scvelo.tl.velocity_graph¶
-
scvelo.tl.
velocity_graph
(data, vkey='velocity', xkey='Ms', tkey=None, basis=None, n_neighbors=None, n_recurse_neighbors=None, random_neighbors_at_max=None, sqrt_transform=None, variance_stabilization=None, gene_subset=None, compute_uncertainties=None, approx=None, mode_neighbors='distances', copy=False, n_jobs=None, backend='loky')¶ Computes velocity graph based on cosine similarities.
The cosine similarities are computed between velocities and potential cell state transitions, i.e. it measures how well a corresponding change in gene expression \(\delta_{ij} = x_j - x_i\) matches the predicted change according to the velocity vector \(\nu_i\),
\[\pi_{ij} = \cos\angle(\delta_{ij}, \nu_i) = \frac{\delta_{ij}^T \nu_i}{\left\lVert\delta_{ij}\right\rVert \left\lVert \nu_i \right\rVert}.\]- data:
AnnData
Annotated data matrix.
- vkey: str (default: ‘velocity’)
Name of velocity estimates to be used.
- xkey: str (default: ‘Ms’)
Layer key to extract count data from.
- tkey: str (default: None)
Observation key to extract time data from.
- basis: str (default: None)
Basis / Embedding to use.
- n_neighbors: int or None (default: None)
Use fixed number of neighbors or do recursive neighbor search (if None).
- n_recurse_neighbors: int (default: None)
Number of recursions for neighbors search. Defaults to 2 if mode_neighbors is ‘distances’, and 1 if mode_neighbors is ‘connectivities’.
- random_neighbors_at_max: int or None (default: None)
If number of iterative neighbors for an individual cell is higher than this threshold, a random selection of such are chosen as reference neighbors.
- sqrt_transform: bool (default: False)
Whether to variance-transform the cell states changes and velocities before computing cosine similarities.
- gene_subset: list of str, subset of adata.var_names or None`(default: `None)
Subset of genes to compute velocity graph on exclusively.
- compute_uncertainties: bool (default: None)
Whether to compute uncertainties along with cosine correlation.
- approx: bool or None (default: None)
If True, first 30 pc’s are used instead of the full count matrix
- mode_neighbors: ‘str’ (default: ‘distances’)
Determines the type of KNN graph used. Options are ‘distances’ or ‘connectivities’. The latter yields a symmetric graph.
- copy: bool (default: False)
Return a copy instead of writing to adata.
- n_jobs: int or None (default: None)
Number of parallel jobs.
- backend: str (default: “loky”)
Backend used for multiprocessing. See
joblib.Parallel
for valid options.
- Returns
velocity_graph (.uns) – sparse matrix with correlations of cell state transitions with velocities
- data: