cellrank.tl.kernels.ConnectivityKernel.compute_transition_matrix
- ConnectivityKernel.compute_transition_matrix(density_normalize=True)[source]
Compute transition matrix based on transcriptomic similarity.
Uses symmetric, weighted KNN graph to compute symmetric transition matrix. The connectivities are computed using
scanpy.pp.neighbors(). Depending on the parameters used there, they can be UMAP connectivities or gaussian-kernel-based connectivities with adaptive kernel width.- Parameters
density_normalize (
bool) – Whether or not to use the underlying KNN graph for density normalization.- Return type
- Returns
Self and updated
transition_matrix.