Analyzing single-cell genomics data and identifying cell types with AI
Single-cell experiments generate large datasets that are difficult to store, analyze, integrate and share. Interpreting them depends on scarce specialist analytics skills, while manual cell-type annotation can take weeks and vary between experts.
Nygen Analytics helps researchers analyze single-cell genomics data in a browser with ScarfWeb. Its CyteType tool uses AI to identify cell types and states, with marker evidence and confidence scores that help teams review and interpret their results.
What stands out about Nygen Analytics
Awarded a SEK 1 million Vinnova grant in 2025 to develop AI-driven predictive models for cancer immunotherapy.
Collaboration with VLP Therapeutics produced an August 2025 preprint on immune-cell dynamics and continues in joint research.
Co-founder Parashar Dhapola holds a Lund University PhD in Computational Biology and developed the foundations of ScarfWeb.
Accepted into SmiLe’s incubator program to support commercialization of its single-cell genomics analysis software.
Nygen reports benchmarking CyteType against cell-annotation tools across 977 clusters, 20 datasets and 16 LLMs in a November 2025 preprint.
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