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README.md
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---
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license: cc-by-4.0
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library_name: scvi-tools
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tags:
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- biology
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- genomics
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- single-cell
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- model_cls_name:SCANVI
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- scvi_version:1.0.0
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- anndata_version:0.9.1
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- modality:rna
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- annotated:True
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---
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# Description
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Mouse scANVI reference model
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# Model properties
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Many model properties are in the model tags. Some more are listed below.
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**model_init_params**:
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```json
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{
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"n_hidden": 128,
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"n_latent": 10,
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"n_layers": 2,
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"dropout_rate": 0.1,
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"dispersion": "gene",
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"gene_likelihood": "nb",
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"linear_classifier": false,
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"latent_distribution": "normal"
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}
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```
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**model_setup_anndata_args**:
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```json
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{
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"labels_key": "ct",
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"unlabeled_category": "Unknown",
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"layer": "counts",
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"batch_key": "batch",
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"size_factor_key": null,
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"categorical_covariate_keys": null,
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"continuous_covariate_keys": null
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}
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```
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**model_summary_stats**:
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|[1m [0m[1m Summary Stat Key [0m[1m [0m|[1m [0m[1mValue[0m[1m [0m|
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|--------------------------|-------|
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|[94m [0m[94m n_batch [0m[94m [0m|[35m [0m[35m 18 [0m[35m [0m|
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|[94m [0m[94m n_cells [0m[94m [0m|[35m [0m[35m2004 [0m[35m [0m|
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|[94m [0m[94mn_extra_categorical_covs[0m[94m [0m|[35m [0m[35m 0 [0m[35m [0m|
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|[94m [0m[94mn_extra_continuous_covs [0m[94m [0m|[35m [0m[35m 0 [0m[35m [0m|
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|[94m [0m[94m n_labels [0m[94m [0m|[35m [0m[35m 16 [0m[35m [0m|
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|[94m [0m[94m n_vars [0m[94m [0m|[35m [0m[35m3000 [0m[35m [0m|
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**model_data_registry**:
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|[1m [0m[1mRegistry Key[0m[1m [0m|[1m [0m[1m scvi-tools Location [0m[1m [0m|
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|--------------|---------------------------|
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|[94m [0m[94m X [0m[94m [0m|[35m [0m[35m adata.layers['counts'] [0m[35m [0m|
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|[94m [0m[94m batch [0m[94m [0m|[35m [0m[35madata.obs['_scvi_batch'] [0m[35m [0m|
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|[94m [0m[94m labels [0m[94m [0m|[35m [0m[35madata.obs['_scvi_labels'][0m[35m [0m|
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**model_parent_module**: https://zenodo.org/records/10669600/files/01_mouse_reprocessed.h5ad?download=1
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**data_is_minified**: False
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# Training data
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This is an optional link to where the training data is stored if it is too large
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to host on the huggingface Model hub.
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<!-- If your model is not uploaded with any data (e.g., minified data) on the Model Hub, then make
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sure to provide this field if you want users to be able to access your training data. See the scvi-tools
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documentation for details. -->
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Training data url: https://github.com/brickmanlab/proks-salehin-et-al
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# Training code
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This is an optional link to the code used to train the model.
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Training code url: N/A
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# References
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Proks, Salehin et al., biorXiv
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