scanpy.tl.sim

scanpy.tl.sim(model, *, params_file=True, tmax=None, branching=None, nrRealizations=None, noiseObs=None, noiseDyn=None, step=None, rng=None, writedir=None, seed=None)

Simulate dynamic gene expression data [Wittmann et al., 2009, Wolf et al., 2018].

Sample from a stochastic differential equation model built from literature-curated boolean gene regulatory networks, as suggested by Wittmann et al. [2009]. The Scanpy implementation can be found in Wolf et al. [2018].

Parameters:

model Literal['krumsiek11', 'toggleswitch']

Model file in ‘sim_models’ directory.

params_file bool (default: True)

Read default params from file.

tmax int | None (default: None)

Number of time steps per realization of time series.

branching bool | None (default: None)

Only write realizations that contain new branches.

nrRealizations int | None (default: None)

Number of realizations.

noiseObs float | None (default: None)

Observatory/Measurement noise.

noiseDyn float | None (default: None)

Dynamic noise.

step int | None (default: None)

Interval for saving state of system.

rng int | integer | Sequence[int] | SeedSequence | Generator | BitGenerator | None (default: None)

Random number generation to control stochasticity.

If a type:SeedLike value, it’s used to seed a new random number generator; If a numpy.random.Generator, rng’s state will be directly advanced; If None, a non-reproducible random number generator is used. See numpy.random.default_rng() for more details.

The default value matches legacy scanpy behavior and will change to None in scanpy 2.0.

writedir Path | str | None (default: None)

Path to directory for writing output files.

Return type:

AnnData

Returns:

Annotated data matrix.

Examples

See this use case