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
SpatialStereoscopefor spatial deconvolution.Original implementation: almaan/stereoscope.
- Parameters:
sc_adata (
AnnData) – Single-cell AnnData registered viasetup_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:
/tutorials/notebooks/spatial/stereoscope_heart_LV_tutorial
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
AnnDataManagerinstance 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
AnnDataManagerfor 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
AnnDataManagerinstance with this model class.save(dir_path[, prefix, overwrite, ...])Save the state of the model.
setup_anndata(adata[, labels_key, layer])Sets up the
AnnDataobject 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
adataData attached to model instance.
adata_managerManager instance associated with self.adata.
deviceThe current device that the module's params are on.
get_normalized_function_nameWhat the get normalized functions name is
historyReturns computed metrics during training.
is_trainedWhether the model has been trained.
registryData attached to model instance.
run_idReturns the run id of the model.
run_nameReturns the run name of the model.
summary_stringSummary string of the model.
test_indicesObservations that are in test set.
train_indicesObservations that are in train set.
validation_indicesObservations that are in validation set.