Marker-Based Package for Single-Cell and Spatial-Transcriptomic Annotation

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Documentation for package ‘SlimR’ version 1.0.7

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calculate_expression Counts average expression of gene set (Use in package)
calculate_probability Calculate gene set expression and infer probabilities with control datasets (Use in package)
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 annotation
Celltype_annotation_Excel Uses "marker_list" from Excel input for cell annotation
Celltype_Annotation_Features Annotate cell types using features plot with different marker databases
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_Seurat Uses "marker_list" from Seurat object for cell annotation
Celltype_Calculate Uses "marker_list" to calculate probability, prediction results, AUC and generate heatmap for cell annotation
Celltype_Verification Perform cell type verification and generate the validation dotplot
Markers_filter_Cellmarker2 Create Marker_list from the Cellmarkers2 database
Markers_filter_PanglaoDB Create Marker_list from the PanglaoDB database
Markers_list_scIBD List of cell type markers in the scIBD dataset
Markers_list_TCellSI List of cell type markers in the TCellSI dataset
PanglaoDB PanglaoDB dataset
PanglaoDB_raw PanglaoDB raw dataset
PanglaoDB_table PanglaoDB table
Read_excel_markers Create "Marker_list" from Excel files ".xlsx"
Read_seurat_markers Create "Marker_list" from Seurat object