NanoCellAnnotator: Formalizing Expert Cell Type Annotation with Large Language Models (opens in new tab)

Motivation: Cell-type annotation in spatial transcriptomics is challenging due to sparse gene panels, spatial heterogeneity, and limited availability of tissue-matched reference atlases. Recent approaches have explored large language models (LLMs) for integrating biological knowledge during annotation, but unconstrained inference can produce biologically unsupported predictions and hallucinated cell types. In addition, many LLM-based pipelines rely on large cloud-hosted models that limit repr...