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CellTypeAI: Automated cell identification for scRNA-seq using local generative-AI

Series
To Immunity and Beyond
Audio Embed
A conversation with Dr Rufus Daw about CellTypeAI.

As single-cell datasets grow from thousands to hundreds of thousands of cells, accurate cell annotation is becoming a major bottleneck in biomedical research. In this episode, bioinformatician Rufus Daw discusses CellTypeAI, a new locally deployable AI framework that uses large language models to automate cell-type identification from single-cell RNA sequencing data. We explore how privacy-preserving AI tools, retrieval-augmented generation, and ensemble prompting can match or exceed conventional annotation approaches while keeping sensitive research data entirely in-house, and what this means for the future of AI-assisted immunology and systems biology.

 Further resources:

  • Rufus H. Daw,  Harry R. Deijnen, Magnus Rattray,  John R. Grainger, ‘CellTypeAI: Automated cell identification for scRNA-seq using local generative-AI’, preprinted posted on bioRxiv March 05, 2026.  https://doi.org/10.64898/2026.03.03.709253 [doi.org]
  • Rufus Daw talk: LLMs in the Laboratory: practical tools for AI-assisted research.
    https://www.youtube.com/watch?v=I7AlwgYnu9c [youtube.com]

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Creative Commons Licence
Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK (BY-NC-SA): England & Wales; https://creativecommons.org/licenses/by-nc-sa/2.0/uk/
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Episode Information

Series
To Immunity and Beyond
People
Rufus Daw
Paul Klenerman
Keywords
single-cell technologies
cell annotation
CellTypeAI
artificial intelligence
immunology
Department: Oxford Immunology Network
Date Added: 18/06/2026
Duration: 00:21:14

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