Dr. Jun Ding’s team at the McGill University Health Centre (RI-MUHC) has developed a groundbreaking tool, scSemiProfiler, to make single-cell sequencing—a technology that uncovers cellular details essential for personalized medicine—more affordable and accessible. Traditional single-cell sequencing, though highly informative, is costly, limiting its use in large studies. Dr. Ding’s tool, recently featured in Nature Communications, uses artificial intelligence to create single-cell profiles from less expensive bulk data, providing highly accurate insights at a fraction of the cost.
By selecting representative single-cell samples and inferring single-cell data from bulk datasets, scSemiProfiler enables researchers to investigate complex diseases at a cellular level, making it viable for broader research. The tool is available on GitHub, with plans for a cloud service to ease access for researchers without advanced computing resources. This project is funded by several grants, including those from CIHR, NSERC, and FRQS.
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RI-MUHC researchers introduce a scalable, cost-effective solution for single-cell profiling.
An innovative computational tool, scSemiProfiler, makes powerful single-cell sequencing technology more accessible for health research. RI-MUHC News. August 27, 2024.
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Wang J., Fonseca GJ. & Ding J. scSemiProfiler: Advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning. Nature Communications 15, 5989 (2024).