license: cc-by-4.0
library_name: scvi-tools
tags:
- biology
- genomics
- single-cell
- model_cls_name:SCANVI
- scvi_version:1.1.0
- anndata_version:0.10.3
- modality:rna
- tissue:Salivary_Gland
- annotated:True
Description
Tabula Sapiens is a benchmark, first-draft human cell atlas of nearly 500,000 cells from 24 organs of 15 normal human subjects.
Model properties
Many model properties are in the model tags. Some more are listed below.
model_init_params:
{
"n_hidden": 128,
"n_latent": 20,
"n_layers": 3,
"dropout_rate": 0.05,
"dispersion": "gene",
"gene_likelihood": "nb",
"linear_classifier": false,
"latent_distribution": "normal",
"use_batch_norm": "none",
"use_layer_norm": "both",
"encode_covariates": true
}
model_setup_anndata_args:
{
"labels_key": "cell_ontology_class",
"unlabeled_category": "unknown",
"layer": null,
"batch_key": "donor_assay",
"size_factor_key": null,
"categorical_covariate_keys": null,
"continuous_covariate_keys": null
}
model_summary_stats:
| Summary Stat Key | Value |
|---|---|
| n_batch | 4 |
| n_cells | 27199 |
| n_extra_categorical_covs | 0 |
| n_extra_continuous_covs | 0 |
| n_labels | 24 |
| n_latent_qzm | 20 |
| n_latent_qzv | 20 |
| n_vars | 4000 |
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://zenodo.org/records/7608635/files/Salivary_Gland_training_data.h5ad
Training code
This is an optional link to the code used to train the model.
Training code url: N/A
References
The Tabula Sapiens Consortium. The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans. Science, May 2022. doi:10.1126/science.abl4896