Inferring TF activation order in time series scRNA-Seq studies
Fig 1
CSHMM-TF model structure and parameters.
The figure presents the assignments of cells and TFs to the reconstructed branching model for the process studies. Each edge (path) represents a set of infinite states parameterized by the path number and the location along the path. We use a function based on parameters learned for the split nodes (nodes at the start and end of each path) and TF assignments to define an emission probability. Emission probability for a gene along a path is a function of the location of the state and prior TFs (t and tstart) and a gene specific parameter k which controls the rate of change of its expression along the path. Split nodes are locations where paths split and are associated with a branch (transition) probability. The t_start parameter defines the TF activation time for a specific TF associated with the path. Cell assignment to paths is determined by the emission probabilities and the expression of specific TF targets for the TFs associated with the path. w is a vector of gene-specific mixture weight, where the weights are a non linear function which depends on (t and tstart). See text for more details.