Improved reconstruction of single-cell developmental potential with CytoTRACE 2.
Minji Kang, Gunsagar S Gulati, Erin L Brown, Zhen Qi, Susanna Avagyan, Jose Juan Almagro Armenteros, Rachel Gleyzer, Wubing Zhang, Chloé B Steen, Jeremy Philip D'Silva, Janella Schwab, Michael F Clarke, Aadel A Chaudhuri, Aaron M Newman
Abstract
Open AccessWhile 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.