scvelo.tl.velocity¶

scvelo.tl.
velocity
(data, vkey='velocity', mode='stochastic', fit_offset=False, fit_offset2=False, filter_genes=False, groups=None, groupby=None, groups_for_fit=None, constrain_ratio=None, use_raw=False, use_latent_time=None, perc=[5, 95], min_r2=0.01, min_likelihood=0.001, r2_adjusted=None, copy=False, **kwargs)¶ Estimates velocities in a genespecific manner.
The steadystate model determines velocities by quantifying how observations deviate from a presumed steadystate equilibrium ratio of unspliced to spliced mRNA levels. This steadystate ratio is obtained by performing a linear regression restricting the input data to the extreme quantiles. By including secondorder moments, the stochastic model exploits not only the balance of of unspliced to spliced mRNA levels but also their covariation. By contrast, the likelihoodbased dynamical model solves the full splicing kinetics and generalizes RNA velocity estimation to transient systems. It is also capable of capturing nonobserved steady states.
Parameters:  data :
AnnData
Annotated data matrix.
 vkey : str (default: ‘velocity’)
Name under which to refer to the computed velocities for velocity_graph and velocity_embedding.
 mode : ‘steady_state’, ‘deterministic’, ‘stochastic’ or ‘dynamical’ (default: ‘stochastic’)
Whether to run the estimation using the deterministic or stochastic model of transcriptional dynamics. The ‘steady_state’ model is default and refers to the deterministic model. The dynamical model requires to run tl.recover_dynamics first; it is yet under development.
 fit_offset : bool (default: False)
Whether to fit with offset for first order moment dynamics.
 fit_offset2 : bool, (default: False)
Whether to fit with offset for second order moment dynamics.
 filter_genes : bool (default: True)
Whether to remove genes that are not used for further velocity analysis.
 groups : str, list (default: None)
Subset of groups, e.g. [‘g1’, ‘g2’, ‘g3’], to which velocity analysis shall be restricted.
 groupby : str, list or np.ndarray (default: None)
Key of observations grouping to consider.
 groups_for_fit : str, list or np.ndarray (default: None)
Subset of groups, e.g. [‘g1’, ‘g2’, ‘g3’], to which steadystate fitting shall be restricted.
 constrain_ratio : float or tuple of type float or None: (default: None)
Bounds for the steadystate ratio gamma’.
 use_raw : bool (default: False)
Whether to use raw data for estimation.
 use_latent_time : bool`or `None (default: `None)
Whether to use latent time as a regularization for velocity when using dynamical mode.
 perc : float (default: None)
Percentile, e.g. 98, upon for extreme quantile fit (to better capture steady states for velocity estimation).
 min_r2 : float (default: 0.01)
Minimum threshold for coefficient of determination
 min_likelihood : float (default: None)
Minimal likelihood for velocity genes to fit the model on.
 r2_adjusted : bool (default: None)
Whether to compute coefficient of determination on full data fit (adjusted) or extreme quantile fit (None)
 copy : bool (default: False)
Return a copy instead of writing to adata.
Returns:  Returns or updates adata with the attributes
 velocity (.layers) – velocity vectors for each individual cell
 variance_velocity (.layers) – velocity vectors for the cell variances
 velocity_offset, velocity_beta, velocity_gamma, velocity_r2 (.var) – parameters
 data :