scvi-tools
/

tabula-sapiens-bone_marrow-condscvi

@@ -6,8 +6,8 @@ tags:
 - genomics
 - single-cell
 - model_cls_name:CondSCVI
-- scvi_version:1.2.0
-- anndata_version:0.11.1
 - modality:rna
 - tissue:various
 - annotated:True
@@ -22,7 +22,7 @@ in the spatial data.
 CondSCVI takes as input a scRNA-seq gene expression matrix with cells and genes as well as a
 cell-type annotation for all cells.
-We provide an extensive [user guide](https://docs.scvi-tools.org/en/1.2.0/user_guide/models/destvi.html)
 for DestVI including a description of CondSCVI.
 - See our original manuscript for further details of the model:
@@ -49,24 +49,14 @@ space might still be useful for analysis.
 **Cell-wise Coefficient of Variation**:
-| Metric                  | Training Value | Validation Value |
-|-------------------------|----------------|------------------|
-| Mean Absolute Error | 3.08  | 3.02           |
-| Pearson Correlation | 0.70  | 0.72  |
-| Spearman Correlation | 0.72 | 0.73  |
-| R² (R-Squared) | 0.25  | 0.28      |
 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 | 25.94   |
-| Pearson Correlation | 0.67  |
-| Spearman Correlation | 0.71 |
-| R² (R-Squared) | -54.23  |
 </details>
@@ -81,22 +71,7 @@ cell-type.
 **Differential expression**:
-| Index | gene_f1 | lfc_mae | lfc_pearson | lfc_spearman | roc_auc | pr_auc | n_cells |
-| --- | --- | --- | --- | --- | --- | --- | --- |
-| neutrophil | 0.90 | 4.02 | 0.13 | 0.39 | 0.32 | 0.87 | 2911.00 |
-| CD4-positive, alpha-beta T cell | 0.87 | 3.14 | 0.21 | 0.49 | 0.45 | 0.82 | 2025.00 |
-| monocyte | 0.84 | 2.84 | 0.22 | 0.49 | 0.44 | 0.77 | 1389.00 |
-| CD8-positive, alpha-beta T cell | 0.75 | 4.40 | 0.12 | 0.42 | 0.42 | 0.76 | 1147.00 |
-| granulocyte | 0.69 | 3.71 | 0.24 | 0.53 | 0.55 | 0.86 | 853.00 |
-| plasma cell | 0.75 | 4.56 | 0.14 | 0.26 | 0.34 | 0.88 | 825.00 |
-| erythroid progenitor cell | 0.74 | 4.12 | 0.29 | 0.61 | 0.57 | 0.91 | 757.00 |
-| mature NK T cell | 0.59 | 5.74 | 0.14 | 0.27 | 0.44 | 0.72 | 678.00 |
-| hematopoietic stem cell | 0.73 | 3.70 | 0.17 | 0.41 | 0.54 | 0.83 | 617.00 |
-| memory B cell | 0.52 | 6.95 | 0.22 | 0.20 | 0.43 | 0.72 | 310.00 |
-| common myeloid progenitor | 0.83 | 4.78 | 0.23 | 0.53 | 0.62 | 0.90 | 287.00 |
-| macrophage | 0.69 | 7.61 | 0.34 | 0.37 | 0.44 | 0.81 | 265.00 |
-| naive B cell | 0.46 | 8.94 | 0.22 | 0.16 | 0.45 | 0.73 | 142.00 |
-| erythrocyte | 0.50 | 10.99 | 0.25 | 0.13 | 0.45 | 0.93 | 87.00 |
 </details>
@@ -126,9 +101,12 @@ These provide the settings to setup the original model:
 Arguments passed to setup_anndata of the original model:
 ```json
 {
-    "labels_key": "cell_ontology_class",
-    "layer": null,
-    "batch_key": null
 }
 ```
@@ -138,10 +116,11 @@ 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          |
-|    labels    | adata.obs['_scvi_labels'] |
 - **Data is Minified**: False
@@ -150,11 +129,12 @@ Registry elements for AnnData manager:
 <details>
 <summary><strong>Summary Statistics</strong></summary>
-| Summary Stat Key | Value |
-|------------------|-------|
-|     n_cells      | 12293 |
-|     n_labels     |  14   |
-|      n_vars      | 3000  |
 </details>

 - genomics
 - single-cell
 - model_cls_name:CondSCVI
+- scvi_version:1.4.2
+- anndata_version:0.12.7
 - modality:rna
 - tissue:various
 - annotated:True
 CondSCVI takes as input a scRNA-seq gene expression matrix with cells and genes as well as a
 cell-type annotation for all cells.
+We provide an extensive [user guide](https://docs.scvi-tools.org/en/stable/user_guide/models/destvi.html)
 for DestVI including a description of CondSCVI.
 - See our original manuscript for further details of the model:
 **Cell-wise Coefficient of Variation**:
+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**:
+Not provided by uploader
 </details>
 **Differential expression**:
+Not provided by uploader
 </details>
 Arguments passed to setup_anndata of the original model:
 ```json
 {
+    "batch_key": null,
+    "labels_key": "cell_type",
+    "fine_labels_key": null,
+    "layer": "counts",
+    "unlabeled_category": "unlabeled",
+    "size_factor_key": null
 }
 ```
 <summary><strong>Data Registry</strong></summary>
 Registry elements for AnnData manager:
+| Registry Key             | scvi-tools Location                  |
+|--------------------------|--------------------------------------|
+| X                         | adata.layers['counts']               |
+| batch                     | adata.obs['_scvi_batch']             |
+| labels                    | adata.obs['_scvi_labels']            |
 - **Data is Minified**: False
 <details>
 <summary><strong>Summary Statistics</strong></summary>
+| Summary Stat Key          | Value |
+|--------------------------|-------|
+| n_batch                   | 1 |
+| n_cells                   | 27112 |
+| n_labels                  | 25 |
+| n_vars                    | 3000 |
 </details>