Using probabilistic methods for hierarchical visualization of single-cell RNA-seq data

This thesis investigates probabilistic methods for building hierarchical visualisations of single-cell RNA-seq data. Rather than relying on a single low-dimensional embedding, the work looks at layered structures that can reveal relationships between cell types and subpopulations. The aim is to provide interpretable overviews that remain faithful to the underlying uncertainties in the data.