## 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.