LLM-based cell type annotation harmonization across single-cell studies using GCTHarmony
Related Experiment Video
Updated: Oct 31, 2026

Spatially Resolved, Integrated Single-Cell Multiomic Profiling of the Transcriptome and Epigenomic Targets in Frozen Tissue Sections
Published on: June 12, 2026
Xingyuan Zhang1,2, Zhicheng Ji3,4
1Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
Abstract:
A major challenge in integrating previously analyzed single-cell RNA-seq studies is the inconsistency of cell type annotations. To address this, we developed GCTHarmony, an LLM-based method for harmonizing cell type annotations across single-cell studies. Utilizing OpenAI's text embedding model, GCTHarmony accurately maps arbitrary cell type annotations to standardized cell ontology terms and reconciles discrepancies in annotation hierarchies across studies. In real data examples, we show that GCTHarmony substantially improves the consistency of cell type annotations across single-cell studies.