SUMO 0.2.0

🔧 Major Enhancements

• Introduced demo_multiomics_analysis() for end-to-end demonstration of MOFA-based integrative analysis using both SUMO-generated and real-world datasets (e.g., CLL).
• Added PowerPoint reporting with automatic visualization export using officer and rvg.

🆕 New Functions

• compute_means_vars(): Computes sample- and feature-level statistics for benchmarking and noise calibration across multiple omics datasets.
• plot_weights(): Refactored with modular plotting helpers and new options for:
  • show.legend (toggle legend)
  • "integrated" mode (combined view of both omics)
  • Signal region annotation from sim_object$signal_annotation
• plot_factor(): Now supports both scatter and histogram visualization of factor scores. Includes support for plotting all factors and controlling legend display.

🎨 Visualization Improvements

• Modularized plotting into helper functions (build_scatter_plot(), build_histogram_plot()).
• Added consistent theming, Viridis color scales, and better axis labeling across plots.
• Improved annotation of signal-vs-noise regions for clarity in benchmarking.

🧪 Simulation Engine Upgrades

• Updated OmixCraftHD() to support:
  • Per-factor specification of means and variances for samples and features (e.g., signal.samples = c(3, 0.5))
  • Automatic derivation of signal masks used for evaluation and annotation
• Better error handling and defaults for edge cases (e.g., NULL factors)

🧼 Internal Cleanup

• Removed deprecated argument signal_vector
• Added globalVariables() suppressions for clean CRAN checks
• Improved code readability and consistency across plotting functions

📦 Infrastructure

• Package now includes robust examples for every major exported function
• Improved documentation headers for Roxygen2 and pkgdown compatibility