scDHMap made by ttgump is a model-based deep learning approach to visualize the complex hierarchical structures of single-cell sequencing data in a low dimensional hyperbolic space.

scDHMap can be used for various dimensionality reduction tasks including revealing trajectory branches, batch correction, and denoising highly dropout counts.