spatialvi.external.RNAStereoscope

spatialvi.external.RNAStereoscope#

class spatialvi.external.RNAStereoscope(sc_adata, **model_kwargs)[source]#

Reimplementation of Stereoscope for the scRNA-seq component [].

Trains the RNA model whose parameters are then transferred to SpatialStereoscope for spatial deconvolution.

Original implementation: almaan/stereoscope.

Parameters:
  • sc_adata (AnnData) – Single-cell AnnData registered via setup_anndata().

  • **model_kwargs – Keyword args for RNADeconv.

Examples

>>> scvi.external.RNAStereoscope.setup_anndata(sc_adata, labels_key="labels")
>>> sc_model = RNAStereoscope(sc_adata)
>>> sc_model.train()

Notes

See further usage examples in the following tutorial:

  1. /tutorials/notebooks/spatial/stereoscope_heart_LV_tutorial

__init__(sc_adata, **model_kwargs)[source]#

Methods

__init__(sc_adata, **model_kwargs)

convert_legacy_save(dir_path, output_dir_path)

Converts a legacy saved model (<v0.15.0) to the updated save format.

data_registry(registry_key)

Returns the object in AnnData associated with the key in the data registry.

deregister_manager([adata])

Deregisters the AnnDataManager instance associated with adata.

differential_abundance(*args, **kwargs)

from_spatialdata(sdata[, table_key, region])

Convenience constructor from a SpatialData object.

get_anndata_manager(adata[, required])

Retrieves the AnnDataManager for a given AnnData object.

get_from_registry(adata, registry_key)

Returns the object in AnnData associated with the key in the data registry.

get_latent_representation([adata, indices, ...])

Return latent representation with optional RAPIDS acceleration.

get_normalized_expression(*args, **kwargs)

get_setup_arg(setup_arg)

Returns the string provided to setup of a specific setup_arg.

get_state_registry(registry_key)

Returns the state registry for the AnnDataField registered with this instance.

get_var_names([legacy_mudata_format])

Variable names of input data.

load(dir_path[, adata, accelerator, device, ...])

Instantiate a model from the saved output.

load_registry(dir_path[, prefix])

Return the full registry saved with the model.

plot_spatial_embedding([adata, basis, color])

Plot latent embedding overlaid on tissue spatial coordinates.

register_manager(adata_manager)

Registers an AnnDataManager instance with this model class.

save(dir_path[, prefix, overwrite, ...])

Save the state of the model.

setup_anndata(adata[, labels_key, layer])

Sets up the AnnData object for this model.

setup_spatialdata(sdata[, table_key, region])

Register fields from a SpatialData object.

to_device(device)

Move the model to the device.

train([max_epochs, lr, accelerator, ...])

Train the model using MAP inference.

transfer_fields(adata, **kwargs)

Transfer fields from a model to an AnnData object.

update_setup_method_args(setup_method_args)

Update setup method args.

view_anndata_setup([adata, ...])

Print summary of the setup for the initial AnnData or a given AnnData object.

view_registry([hide_state_registries])

Prints summary of the registry.

view_setup_args(dir_path[, prefix])

Print args used to setup a saved model.

view_setup_method_args()

Prints setup kwargs used to produce a given registry.

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.

get_normalized_function_name

What the get normalized functions name is

history

Returns computed metrics during training.

is_trained

Whether the model has been trained.

registry

Data attached to model instance.

run_id

Returns the run id of the model.

run_name

Returns the run name of the model.

summary_string

Summary string of the model.

test_indices

Observations that are in test set.

train_indices

Observations that are in train set.

validation_indices

Observations that are in validation set.