readme: ---
  license: cc-by-4.0
  library_name: scvi-tools
  tags:
  - biology
  - genomics
  - single-cell
  - model_cls_name:SCANVI
  - scvi_version:0.19.0a0
  - anndata_version:0.8.0
  - modality:rna
  - tissue:nose
  - tissue:respiratory airway
  - tissue:lung parenchyma
  - annotated:True
  ---
  
  # Description
  
  The first integrated, universal transcriptomic reference of the human lung on the single-cell level.  
  For more details, see https://github.com/LungCellAtlas/HLCA.
  
  # Model properties
  
  Many model properties are in the model tags. Some more are listed below.
  
  **model_init_params**:
  ```json
  {
      "n_hidden": 128,
      "n_latent": 30,
      "n_layers": 2,
      "dropout_rate": 0.1,
      "dispersion": "gene",
      "gene_likelihood": "nb",
      "encode_covariates": true,
      "deeply_inject_covariates": false,
      "use_layer_norm": "both",
      "use_batch_norm": "none"
  }
  ```
  
  **model_setup_anndata_args**:
  ```json
  {
      "labels_key": "scanvi_label",
      "unlabeled_category": "unlabeled",
      "layer": null,
      "batch_key": "dataset",
      "size_factor_key": null,
      "categorical_covariate_keys": null,
      "continuous_covariate_keys": null
  }
  ```
  
  **model_summary_stats**:
  |     Summary Stat Key     | Value  |
  |--------------------------|--------|
  |         n_batch          |   14   |
  |         n_cells          | 584884 |
  | n_extra_categorical_covs |   0    |
  | n_extra_continuous_covs  |   0    |
  |         n_labels         |   29   |
  |       n_latent_qzm       |   30   |
  |       n_latent_qzv       |   30   |
  |          n_vars          |  2000  |
  
  **model_data_registry**:
  |   Registry Key    |          scvi-tools Location           |
  |-------------------|----------------------------------------|
  |         X         |                adata.X                 |
  |       batch       |        adata.obs['_scvi_batch']        |
  |      labels       |       adata.obs['_scvi_labels']        |
  |    latent_qzm     |    adata.obsm['_scanvi_latent_qzm']    |
  |    latent_qzv     |    adata.obsm['_scanvi_latent_qzv']    |
  |    minify_type    |  adata.uns['_scvi_adata_minify_type']  |
  | observed_lib_size | adata.obs['_scanvi_observed_lib_size'] |
  
  **model_parent_module**: scvi.model
  
  **data_is_minified**: True
  
  # Training data
  
  This is an optional link to where the training data is stored if it is too large
  to host on the huggingface Model hub.
  
  <!-- If your model is not uploaded with any data (e.g., minified data) on the Model Hub, then make
  sure to provide this field if you want users to be able to access your training data. See the scvi-tools
  documentation for details. -->
  
  Training data url: https://cellxgene.cziscience.com/e/066943a2-fdac-4b29-b348-40cede398e4e.cxg/
  
  # Training code
  
  This is an optional link to the code used to train the model.
  
  Training code url: https://github.com/LungCellAtlas/HLCA_reproducibility
  
  # References
  
  An integrated cell atlas of the human lung in health and disease  
  L Sikkema, D Strobl, L Zappia, E Madissoon, NS Markov, L Zaragosi, M Ansari, M Arguel, L Apperloo, C Bécavin, M Berg, E Chichelnitskiy, M Chung, A Collin, ACA Gay, B Hooshiar Kashani, M Jain, T Kapellos, TM Kole, C Mayr, M von Papen, L Peter, C Ramírez-Suástegui, J Schniering, C Taylor, T Walzthoeni, C Xu, LT Bui, C de Donno, L Dony, M Guo, AJ Gutierrez, L Heumos, N Huang, I Ibarra, N Jackson, P Kadur Lakshminarasimha Murthy, M Lotfollahi, T Tabib, C Talavera-Lopez, K Travaglini, A Wilbrey-Clark, KB Worlock, M Yoshida, Lung Biological Network Consortium, T Desai, O Eickelberg, C Falk, N Kaminski, M Krasnow, R Lafyatis, M Nikolíc, J Powell, J Rajagopal, O Rozenblatt-Rosen, MA Seibold, D Sheppard, D Shepherd, SA Teichmann, A Tsankov, J Whitsett, Y Xu, NE Banovich, P Barbry, TE Duong, KB Meyer, JA Kropski, D Pe’er, HB Schiller, PR Tata, JL Schultze, AV Misharin, MC Nawijn, MD Luecken, F Theis  
  bioRxiv 2022.03.10.483747; doi: https://doi.org/10.1101/2022.03.10.483747