Applying giotto-tda mapper to resolve both mature and transient pancreatic cellular states.
We aim to analyze single-cell gene expression data to visualize unipotent states, such as Ngn3+ and Fev+ populations, alongside fully differentiated islet cells (alpha, beta, and epsilon). Additionally, we propose that this approach will provide insights into the differentiation trajectories these cells undergo, all within a unified analytical framework.