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CReSCENT: CanceR Single Cell ExpressioN Toolkit

Status: 
Active
Competition: 
2017 Bioinformatics and Computational Biology Competition
Sector: 
Health
Genome Centre(s):
Ontario Genomics
Project Leader(s):
Trevor Pugh (Princess Margaret Cancer Centre ), Michael Brudno (The Hospital for Sick Children)
Project Description: 

Tumours are complex mixtures of cancer, immune, and normal cells that interact and change during treatment. The interplay of all three types of cells can dictate development of cancer over time, as well as response or resistance to treatments. Recent advances in microfluidic and DNA sequencing technologies have enabled researchers to simultaneously analyze tens of thousands of single cells from complex tissues, including tumours. Interpreting these data is challenging, due to the lack of high-quality reference sets of each cell type in the body and a lack of methods to link these data back to tumour biology.

Drs. Trevor Pugh of the Princess Margaret Cancer Centre and Michael Brudno of The Hospital for Sick Children are developing the CanceR Single Cell ExpressioN Toolkit (CReSCENT), a scalable and standardized set of novel algorithmic methods, tools, and a data portal deployed on cloud computing infrastructure. To allow comparison of cells in cancerous and healthy tissues, the system will aggregate single-cell genomic data generated by cancer researchers and connect them to international reference data generated by experts from around the world as part of the Human Cell Atlas. This data sharing and aggregation system is a key differentiating factor in CReSCENT that will increase researcher productivity by accelerating execution and comparison of computational methods, as well as providing contextual data for understanding how cells behave within tumour tissues.

This platform, which will be useable by any researcher on any computing platform, will assemble a crucial data resource to navigate the upcoming wave of single cell cancer genomics research. CReSCENT will bring together researchers across a broad spectrum of scientific areas and disease types and increase the impact of data generated across research programs. In the long term, this system will pave the way for novel single cell diagnostics and discovery of new drug strategies for improved health care.