Minji Kang, Gunsagar S. Gulati, Erin L. Brown, Zhen Qi, Susanna Avagyan, José Juan Almagro Armenteros, Rachel Gleyzer, Wubing Zhang, Chloé B. Steen, Jeremy Philip D’Silva, Janella C. Schwab, Michael F. Clarke, Aadel A. Chaudhuri, Aaron M. Newman
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.