cellrank.tl.estimators.CFLARE.fit

CFLARE.fit(n_lineages, keys=None, cluster_key=None, compute_absorption_probabilities=True, **kwargs)[source]

Run the pipeline, computing the initial or terminal states and optionally the absorption probabilities.

It is equivalent to running:

compute_eigendecomposition(...)
compute_terminal_states(...)
compute_absorption_probabilities(...)
Parameters
  • n_lineages (Optional[int]) – Number of lineages. If None, it will be determined automatically.

  • cluster_key (Optional[str]) – Match computed states against pre-computed clusters to annotate the states. For this, provide a key from adata .obs where cluster labels have been computed.

  • keys (Optional[Sequence[str]]) – Determines which initial or terminaltates to use by passing their names. Further, initial or terminal states can be combined. If e.g. the terminal states are [‘Neuronal_1’, ‘Neuronal_1’, ‘Astrocytes’, ‘OPC’], then passing keys=['Neuronal_1, Neuronal_2', 'OPC'] means that the two neuronal terminal states are treated as one and the ‘Astrocyte’ state is excluded.

  • **kwargs – Keyword arguments for compute_terminal_states(), such as n_cells.

Returns

Nothing, just makes available the following fields:

Return type

None