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LLM-based cell type annotation harmonization across single-cell studies using GCTHarmony

delete2026-08-04
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OA
AI
X
Xingyuan Zhang
Z
Zhicheng Ji *
DOI:10.1186/s13059-026-04231-7delete
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Abstract

Abstract

En 中文
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.

Journal

G
Genome Biology
IF:
9.4
Papers:
6.3K
Citations:
7.3W

Organization

D
Department of Biostatistics and Bioinformatics
Scholars:
67
Papers: 43
Citations: 0
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