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README.md

@@ -6,8 +6,8 @@ tags:
 - genomics
 - single-cell
 - model_cls_name:SCANVI
-- scvi_version:1.2.0
-- anndata_version:0.11.1
+- scvi_version:1.4.2
+- anndata_version:0.12.7
 - modality:rna
 - tissue:various
 - annotated:True
@@ -23,7 +23,7 @@ clustering.
 
 scANVI takes as input a scRNA-seq gene expression matrix with cells and genes as well as a
 cell-type annotation for a subset of cells.
-We provide an extensive [user guide](https://docs.scvi-tools.org/en/1.2.0/user_guide/models/scanvi.html).
+We provide an extensive [user guide](https://docs.scvi-tools.org/en/stable/user_guide/models/scanvi.html).
 
 - See our original manuscript for further details of the model:
 [scANVI manuscript](https://www.embopress.org/doi/full/10.15252/msb.20209620).
@@ -31,7 +31,7 @@ We provide an extensive [user guide](https://docs.scvi-tools.org/en/1.2.0/user_g
 how to leverage pre-trained models.
 
 This model can be used for fine tuning on new data using our Arches framework:
-[Arches tutorial](https://docs.scvi-tools.org/en/1.0.0/tutorials/notebooks/scarches_scvi_tools.html).
+[Arches tutorial](https://docs.scvi-tools.org/en/stable/tutorials/notebooks/scrna/scarches_scvi_tools.html).
 
 
 # Model Description
@@ -52,24 +52,14 @@ space might still be useful for analysis.
 
 **Cell-wise Coefficient of Variation**:
 
-| Metric                  | Training Value | Validation Value |
-|-------------------------|----------------|------------------|
-| Mean Absolute Error | 2.14  | 2.16           |
-| Pearson Correlation | 0.77  | 0.78  |
-| Spearman Correlation | 0.78 | 0.79  |
-| R² (R-Squared) | 0.50  | 0.55      |
+Not provided by uploader
 
 The gene-wise coefficient of variation summarizes how well variation between different genes is
 preserved by the generated model expression. This value is usually quite high.
 
 **Gene-wise Coefficient of Variation**:
 
-| Metric                  | Training Value |
-|-------------------------|----------------|
-| Mean Absolute Error | 10.85   |
-| Pearson Correlation | 0.61  |
-| Spearman Correlation | 0.62 |
-| R² (R-Squared) | -1.01  |
+Not provided by uploader
 
 </details>
 
@@ -84,21 +74,7 @@ cell-type.
 
 **Differential expression**:
 
-| Index | gene_f1 | lfc_mae | lfc_pearson | lfc_spearman | roc_auc | pr_auc | n_cells |
-| --- | --- | --- | --- | --- | --- | --- | --- |
-| fibroblast | 0.96 | 0.40 | 0.80 | 0.95 | 0.40 | 0.85 | 3014.00 |
-| endothelial cell | 0.94 | 1.25 | 0.73 | 0.96 | 0.27 | 0.89 | 2077.00 |
-| T cell | 0.91 | 2.30 | 0.67 | 0.88 | 0.35 | 0.82 | 546.00 |
-| vascular associated smooth muscle cell | 0.92 | 3.14 | 0.69 | 0.83 | 0.21 | 0.82 | 390.00 |
-| macrophage | 0.84 | 2.16 | 0.59 | 0.86 | 0.38 | 0.84 | 344.00 |
-| myometrial cell | 0.87 | 3.53 | 0.65 | 0.76 | 0.25 | 0.72 | 199.00 |
-| epithelial cell of uterus | 0.83 | 1.80 | 0.64 | 0.89 | 0.47 | 0.80 | 194.00 |
-| pericyte | 0.87 | 4.07 | 0.61 | 0.67 | 0.31 | 0.62 | 95.00 |
-| endothelial cell of lymphatic vessel | 0.76 | 3.31 | 0.59 | 0.76 | 0.53 | 0.79 | 86.00 |
-| epithelial cell | 0.66 | 2.24 | 0.63 | 0.89 | 0.58 | 0.87 | 68.00 |
-| mature NK T cell | 0.77 | 5.10 | 0.62 | 0.69 | 0.37 | 0.67 | 53.00 |
-| ciliated epithelial cell | 0.56 | 3.58 | 0.64 | 0.82 | 0.51 | 0.78 | 31.00 |
-| leukocyte | 0.49 | 4.21 | 0.66 | 0.70 | 0.46 | 0.69 | 17.00 |
+Not provided by uploader
 
 </details>
 
@@ -118,7 +94,9 @@ These provide the settings to setup the original model:
     "dropout_rate": 0.05,
     "dispersion": "gene",
     "gene_likelihood": "nb",
+    "use_observed_lib_size": true,
     "linear_classifier": false,
+    "datamodule": null,
     "latent_distribution": "normal",
     "use_batch_norm": "none",
     "use_layer_norm": "both",
@@ -134,9 +112,9 @@ These provide the settings to setup the original model:
 Arguments passed to setup_anndata of the original model:
 ```json
 {
-    "labels_key": "cell_ontology_class",
+    "labels_key": "cell_type",
     "unlabeled_category": "unknown",
-    "layer": null,
+    "layer": "counts",
     "batch_key": "donor_assay",
     "size_factor_key": null,
     "categorical_covariate_keys": null,
@@ -151,15 +129,15 @@ Arguments passed to setup_anndata of the original model:
 <summary><strong>Data Registry</strong></summary>
 
 Registry elements for AnnData manager:
-|   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['observed_lib_size']    |
+| Registry Key             | scvi-tools Location                  |
+|--------------------------|--------------------------------------|
+| X                         | adata.layers['counts']               |
+| 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['observed_lib_size']       |
 
 - **Data is Minified**: False
 
@@ -168,16 +146,16 @@ Registry elements for AnnData manager:
 <details>
 <summary><strong>Summary Statistics</strong></summary>
 
-|     Summary Stat Key     | Value |
+| Summary Stat Key          | Value |
 |--------------------------|-------|
-|         n_batch          |   2   |
-|         n_cells          | 7114  |
-| n_extra_categorical_covs |   0   |
-| n_extra_continuous_covs  |   0   |
-|         n_labels         |  14   |
-|       n_latent_qzm       |  20   |
-|       n_latent_qzv       |  20   |
-|          n_vars          | 3000  |
+| n_batch                   | 3 |
+| n_cells                   | 22029 |
+| n_extra_categorical_covs  | 0 |
+| n_extra_continuous_covs   | 0 |
+| n_labels                  | 29 |
+| n_latent_qzm              | 20 |
+| n_latent_qzv              | 20 |
+| n_vars                    | 3000 |
 
 </details>