scvelo.utils.get_transition_matrix¶
-
scvelo.utils.
get_transition_matrix
(adata, vkey='velocity', basis=None, backward=False, self_transitions=True, scale=10, perc=None, threshold=None, use_negative_cosines=False, weight_diffusion=0, scale_diffusion=1, weight_indirect_neighbors=None, n_neighbors=None, vgraph=None, basis_constraint=None)¶ Computes cell-to-cell transition probabilities.
\[\tilde \pi_{ij} = \frac1{z_i} \exp( \pi_{ij} / \sigma),\]from the velocity graph \(\pi_{ij}\), with row-normalization \(z_i\) and kernel width \(\sigma\) (scale parameter \(\lambda = \sigma^{-1}\)).
Alternatively, use
cellrank.tl.transition_matrix()
to account for uncertainty in the velocity estimates.- adata:
AnnData
Annotated data matrix.
- vkey: str (default: ‘velocity’)
Name of velocity estimates to be used.
- basis: str or None (default: None)
Restrict transition to embedding if specified
- backward: bool (default: False)
Whether to use the transition matrix to push forward (False) or to pull backward (True)
- self_transitions: bool (default: True)
Allow transitions from one node to itself.
- scale: float (default: 10)
Scale parameter of gaussian kernel.
- perc: float between 0 and 100 or None (default: None)
Determines threshold of transitions to include.
- use_negative_cosines: bool (default: False)
If True, negatively similar transitions are taken into account.
- weight_diffusion: float (default: 0)
Relative weight to be given to diffusion kernel (Brownian motion)
- scale_diffusion: float (default: 1)
Scale of diffusion kernel.
- weight_indirect_neighbors: float between 0 and 1 or None (default: None)
Weight to be assigned to indirect neighbors (i.e. neighbors of higher degrees).
- n_neighbors:int (default: None)
Number of nearest neighbors to consider around each cell.
- vgraph: csr matrix or None (default: None)
Velocity graph representation to use instead of adata.uns[f’{vkey}_graph’].
- Returns
Returns sparse matrix with transition probabilities.
- adata: