evolocity.tl.terminal_states

evolocity.tl.terminal_states(data, vkey='velocity', groupby=None, groups=None, self_transitions=False, eps=0.001, random_state=0, exp_scale=50, copy=False, **kwargs)

Computes terminal states (root and end points).

The end points and root nodes are obtained as stationary states of the velocity-inferred transition matrix and its transposed, respectively, which is given by left eigenvectors corresponding to an eigenvalue of 1, i.e.

\[μ^{\textrm{end}}=μ^{\textrm{end}} \pi, \quad μ^{\textrm{root}}=μ^{\textrm{root}} \pi^{\small \textrm{T}}.\]

evo.tl.terminal_states(adata)
evo.pl.scatter(adata, color=['root_nodes', 'end_points'])

Parameters

data : AnnData

Annotated data matrix.

vkey : str (default: ‘velocity’)

Name of velocity estimates to be used.

groupby : str, list or np.ndarray (default: None)

Key of observations grouping to consider. Only to be set, if each group is assumed to have a distinct lineage with an independent root and end point.

groups : str, list or np.ndarray (default: None)

Groups selected to find terminal states on. Must be an element of .obs[groupby]. To be specified only for very distinct/disconnected clusters.

self_transitions : bool (default: False)

Allow transitions from one node to itself.

eps : float (default: 1e-3)

Tolerance for eigenvalue selection.

random_state : int or None (default: 0)

Seed used by the random number generator. If None, use the RandomState instance by np.random.

copy : bool (default: False)

Return a copy instead of writing to data.

**kwargs

Passed to evolocity.tl.transition_matrix(), e.g. basis, weight_diffusion.

Returns

• Returns or updates data with the attributes

• root_nodes (.obs) – sparse matrix with transition probabilities.

• end_points (.obs) – sparse matrix with transition probabilities.