ReCellTy: Domain-specific knowledge graph retrieval-augmented LLMs workflow for single-cell annotation

Dezheng Han, Yibin Jia, Ruxiao Chen, Wenjie Han, Shuaishuai Guo +1 more
4/24/2025
cs.CLcs.AIcs.DB

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Abstract

To enable precise and fully automated cell type annotation with large language models (LLMs), we developed a graph structured feature marker database to retrieve entities linked to differential genes for cell reconstruction. We further designed a multi task workflow to optimize the annotation process. Compared to general purpose LLMs, our method improves human evaluation scores by up to 0.21 and semantic similarity by 6.1% across 11 tissue types, while more closely aligning with the cognitive logic of manual annotation.

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Cite this paper

@article{han2025recellty,
  title  = {ReCellTy: Domain-specific knowledge graph retrieval-augmented LLMs workflow for single-cell annotation},
  author = {Dezheng Han and Yibin Jia and Ruxiao Chen and Wenjie Han and Shuaishuai Guo and Jianbo Wang},
  year   = {2025},
  eprint = {2505.00017},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.00017v1}
}

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