in the development process. Also, most of the research activities are carried out in parallel and without enough collaboration. This leads to the duplication of a great amount of effort and raises the cost of cancer drugs that do make it to the clinic,” explains Dr. Cheryl Arrowsmith, Chief Scientist at SGC Toronto.
Continue reading – Open source cancer research
