scvelo.tl.velocity_embedding

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

\[\tilde \nu_i = E_{\tilde \pi_{i\cdot}} [\tilde \delta_{i \cdot}] = \sum_{j \neq i} \left( \tilde \pi_{ij} - \frac1n \right) \tilde \delta_{ij}.\]
Parameters:

  • 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 – coordinates of velocity projection on embedding (e.g., basis=’umap’)

Return type:

.obsm