
# 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**:
```json
{
    "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**:
```json
{
    "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          |   3   |
|         n_cells          | 20259 |
| n_extra_categorical_covs |   0   |
| n_extra_continuous_covs  |   0   |
|         n_labels         |  13   |
|       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.

<!-- 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://zenodo.org/records/7608635/files/Fat_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
{"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:Fat", "annotated:True"]}
scvi-tools biology genomics single-cell model_cls_name:SCANVI scvi_version:1.1.0 anndata_version:0.10.3 modality:rna tissue:Fat annotated:True license:cc-by-4.0 region:us
TAGS
#scvi-tools #biology #genomics #single-cell #model_cls_name-SCANVI #scvi_version-1.1.0 #anndata_version-0.10.3 #modality-rna #tissue-Fat #annotated-True #license-cc-by-4.0 #region-us 

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:


model\_setup\_anndata\_args:


model\_summary\_stats:



model\_data\_registry:



model\_parent\_module: URL


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: URL


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



TAGS
#scvi-tools #biology #genomics #single-cell #model_cls_name-SCANVI #scvi_version-1.1.0 #anndata_version-0.10.3 #modality-rna #tissue-Fat #annotated-True #license-cc-by-4.0 #region-us 

TAGS
#scvi-tools #biology #genomics #single-cell #model_cls_name-SCANVI #scvi_version-1.1.0 #anndata_version-0.10.3 #modality-rna #tissue-Fat #annotated-True #license-cc-by-4.0 #region-us 
