The human brain undergoes complex transitions between different states, which can be modeled as stochastic processes on graphs. By analyzing scRNA-seq data from different stages of a brain disease, we can reconstruct the underlying trajectory of cell populations and estimate the velocity of their evolution. This information can provide valuable insights into the disease mechanisms, such as identifying critical transition points and understanding the roles of specific cell types.