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 [Setty et al., 2019], or to downweight them [Stassen et al., 2021].

Parameters
  • adata (anndata.AnnData) – Annotated data object.

  • backward (bool) – Direction of the process.

  • time_key (str) – Key in adata .obs where the pseudotime is stored.

  • compute_cond_num (bool) – Whether to compute condition number of the transition matrix. Note that this might be costly, since it does not use sparse implementation.

  • kwargs (Any) – Keyword arguments for cellrank.tl.kernels.Kernel.

Attributes

adata

Annotated data object.

backward

Direction of the process.

condition_number

Condition number of the transition matrix.

kernels

Get the kernels of the kernel expression, except for constants.

params

Parameters which are used to compute the transition matrix.

pseudotime

Pseudotemporal ordering of cells.

transition_matrix

Return row-normalized transition matrix.

Methods

compute_projection([basis, key_added, copy])

Compute a projection of the transition matrix in the embedding.

compute_transition_matrix([…])

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.

plot_single_flow(cluster, cluster_key, time_key)

Visualize outgoing flow from a cluster of cells [Mittnenzweig et al., 2021].

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.