Some examples of inferred trajectories on the same dataset for different methods (Figure 1).
Figure 1: Demonstration of how a common framework for TI methods facilitates broad applicability using some example datasets. Trajectories inferred by each method were projected to a common dimensionality reduction using multi-dimensional scaling. For each dataset, we also calculated a “consensus” prediction, by calculating the cordist between each pair of models, and picking the model with the highest score on average. (a) The top methods applied on a dataset containing a linear trajectory of differentiation dendritic cells, going from MDP, CDP to PreDC. (b) The top methods applied on a dataset containing a bifurcating trajectory of reprogrammed fibroblasts. (c) A synthetic dataset generated by dyntoy, containing four disconnected trajectories. (d) A synthetic dataset generated by dyngen, containing a cyclic trajectory.