scanpy.tl.sim¶
-
scanpy.tl.
sim
(model, params_file=True, tmax=None, branching=None, nrRealizations=None, noiseObs=None, noiseDyn=None, step=None, seed=None, writedir=None)¶ Simulate dynamic gene expression data [Wittmann09] [Wolf17].
Sample from a stochastic differential equation model built from literature-curated boolean gene regulatory networks, as suggested by [Wittmann09]. The Scanpy implementation is due to [Wolf17].
Parameters: - model : {'krumsiek11', 'toggleswitch'}
Model file in ‘sim_models’ directory.
- params_file :
bool
, (default:True
) Read default params from file.
- tmax :
int
, optional (default:None
) Number of time steps per realization of time series.
- branching :
bool
, optional (default:None
) Only write realizations that contain new branches.
- nrRealizations : int, optional (default:
None
) Number of realizations.
- noiseObs : float, optional (default:
None
) Observatory/Measurement noise.
- noiseDyn : float, optional (default:
None
) Dynamic noise.
- step : int, optional (default:
None
) Interval for saving state of system.
- seed : int, optional (default:
None
) Seed for generation of random numbers.
- writedir : str, optional (default:
None
) Path to directory for writing output files.
Returns: adata – Annotated data matrix.
Return type: Examples
See this use case