Mapping single-cell developmental potential in health and disease with interpretable deep learning.

Area of Science:

• Developmental Biology
• Genomics
• Computational Biology

Background:

• Single-cell RNA sequencing (scRNA-seq) has revolutionized developmental biology, but quantifying cellular potency remains difficult.
• Identifying molecular markers of cell potency is crucial for understanding cell fate and differentiation.
• Existing methods struggle to accurately capture the full spectrum of cellular potency.

Conclusions:

• CytoTRACE 2 provides a broadly applicable platform for delineating single-cell differentiation landscapes.
• Illuminates a fundamental feature of cell biology related to potency and differentiation.
• Offers new insights into cellular phenotypes in cancer, impacting survival and treatment resistance.