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

Published 24 Apr 2025 in cs.CL, cs.AI, cs.DB, and cs.LG | (2505.00017v1)

Abstract: To enable precise and fully automated cell type annotation with 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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