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bioRxiv · 10.1101/2025.05.20.655112

CellReasoner: A reasoning-enhanced large language model for cell type annotation

Cao, G.·Shen, Y.·Wu, J.·Chao, H.·Chen, M.·Chen, D.
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Abstract

We present CellReasoner, a lightweight, open-source large language model (LLM) tailored for single-cell type annotation. We introduced a compact training strategy that activates the reasoning capabilities of 7B-parameter LLMs using only 380 high-quality chain-of-thought exemplars. CellReasoner directly maps cell-level gene expression profiles to cell type labels, exhibiting robust zero- and few-shot generalization. The model further demonstrates expert-level, marker-by-marker reasoning, enabling structured, interpretable annotations and offering a practical solution for intelligent single-cell analysis.

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Cao, G., Shen, Y., Wu, J., Chao, H., Chen, M., Chen, D.. 2025-05-26. CellReasoner: A reasoning-enhanced large language model for cell type annotation. https://doi.org/10.1101/2025.05.20.655112

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