popv.algorithms.SCANVI_POPV

popv.algorithms.SCANVI_POPV#

class popv.algorithms.SCANVI_POPV(batch_key='_batch_annotation', labels_key='_labels_annotation', save_folder=None, result_key='popv_scanvi_prediction', embedding_key='X_scanvi_popv', umap_key='X_umap_scanvi_popv', model_kwargs=None, classifier_kwargs=None, embedding_kwargs=None, train_kwargs=None)[source]#

Class to compute classifier in scANVI model.

Parameters:

  • batch_key (str | None (default: '_batch_annotation')) – Key in obs field of adata for batch information. Default is “_batch_annotation”.

  • labels_key (str | None (default: '_labels_annotation')) – Key in obs field of adata for cell-type information. Default is “_labels_annotation”.

  • result_key (str | None (default: 'popv_scanvi_prediction')) – Key in obs in which celltype annotation results are stored. Default is “popv_scanvi_prediction”.

  • embedding_key (str | None (default: 'X_scanvi_popv')) – Key in obsm in which latent embedding is stored. Default is “X_scanvi_popv”.

  • umap_key (str | None (default: 'X_umap_scanvi_popv')) – Key in obsm in which UMAP embedding of integrated data is stored. Default is “X_umap_scanvi_popv”.

  • model_kwargs (dict | None (default: None)) – Dictionary to supply non-default values for SCVI model. Options at scvi.model.SCANVI.

  • classifier_kwargs (dict | None (default: None)) – Dictionary to supply non-default values for SCANVI classifier. Options at classifier_paramerers in scvi.model.SCANVI.

  • embedding_kwargs (dict | None (default: None)) – Dictionary to supply non-default values for UMAP embedding. Options at scanpy.tl.umap().

  • train_kwargs (dict | None (default: None)) – Dictionary to supply non-default values for training scvi. Options at scvi.model.SCANVI.train().

Methods table#

compute_integration(adata)

Compute scANVI model and integrate data.

compute_umap(adata)

Compute UMAP embedding of integrated data.

predict(adata)

Predict celltypes using scANVI.

Methods#

SCANVI_POPV.compute_integration(adata)[source]#

Compute scANVI model and integrate data.

Parameters:

adata – Anndata object. Results are stored in adata.obsm[self.embedding_key].

SCANVI_POPV.compute_umap(adata)[source]#

Compute UMAP embedding of integrated data.

Parameters:

adata – Anndata object. Results are stored in adata.obsm[self.umap_key].

SCANVI_POPV.predict(adata)[source]#

Predict celltypes using scANVI.

Parameters:

adata – Anndata object. Results are stored in adata.obs[self.result_key].

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