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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

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.
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