Tools

tools.inferred_grn(vae, adata[, label, ...])	Infer the gene regulatory network (GRN) using a trained RegVelo VAE model.
tools.perturbation_effect(adata_perturb, ...)	Compute change in fate probabilities towards terminal states after perturbation.
tools.set_output(adata, vae[, n_samples, ...])	Add inference results from a trained RegVelo model to adata.
tools.in_silico_block_simulation(model, ...)	Perform an in silico transcription factor (TF) regulon knock-out by modifying the gene regulatory network (GRN) in a trained RegVelo model.
tools.in_silico_block_regulation_simulation(...)	Simulate in-silico blocking of a specific regulation between a regulator and a target gene.
tools.TFScanning_func(model, adata[, ...])	Perform in silico TF regulon knock-out screening
tools.TFscreening(adata, prior_graph[, lam, ...])	Perform repeated in silico TF regulon knock-out screening.
tools.markov_density_simulation(adata, T, ...)	Simulate transitions on a velocity-derived Markov transition matrix.
tools.simulated_visit_diff(adata, ...)	Compute difference scores and p-values for terminal states between baseline and perturbation simulations.
tools.regulation_scanning(model, adata, ...)	Perform transcription factor (TF) scanning and perturbation analysis on a gene regulatory network.