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
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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