Man pages for SlimR
Adaptive Machine Learning-Powered, Context-Matching Tool for Single-Cell and Spatial Transcriptomics Annotation
| calculate_cluster_variability | Calculate Cluster Variability (Use in package) |
| calculate_expression | Counts average expression of gene set (Use in package) |
| calculate_expression_skewness | Calculate Expression Distribution Skewness (Use in package) |
| calculate_probability | Calculate gene set expression and infer probabilities with... |
| Cellmarker2 | Cellmarker2 dataset |
| Cellmarker2_raw | Cellmarker2 raw dataset |
| Cellmarker2_table | Cellmarker2 table |
| Celltype_Annotation | Annotate Seurat Object with SlimR Cell Type Predictions |
| Celltype_annotation_Cellmarker2 | Uses "marker_list" from Cellmarker2 for cell annotation |
| Celltype_Annotation_Combined | Uses "marker_list" to generate combined plot for cell... |
| Celltype_annotation_Excel | Uses "marker_list" from Excel input for cell annotation |
| Celltype_Annotation_Features | Annotate cell types using features plot with different marker... |
| Celltype_Annotation_Heatmap | Uses "marker_list" to generate heatmap for cell annotation |
| Celltype_annotation_PanglaoDB | Uses "marker_list" from PanglaoDB for cell annotation |
| Celltype_Annotation_PerCell | Annotate Seurat Object with Per-Cell SlimR Predictions |
| Celltype_annotation_Seurat | Uses "marker_list" from Seurat object for cell annotation |
| Celltype_Calculate | Uses "marker_list" to calculate probability, prediction... |
| Celltype_Calculate_PerCell | Per-cell annotation using marker expression and optional UMAP... |
| Celltype_Verification | Perform cell type verification and generate the validation... |
| Celltype_Verification_PerCell | Verify per-cell annotations with marker expression dotplot |
| compute_adaptive_parameters | Compute Adaptive Parameters Based on Dataset Features (Use in... |
| dot-apply_umap_smoothing | Apply UMAP-based spatial smoothing to scores |
| dot-compute_aucell_scores | Compute AUCell-like rank-based scores |
| dot-compute_weighted_scores | Compute weighted scores for per-cell annotation |
| estimate_batch_effect | Estimate Batch Effect Strength (Use in package) |
| extract_dataset_features | Extract Dataset Characteristics for Adaptive Parameter... |
| Markers_filter_Cellmarker2 | Create Marker_list from the Cellmarkers2 database |
| Markers_filter_PanglaoDB | Create Marker_list from the PanglaoDB database |
| Markers_list_PCTAM | List of Macrophage subtype markers in the article "Macrophage... |
| Markers_list_PCTIT | List of T cell subtype markers in the article "Pan-cancer... |
| Markers_list_scIBD | List of cell type markers in the article scIBD |
| Markers_list_TCellSI | List of T cell subtype markers in the article TCellSI |
| PanglaoDB | PanglaoDB dataset |
| PanglaoDB_raw | PanglaoDB raw dataset |
| PanglaoDB_table | PanglaoDB table |
| Parameter_Calculate | Adaptive Parameter Tuning for Single-Cell Data Annotation in... |
| percell_workflow | Per-Cell Annotation Workflow Example |
| plot.pheatmap | Plot Method for pheatmap Objects |
| Read_excel_markers | Create "Marker_list" from Excel files ".xlsx" |
| Read_seurat_markers | Create "Marker_list" from Seurat object |
