Fig. 1

Overview of SLICER method. a Genes to use in building a trajectory are selected by comparing sample variance and neighborhood variance. Note that this gene selection method does not require either prior knowledge of genes involved in the process or differential expression analysis of cells from multiple time points. Next, the number of nearest neighbors k to use in constructing a low-dimensional embedding is chosen so as to yield the shape that most resembles a trajectory, as measured by the a-convex hull of the cells. b SLICER builds a k-nearest neighbor graph in high-dimensional space and then performs LLE to give a nonlinear low-dimensional embedding of the cells. The low-dimensional embedding is then used to build another neighbor graph, and cells are ordered based on their shortest path distances from a user-specified starting cell. c SLICER computes geodesic entropy based on the collection of shortest paths from the starting cell and uses the geodesic entropy values to detect branches in the cellular trajectory