Skip to main content

Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis.

Publication ,  Journal Article
Hou, W; Ji, Z
Published in: Nat Methods
August 2024

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.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Nat Methods

DOI

EISSN

1548-7105

Publication Date

August 2024

Volume

21

Issue

8

Start / End Page

1462 / 1465

Location

United States

Related Subject Headings

  • Software
  • Single-Cell Gene Expression Analysis
  • RNA-Seq
  • Molecular Sequence Annotation
  • Mice
  • Humans
  • Developmental Biology
  • Animals
  • 31 Biological sciences
  • 11 Medical and Health Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Hou, W., & Ji, Z. (2024). Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis. Nat Methods, 21(8), 1462–1465. https://doi.org/10.1038/s41592-024-02235-4
Hou, Wenpin, and Zhicheng Ji. “Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis.Nat Methods 21, no. 8 (August 2024): 1462–65. https://doi.org/10.1038/s41592-024-02235-4.
Hou W, Ji Z. Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis. Nat Methods. 2024 Aug;21(8):1462–5.
Hou, Wenpin, and Zhicheng Ji. “Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis.Nat Methods, vol. 21, no. 8, Aug. 2024, pp. 1462–65. Pubmed, doi:10.1038/s41592-024-02235-4.
Hou W, Ji Z. Assessing GPT-4 for cell type annotation in single-cell RNA-seq analysis. Nat Methods. 2024 Aug;21(8):1462–1465.

Published In

Nat Methods

DOI

EISSN

1548-7105

Publication Date

August 2024

Volume

21

Issue

8

Start / End Page

1462 / 1465

Location

United States

Related Subject Headings

  • Software
  • Single-Cell Gene Expression Analysis
  • RNA-Seq
  • Molecular Sequence Annotation
  • Mice
  • Humans
  • Developmental Biology
  • Animals
  • 31 Biological sciences
  • 11 Medical and Health Sciences