Abstract Inferring cellular trajectories using a variety of omic data is critical task in single-cell science. However, accurate prediction cell fates, and thereby biologically meaningful discovery, challenged by the sheer size data, diversity types, complexity their topologies. We present VIA, scalable trajectory inference algorithm that overcomes these limitations lazy-teleporting random walk...
