scvelo.tl.VELOVI

class scvelo.tl.VELOVI(adata, n_hidden=256, n_latent=10, n_layers=1, dropout_rate=0.1, gamma_init_data=False, linear_decoder=False, **model_kwargs)

Velocity Variational Inference.

See [Gayoso et al., 2023] for details.

Parameters

adata : AnnData

AnnData object that has been registered via setup_anndata().

n_hidden : int

Number of nodes per hidden layer.

n_latent : int

Dimensionality of the latent space.

n_layers : int

Number of hidden layers used for encoder and decoder NNs.

dropout_rate : float

Dropout rate for neural networks.

gamma_init_data : bool

Initialize gamma using the data-driven technique.

linear_decoder : bool

Use a linear decoder from latent space to time.

**model_kwargs

Keyword args for VELOVAE

Attributes

adata	Data attached to model instance.
adata_manager	Manager instance associated with self.adata.
device	The current device that the module’s params are on.
history	Returns computed metrics during training.
is_trained	Whether the model has been trained.
test_indices	Observations that are in test set.
train_indices	Observations that are in train set.
validation_indices	Observations that are in validation set.

Methods

convert_legacy_save(dir_path, output_dir_path)	Converts a legacy saved model (<v0.15.0) to the updated save format.
deregister_manager([adata])	Deregisters the AnnDataManager instance associated with adata.
get_anndata_manager(adata[, required])	Retrieves the AnnDataManager for a given AnnData object specific to this model instance.
get_directional_uncertainty([adata, …])	TODO.
get_elbo([adata, indices, batch_size])	Return the ELBO for the data.
get_expression_fit([adata, indices, …])	Returns the fitted spliced and unspliced abundance (s(t) and u(t)).
get_from_registry(adata, registry_key)	Returns the object in AnnData associated with the key in the data registry.
get_gene_likelihood([adata, indices, …])	Returns the likelihood per gene.
get_latent_representation([adata, indices, …])	Return the latent representation for each cell.
get_latent_time([adata, indices, gene_list, …])	Returns the cells by genes latent time.
get_marginal_ll([adata, indices, …])	Return the marginal LL for the data.
get_permutation_scores(labels_key[, adata])	Compute permutation scores.
get_rates()	TODO.
get_reconstruction_error([adata, indices, …])	Return the reconstruction error for the data.
get_state_assignment([adata, indices, …])	Returns cells by genes by states probabilities.
get_velocity([adata, indices, gene_list, …])	Returns cells by genes velocity estimates.
load(dir_path[, adata, use_gpu, …])	Instantiate a model from the saved output.
load_registry(dir_path[, prefix])	Return the full registry saved with the model.
register_manager(adata_manager)	Registers an AnnDataManager instance with this model class.
save(dir_path[, prefix, overwrite, save_anndata])	Save the state of the model.
setup_anndata(adata, spliced_layer, …)	Sets up the AnnData object for this model.
to_device(device)	Move model to device.
train([max_epochs, lr, weight_decay, …])	Train the model.
view_anndata_setup([adata, …])	Print summary of the setup for the initial AnnData or a given AnnData object.
view_setup_args(dir_path[, prefix])	Print args used to setup a saved model.