CellRank: consistent and data view agnostic fate mapping for single-cell genomics

Key Points

• Fate mapping reveals cell trajectories in single-cell genomics, enhancing understanding of cellular differentiation processes.
• Key metrics indicate improved accuracy using CellRank's approach, enabling better predictions across varying datasets.
• Analysis employs a data view agnostic method to map cell fates from complex single-cell genomics data across multiple experiments.
• Significance lies in its potential for broad applications in developmental biology, disease modeling, and therapeutic strategies.