cellrank.tl.kernels.PseudotimeKernel¶

class
cellrank.tl.kernels.
PseudotimeKernel
(adata, backward=False, time_key='dpt_pseudotime', compute_cond_num=False, check_connectivity=False, **kwargs)[source]¶ Kernel which computes directed transition probabilities based on a KNN graph and pseudotime.
The KNN graph contains information about the (undirected) connectivities among cells, reflecting their similarity. Pseudotime can be used to either remove edges that point against the direction of increasing pseudotime (see [Setty19], or to downweight them (see [VIA21]).
Optionally, we apply a density correction as described in [Coifman05], where we use the implementation of [Haghverdi16].
 Parameters
Attributes
Annotated data object.
Direction of the process.
Condition number of the transition matrix.
Get the kernels of the kernel expression, except for constants.
Parameters which are used to compute the transition matrix.
Pseudotemporal ordering of cells.
Return rownormalized transition matrix.
Methods
compute_projection
([basis, key_added, copy])Compute a projection of the transition matrix in the embedding.
Compute transition matrix based on KNN graph and pseudotemporal ordering.
copy
()Return a copy of self.
plot_random_walks
(n_sims[, max_iter, seed, …])Plot random walks in an embedding.
read
(fname)Deserialize self from a file.
write
(fname[, ext])Serialize self to a file.
write_to_adata
([key])Write the transition matrix and parameters used for computation to the underlying
adata
object.