Version 1.1.2 (2026-03-12)

• New Features
  • Integrated the ScType marker database for tissue-aware cell type annotation.
  • Added Markers_filter_ScType() for filtering ScType markers by tissue type and cell name.
  • Added ScType, ScType_raw, and ScType_table data objects.

Version 1.1.1 (2026-02-05)

This release introduces a major new feature for fine-grained cell type identification alongside significant improvements to accuracy, performance, and usability.

• New Feature: Per-Cell Annotation System
  • Added a new workflow for annotating individual cells, complementing the existing cluster-based approach.
  • Offers three scoring methods: weighted (default), mean, and AUCell.
  • Includes optional UMAP-based spatial smoothing to improve annotation consistency.
• Major Improvements to Per-Cell Annotation
  • Introduced an adaptive min_score = "auto" threshold that scales with the number of cell types, preventing excessive “Unassigned” labels in large marker sets (e.g., 30+ types).
  • Added a new min_confidence parameter for ratio-based filtering, providing more robust cell type discrimination than simple score differences.
  • Enhanced the weighted scoring method with new marker specificity and IDF-like weights.
  • Improved the AUCell method with adaptive n_top calculation and a combined binary/rank-weighted scoring strategy.
  • Annotation results now include a Raw_score_matrix and a Parameters list for better reproducibility and debugging.
• Performance & Stability
  • Optimized for large datasets with vectorized operations and memory-efficient processing.
  • Integrated the RANN package for optional 10-100x faster k-NN computations in spatial smoothing.
  • Added comprehensive validation and error handling in core functions like compute_adaptive_parameters().
• Testing & Documentation
  • Added a comprehensive test suite with 147 tests covering core functionality, NA handling, and workflows.
  • Reorganized documentation and README with clearer distinctions between cluster-based and per-cell annotation.

Version 1.1.0 (2026-01-20)

• Improvements
  • Optimized AUC calculation in Celltype_Calculate() to use individual gene AUCs for more robust predictions.
  • Enhanced the adaptive machine learning algorithm in Parameter_Calculate() for better model generalization.
  • Extended Parameter_Calculate() to include threshold parameter prediction.
  • Updated general documentation and README structure.

Version 1.0.9 (2025-12-18)

• New Features
  • Integrated two new pan-cancer immune cell reference databases:
    • PCTIT: Pan-cancer T cell markers.
    • PCTAM: Pan-cancer macrophage markers.
• Improvements
  • Added a has_colnames parameter to Read_excel_markers() to support reading Excel files without column headers.
  • Updated documentation.

Version 1.0.8 (2025-10-08)

• New Features
  • Implemented machine learning-based parameter recognition using Random Forest, Gradient Boosting, SVM, and an Ensemble learner.
• Improvements
  • Optimized data filtering for the Markers_list_scIBD database.
  • Enhanced FSS (Fraction of Samples Significant) calculation in Read_seurat_markers() for outputs from the presto package.
  • Improved console output formatting in Celltype_Verification().

Version 1.0.7 (2025-08-19)

• New Features
  • Added the Celltype_Verification() function for generating validation dot plots.
  • Introduced custom color parameters (colour_low, colour_high) for all plotting functions.
• Improvements
  • Enhanced Read_seurat_markers() with better compatibility for FindMarkers results from the presto package.
  • Standardized function names across the package for consistency.
  • Improved the internal messaging system for clearer user feedback.
  • General updates for CRAN compliance.
• Bug Fixes
  • Resolved various user-reported issues.

Version 1.0.6 (2025-08-06)

• New Features
  • Integrated the scIBD human intestine cell reference database.
  • Added AUC (Area Under the Curve) calculation and visualization to the Celltype_Calculate() function.
  • Implemented AUC-based prediction correction.
• Improvements
  • Streamlined the formatting of function outputs.
  • General updates for CRAN compliance.
• Bug Fixes
  • Fixed critical bugs in the core prediction pipeline.

Version 1.0.5 (2025-08-05)

• New Features
  • Added the TCellSI T-cell reference database.
  • Introduced the Celltype_Calculate() function for automated cluster scoring.
  • Introduced the Celltype_Annotation() function for an end-to-end annotation workflow.
• Improvements
  • Enhanced the console message output system.
  • General updates for CRAN compliance.
• Bug Fixes
  • Resolved multiple code errors.

Version 1.0.4 (2025-07-30)

• Improvements
  • Optimized the performance of the Celltype_annotation_Heatmap() function.
  • Enhanced the probability calculation in the helper function calculate_probability().
  • Changed the package license from GPL-3 to MIT.
  • General updates for CRAN compliance.

Version 1.0.3 (2025-07-28)

• Improvements
  • Updated Celltype_annotation_Heatmap() to use the new calculate_probability() function.
  • General updates for CRAN compliance.

Version 1.0.1 (2025-07-19)

• Changes
  • Renamed Celltype_annotation_Bar() to Celltype_annotation_Box() and improved its visualization output.

Version 1.0.0 (2025-07-07)

• Initial release on CRAN.
• Provides the core framework for cluster-based cell type annotation and visualization.