Multi-agent AI enables evidence-based cell annotation in single-cell transcriptomics

Abstract excerpt

Cell type annotation remains a critical bottleneck, with current methods often inaccurate and requiring extensive manual validation, particularly in disease contexts. While large language models (LLMs) show promise, they can be unreliable due to hallucinations. We developed CyteType, a multi-agent framework that generates competing hypotheses grounded in full expression data and study context, validates against ex...

Topics

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• Benchmarking
• Cells
• Datasets as Topic
• Leukocytes, Mononuclear
• Logistic Models
• Machine Learning
• Models, Biological
• Phenotype

Identifiers and source

Literature Corpus work

2e541a78-40cc-5a97-aa1e-0e935bc448ff

DOI

10.1101/2025.11.06.686964