River is an interpretable deep learning framework designed to identify genes with differential spatial expression patterns (DSEP) across multiple conditions. It utilizes a two-branch architecture and attribution methods to outperform existing tools in scalability and accuracy.

References:

• Cui Y, Yuan Z. Prioritizing perturbation-responsive gene patterns using interpretable deep learning[J]. Nature Communications, 2025, 16(1): 6095.