scvelo.tl.velocity_embedding¶
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scvelo.tl.
velocity_embedding
(data, basis=None, vkey='velocity', scale=10, self_transitions=True, use_negative_cosines=True, direct_pca_projection=None, retain_scale=False, autoscale=True, all_comps=True, T=None, copy=False)¶ Projects the single cell velocities into any embedding.
Given normalized difference of the embedding positions
\[\tilde \delta_{ij} = \frac{x_j-x_i}{\left\lVert x_j-x_i \right\rVert},\]the projections are obtained as expected displacements with respect to the transition matrix \(\tilde \pi_{ij}\) as
\[\tilde \nu_i = E_{\tilde \pi_{i\cdot}} [\tilde \delta_{i \cdot}] = \sum_{j \neq i} \left( \tilde \pi_{ij} - \frac1n \right) \tilde \delta_{ij}.\]- data:
AnnData
Annotated data matrix.
- basis: str (default: ‘tsne’)
Which embedding to use.
- vkey: str (default: ‘velocity’)
Name of velocity estimates to be used.
- scale: int (default: 10)
Scale parameter of gaussian kernel for transition matrix.
- self_transitions: bool (default: True)
Whether to allow self transitions, based on the confidences of transitioning to neighboring cells.
- use_negative_cosines: bool (default: True)
Whether to project cell-to-cell transitions with negative cosines into negative/opposite direction.
- direct_pca_projection: bool (default: None)
Whether to directly project the velocities into PCA space, thus skipping the velocity graph.
- retain_scale: bool (default: False)
Whether to retain scale from high dimensional space in embedding.
- autoscale: bool (default: True)
Whether to scale the embedded velocities by a scalar multiplier, which simply ensures that the arrows in the embedding are properly scaled.
- all_comps: bool (default: True)
Whether to compute the velocities on all embedding components.
- T: csr_matrix (default: None)
Allows the user to directly pass a transition matrix.
- copy: bool (default: False)
Return a copy instead of writing to adata.
- Returns
velocity_umap (.obsm) – coordinates of velocity projection on embedding (e.g., basis=’umap’)
- data: