scvelo.tl.recover_dynamics¶
-
scvelo.tl.
recover_dynamics
(data, var_names='velocity_genes', n_top_genes=None, max_iter=10, assignment_mode='projection', t_max=None, fit_time=True, fit_scaling=True, fit_steady_states=True, fit_connected_states=None, fit_basal_transcription=None, use_raw=False, load_pars=None, return_model=None, plot_results=False, steady_state_prior=None, add_key='fit', copy=False, n_jobs=None, backend='loky', **kwargs)¶ Recovers the full splicing kinetics of specified genes.
The model infers transcription rates, splicing rates, degradation rates, as well as cell-specific latent time and transcriptional states, estimated iteratively by expectation-maximization.
- data:
AnnData
Annotated data matrix.
- var_names: str, list of str (default: ‘velocity_genes’)
Names of variables/genes to use for the fitting. If var_names=’velocity_genes’ but there is no column ‘velocity_genes’ in adata.var, velocity genes are estimated using the steady state model.
- n_top_genes: int or None (default: None)
Number of top velocity genes to use for the dynamical model.
- max_iter:int (default: 10)
Maximal iterations in the EM-Algorithm.
- assignment_mode: str (default: projection)
Determined how times are assigned to observations. If projection, observations are projected onto the model trajectory. Else uses an inverse approximating formula.
- t_max: float, False or None (default: None)
Total range for time assignments.
- fit_scaling: bool or float or None (default: True)
Whether to fit scaling between unspliced and spliced.
- fit_time: bool or float or None (default: True)
Whether to fit time or keep initially given time fixed.
- fit_steady_states: bool or None (default: True)
Whether to explicitly model and fit steady states (next to induction/repression)
- fit_connected_states: bool or None (default: None)
Restricts fitting to neighbors given by connectivities.
- fit_basal_transcription: bool or None (default: None)
Enables model to incorporate basal transcriptions.
- use_raw: bool or None (default: None)
if True, use .layers[‘sliced’], else use moments from .layers[‘Ms’]
- load_pars: bool or None (default: None)
Load parameters from past fits.
- return_model: bool or None (default: True)
Whether to return the model as :DynamicsRecovery: object.
- plot_results: bool or None (default: False)
Plot results after parameter inference.
- steady_state_prior: list of bool or None (default: None)
Mask for indices used for steady state regression.
- add_key: str (default: ‘fit’)
Key to add to parameter names, e.g. ‘fit_t’ for fitted time.
- 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
adata (AnnData) – Updated AnnData with inferred parameters added to .var if copy=True. The inferred parameters are the transcription rates fit_alpha, splicing rates fit_beta, degradation rates fit_gamma, switching times fit_t_, variance scaling factor for unspliced and spliced counts, model likelihoods fit_likelihood, and the scaling factor to align gene-wise latent times to a universal latent time fit_alignment_scaling.
- data: