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SlimR 1.0.9 (2025-11-27)

• This version incorporates the T Cell Markers database PCTIT, with the data sourced from the article “Pan-cancer single cell landscape of tumor-infiltrating T cells”. The reference literature is: L. Zheng et al. (2021) doi:10.1126/science.abe6474.
• This version incorporates the Macrophage Markers database PCTAM, with the data sourced from the article “Macrophage diversity in cancer revisited in the era of single-cell omics”. The reference literature is: Ruo-Yu Ma et al. (2022) doi:10.1016/j.it.2022.04.008.
• Added a ‘has_colnames’ parameter to ‘Read_excel_markers()’ function to support reading Excel files without column headers by automatically naming the first column as “Markers”.
• Modify and optimize the README and NEWS files.

SlimR 1.0.8 (2025-10-08)

• This version adds the function of machine learning (e.g., ‘Random Forest’, ‘Gradient Boosting’, ‘Support Vector Machine’, ‘Ensemble Learning’) for cell types probability calculation parameter recognition.
• Optimize the data filter mode of “Markers_list_scIBD” in the package, and filter through sort_by = "logFC" and gene_filter = 20 parameter.
• Adjust the calculation process of the ‘FSS’ value in the read_seurat_markers() function when ‘resources’ is set to ‘presto’.
• Optimize the prompt output during the execution of the Celltype_Verification() function.
• Modify and optimize the README and NEWS files.

SlimR 1.0.7 (2025-08-19)

• Added new function Celltype_Verification() for predicted cell types validation and generated the validation dotplot.
• Optimize the function ‘Read_seurat_markers()’, which is compatible with the ‘presto::wilcoxauc()’ source tag, and the ‘Feature Significance Score’ (FSS, which is the product of log2FC and Expression ratio) can be calculated and sorted accordingly.
• Add custom color parameters colour_low and colour_high to all plotting output functions.
• Renamed Celltype_annotation_Dotplot() to Celltype_Annotation_Features(), Celltype_annotation_Box() to Celltype_Annotation_Combined(), read_seurat_markers() to Read_seurat_markers(), read_excel_markers() to Read_excel_markers() for unified function naming structure.
• Enhanced README with detailed process descriptions.
• Optimized message output system for cleaner console feedback.
• Resolved various code bugs reported by users.
• Modified codebase to meet CRAN standards and policies.

SlimR 1.0.6 (2025-08-06)

• Integrated “scIBD” human intestine reference database.
• Added AUC calculation and visualization to Celltype_Calculate().
• Implemented AUC-based prediction correction in cell typing.
• Streamlined code output formatting.
• Fixed critical bugs in the prediction pipeline.
• Modified code to meet CRAN submission requirements.

SlimR 1.0.5 (2025-08-05)

• Added “TCellSI” T-cell reference database.
• Introduced Celltype_Calculate() for automated scoring.
• Added Celltype_Annotation() for end-to-end cell typing.
• Improved message output system.
• Resolved multiple code errors.
• Modified code to meet CRAN standards and policies.

SlimR 1.0.4 (2025-07-30)

• Optimized Celltype_annotation_Heatmap() performance.
• Enhanced probability calculation in calculate_probability().
• Modified code to meet CRAN submission requirements.
• Change the License type from “GPL-3” to “MIT”.

SlimR 1.0.3 (2025-07-28)

• Replaced calculate_mean_expression() with calculate_probability() in Celltype_annotation_Heatmap().
• Modified code to meet CRAN standards and policies.

SlimR 1.0.1 (2025-07-19)

• Changed Celltype_annotation_Bar() to Celltype_annotation_Box() with improved visualization capabilities.

SlimR 1.0.0 (2025-07-07)

• Initial release of the SlimR package with the core cell type annotation framework and basic visualization functions.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.