Description

The integrated Human Lung Cell Atlas (HLCA) represents the first large-scale, integrated single-cell reference atlas of the human lung.

Model properties

Many model properties are in the model tags. Some more are listed below.

model_init_params:

{
    "n_hidden": 128,
    "n_latent": 30,
    "n_layers": 2,
    "dropout_rate": 0.1,
    "dispersion": "gene",
    "gene_likelihood": "nb",
    "linear_classifier": false,
    "encode_covariates": true,
    "deeply_inject_covariates": false,
    "use_layer_norm": "both",
    "use_batch_norm": "none"
}

model_setup_anndata_args:

{
    "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	584944
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.

Training data url: https://cellxgene.cziscience.com/collections/6f6d381a-7701-4781-935c-db10d30de293

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

Lisa Sikkema, Ciro Ramírez-Suástegui, Daniel C. Strobl, Tessa E. Gillett, Luke Zappia, Elo Madissoon, Nikolay S. Markov, Laure-Emmanuelle Zaragosi, Yuge Ji, Meshal Ansari, Marie-Jeanne Arguel, Leonie Apperloo, Martin Banchero, Christophe Bécavin, Marijn Berg, Evgeny Chichelnitskiy, Mei-i Chung, Antoine Collin, Aurore C. A. Gay, Janine Gote-Schniering, Baharak Hooshiar Kashani, Kemal Inecik, Manu Jain, Theodore S. Kapellos, Tessa M. Kole, Sylvie Leroy, Christoph H. Mayr, Amanda J. Oliver, Michael von Papen, Lance Peter, Chase J. Taylor, Thomas Walzthoeni, Chuan Xu, Linh T. Bui, Carlo De Donno, Leander Dony, Alen Faiz, Minzhe Guo, Austin J. Gutierrez, Lukas Heumos, Ni Huang, Ignacio L. Ibarra, Nathan D. Jackson, Preetish Kadur Lakshminarasimha Murthy, Mohammad Lotfollahi, Tracy Tabib, Carlos Talavera-López, Kyle J. Travaglini, Anna Wilbrey-Clark, Kaylee B. Worlock, Masahiro Yoshida, Lung Biological Network Consortium, Maarten van den Berge, Yohan Bossé, Tushar J. Desai, Oliver Eickelberg, Naftali Kaminski, Mark A. Krasnow, Robert Lafyatis, Marko Z. Nikolic, Joseph E. Powell, Jayaraj Rajagopal, Mauricio Rojas, Orit Rozenblatt-Rosen, Max A. Seibold, Dean Sheppard, Douglas P. Shepherd, Don D. Sin, Wim Timens, Alexander M. Tsankov, Jeffrey Whitsett, Yan Xu, Nicholas E. Banovich, Pascal Barbry, Thu Elizabeth Duong, Christine S. Falk, Kerstin B. Meyer, Jonathan A. Kropski, Dana Pe’er, Herbert B. Schiller, Purushothama Rao Tata, Joachim L. Schultze, Sara A. Teichmann, Alexander V. Misharin, Martijn C. Nawijn, Malte D. Luecken, and Fabian J. Theis. Nature Medicine, June 2023. doi:10.1038/s41591-023-02327-2.