Changes in version 1.0.0                        

Initial Release

Features

  - Multi-objective gene selection using NSGA-II algorithm
  - Built-in objective functions:
      - compute_correlation(): Minimize pairwise correlation between
        cell types
      - compute_distance(): Maximize pairwise Euclidean distance
      - compute_condition(): Minimize condition number for stability
  - Support for custom objective functions
  - Two selection modes:
      - standard: Variable number of genes
      - fixed: Fixed number of genes
  - Flexible input formats:
      - Seurat objects (V4 and V5)
      - SingleCellExperiment objects
      - Matrix and data.frame
  - Multiple selection methods from Pareto front:
      - Weighted selection
      - Index-based selection
      - Target value proximity
  - Built-in deconvolution methods:
      - NuSVR (requires e1071 package)
      - NNLS (non-negative least squares)
      - Linear regression
  - High-performance implementation:
      - Vectorized R operations
      - Optional C++ acceleration via Rcpp/RcppArmadillo
      - Parallel computing support via future package
  - Cross-platform compatibility (Windows, macOS, Linux)
  - Comprehensive test suite
  - Detailed documentation and vignettes

Technical Details

  - R6 class-based interface for object-oriented usage
  - Caching of fitness evaluations for efficiency
  - Configurable genetic algorithm parameters
  - Progress tracking with cli package

This package implements the multi-objective gene selection methodology
for RNA-seq deconvolution.