Nature Methods· 2025Q1
Improved reconstruction of single-cell developmental potential with CytoTRACE 2
- 110citations
- Q1SCImago
- 2025year
Short summary
CytoTRACE 2, a deep learning framework, accurately predicts a cell's absolute developmental potential from single-cell RNA sequencing data, outperforming previous methods across diverse platforms and tissues.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces CytoTRACE 2, a deep learning framework for predicting absolute developmental potential.
- CytoTRACE 2 outperforms previous methods in predicting developmental hierarchies.
- The framework is interpretable and works across diverse single-cell RNA sequencing platforms and tissues.
- Enables detailed mapping of single-cell differentiation landscapes and cell potency.
AI-generated from the title and abstract; the full text is not read.
Abstract
While single-cell RNA sequencing has advanced our understanding of cell fate, identifying molecular hallmarks of potency-a cell's ability to differentiate into other cell types-remains a challenge. Here we introduce CytoTRACE 2, an interpretable deep learning framework for predicting absolute developmental potential from single-cell RNA sequencing data. Across diverse platforms and tissues, CytoTRACE 2 outperformed previous methods in predicting developmental hierarchies, enabling detailed mapping of single-cell differentiation landscapes and expanding insights into cell potency.
The authors' abstract, as published at the source. Nature Methods, 2025 · DOI ↗
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Field: Molecular Biology
Molecular BiologyBiochemistry, Genetics and Molecular Biology