Decision-centric multi-agent orchestration with structured biological evidence improves repeated-run stability of scRNA-seq therapeutic target gene shortlists versus general agents and ablations.
CellTypeAgent: Trustworthy cell type annotation with Large Language Models
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abstract
Cell type annotation is a critical yet laborious step in single-cell RNA sequencing analysis. We present a trustworthy large language model (LLM)-agent, CellTypeAgent, which integrates LLMs with verification from relevant databases. CellTypeAgent achieves higher accuracy than existing methods while mitigating hallucinations. We evaluated CellTypeAgent across nine real datasets involving 303 cell types from 36 tissues. This combined approach holds promise for more efficient and reliable cell type annotation.
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SCTA: An Agentic Framework for Stable and Interpretable Target Gene Discovery from Single-Cell RNA Sequencing
Decision-centric multi-agent orchestration with structured biological evidence improves repeated-run stability of scRNA-seq therapeutic target gene shortlists versus general agents and ablations.