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Updated: Jun 29, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
Published on: January 10, 2019
Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis
1Department of Biostatistics, Columbia University Mailman School of Public Health, New York City, NY, USA. wh2526@cumc.columbia.edu.
Abstract:
Here we demonstrate that the large language model GPT-4 can accurately annotate cell types using marker gene information in single-cell RNA sequencing analysis. When evaluated across hundreds of tissue and cell types, GPT-4 generates cell type annotations exhibiting strong concordance with manual annotations. This capability can considerably reduce the effort and expertise required for cell type annotation. Additionally, we have developed an R software package GPTCelltype for GPT-4's automated cell type annotation.

