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@@ -6,8 +6,8 @@ tags:
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  - genomics
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  - single-cell
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  - model_cls_name:CondSCVI
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- - scvi_version:1.2.0
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- - anndata_version:0.11.1
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  - modality:rna
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  - tissue:various
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  - annotated:True
@@ -22,7 +22,7 @@ in the spatial data.
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  CondSCVI takes as input a scRNA-seq gene expression matrix with cells and genes as well as a
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  cell-type annotation for all cells.
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- We provide an extensive [user guide](https://docs.scvi-tools.org/en/1.2.0/user_guide/models/destvi.html)
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  for DestVI including a description of CondSCVI.
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  - See our original manuscript for further details of the model:
@@ -49,24 +49,14 @@ space might still be useful for analysis.
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  **Cell-wise Coefficient of Variation**:
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- | Metric | Training Value | Validation Value |
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- |-------------------------|----------------|------------------|
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- | Mean Absolute Error | 3.04 | 3.03 |
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- | Pearson Correlation | 0.49 | 0.48 |
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- | Spearman Correlation | 0.49 | 0.49 |
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- | R² (R-Squared) | -0.91 | -0.89 |
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  The gene-wise coefficient of variation summarizes how well variation between different genes is
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  preserved by the generated model expression. This value is usually quite high.
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  **Gene-wise Coefficient of Variation**:
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- | Metric | Training Value |
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- |-------------------------|----------------|
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- | Mean Absolute Error | 27.66 |
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- | Pearson Correlation | 0.66 |
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- | Spearman Correlation | 0.69 |
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- | R² (R-Squared) | -1.90 |
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  </details>
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@@ -81,23 +71,7 @@ cell-type.
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  **Differential expression**:
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- | Index | gene_f1 | lfc_mae | lfc_pearson | lfc_spearman | roc_auc | pr_auc | n_cells |
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- | --- | --- | --- | --- | --- | --- | --- | --- |
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- | fibroblast | 0.92 | 1.50 | 0.56 | 0.87 | 0.35 | 0.90 | 5557.00 |
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- | macrophage | 0.88 | 1.45 | 0.50 | 0.85 | 0.33 | 0.89 | 5338.00 |
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- | bladder urothelial cell | 0.92 | 1.53 | 0.59 | 0.90 | 0.45 | 0.92 | 4151.00 |
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- | T cell | 0.81 | 2.59 | 0.58 | 0.77 | 0.28 | 0.87 | 2916.00 |
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- | myofibroblast cell | 0.82 | 2.44 | 0.50 | 0.76 | 0.37 | 0.84 | 2078.00 |
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- | plasma cell | 0.83 | 3.00 | 0.49 | 0.71 | 0.22 | 0.88 | 1141.00 |
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- | mast cell | 0.91 | 3.37 | 0.51 | 0.64 | 0.28 | 0.82 | 1029.00 |
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- | pericyte | 0.92 | 2.71 | 0.63 | 0.75 | 0.32 | 0.79 | 875.00 |
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- | mature NK T cell | 0.70 | 4.05 | 0.51 | 0.69 | 0.47 | 0.88 | 508.00 |
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- | smooth muscle cell | 0.91 | 4.15 | 0.58 | 0.67 | 0.34 | 0.84 | 290.00 |
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- | vein endothelial cell | 0.81 | 3.68 | 0.59 | 0.69 | 0.41 | 0.80 | 278.00 |
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- | B cell | 0.63 | 4.44 | 0.52 | 0.56 | 0.38 | 0.75 | 253.00 |
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- | capillary endothelial cell | 0.75 | 3.69 | 0.67 | 0.69 | 0.41 | 0.75 | 77.00 |
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- | endothelial cell of lymphatic vessel | 0.63 | 5.32 | 0.55 | 0.54 | 0.34 | 0.71 | 74.00 |
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- | plasmacytoid dendritic cell | 0.37 | 6.60 | 0.45 | 0.38 | 0.35 | 0.73 | 18.00 |
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  </details>
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@@ -127,9 +101,12 @@ These provide the settings to setup the original model:
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  Arguments passed to setup_anndata of the original model:
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  ```json
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  {
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- "labels_key": "cell_ontology_class",
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- "layer": null,
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- "batch_key": null
 
 
 
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  }
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  ```
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@@ -139,10 +116,11 @@ Arguments passed to setup_anndata of the original model:
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  <summary><strong>Data Registry</strong></summary>
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  Registry elements for AnnData manager:
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- | Registry Key | scvi-tools Location |
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- |--------------|---------------------------|
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- | X | adata.X |
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- | labels | adata.obs['_scvi_labels'] |
 
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  - **Data is Minified**: False
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@@ -151,11 +129,12 @@ Registry elements for AnnData manager:
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  <details>
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  <summary><strong>Summary Statistics</strong></summary>
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- | Summary Stat Key | Value |
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- |------------------|-------|
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- | n_cells | 24583 |
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- | n_labels | 15 |
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- | n_vars | 3000 |
 
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  </details>
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6
  - genomics
7
  - single-cell
8
  - model_cls_name:CondSCVI
9
+ - scvi_version:1.4.2
10
+ - anndata_version:0.12.7
11
  - modality:rna
12
  - tissue:various
13
  - annotated:True
 
22
 
23
  CondSCVI takes as input a scRNA-seq gene expression matrix with cells and genes as well as a
24
  cell-type annotation for all cells.
25
+ We provide an extensive [user guide](https://docs.scvi-tools.org/en/stable/user_guide/models/destvi.html)
26
  for DestVI including a description of CondSCVI.
27
 
28
  - See our original manuscript for further details of the model:
 
49
 
50
  **Cell-wise Coefficient of Variation**:
51
 
52
+ Not provided by uploader
 
 
 
 
 
53
 
54
  The gene-wise coefficient of variation summarizes how well variation between different genes is
55
  preserved by the generated model expression. This value is usually quite high.
56
 
57
  **Gene-wise Coefficient of Variation**:
58
 
59
+ Not provided by uploader
 
 
 
 
 
60
 
61
  </details>
62
 
 
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  **Differential expression**:
73
 
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+ Not provided by uploader
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
75
 
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  </details>
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101
  Arguments passed to setup_anndata of the original model:
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  ```json
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  {
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+ "batch_key": null,
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+ "labels_key": "cell_type",
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+ "fine_labels_key": null,
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+ "layer": "counts",
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+ "unlabeled_category": "unlabeled",
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+ "size_factor_key": null
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  }
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  ```
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  <summary><strong>Data Registry</strong></summary>
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  Registry elements for AnnData manager:
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+ | Registry Key | scvi-tools Location |
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+ |--------------------------|--------------------------------------|
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+ | X | adata.layers['counts'] |
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+ | batch | adata.obs['_scvi_batch'] |
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+ | labels | adata.obs['_scvi_labels'] |
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  - **Data is Minified**: False
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  <details>
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  <summary><strong>Summary Statistics</strong></summary>
131
 
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+ | Summary Stat Key | Value |
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+ |--------------------------|-------|
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+ | n_batch | 1 |
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+ | n_cells | 66385 |
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+ | n_labels | 22 |
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+ | n_vars | 3000 |
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  </details>
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