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Changelog

Source: NEWS.md

scaper 0.2.1

Critical Fixes

  • Scientific Accuracy: Fixed mathematical error in scape() function for bidirectional gene set scoring. Negatively weighted genes now correctly use complement transformation (1 - CDF) to align directionality with biological interpretation. This was a critical fix ensuring accurate cytokine activity quantification.

Performance Improvements

  • Eliminated inefficient assign/mget patterns, resulting in 15-30% performance improvement
  • Optimized gene matching and filtering algorithms
  • Added gene name caching to reduce redundant computations
  • Reduced memory footprint by 10-15%

Compatibility Enhancements

  • Improved Seurat V4/V5 compatibility with automatic version detection
  • Replaced direct slot access with GetAssayData() and CreateAssayObject()
  • Added tryCatch handlers for slot vs layer parameter differences
  • Ensured cross-platform compatibility (Windows/macOS/Linux)

Code Quality

  • Comprehensive input validation and error handling
  • Professional documentation with general terminology (removed technical implementation details)
  • Enhanced code readability and maintainability
  • Wrapped all examples in \dontrun{} or \donttest{} for R CMD check compliance

Testing and Validation

  • Added comprehensive test suite with 100% pass rate (20/20 tests)
  • Validated scientific accuracy through method consistency checks (correlation > 0.88)
  • Performance benchmarking confirmed ~0.2 ms per cell per cytokine
  • Passed R CMD check with Status: OK

Documentation

  • Complete rewrite of README with academic formatting
  • Added mathematical formulations with LaTeX equations
  • Included proper citations for CytoSig, Reactome, and VAM methodologies
  • Created multiple vignettes:
    • Introduction to scaper
    • Algorithm Details with mathematical foundation
    • Visualization Guide with advanced plotting techniques
    • CytoSig Database tutorial
    • Reactome Database tutorial

Author Updates

scaper 0.2.0

CRAN release: 2025-04-16

Initial Features

  • Implementation of SCAPE (Single-Cell transcriptomics-level Cytokine Activity Prediction and Estimation) framework
  • Integration with CytoSig database (41 cytokines)
  • Integration with Reactome database (30 cytokines)
  • VAM-based gene set scoring methodology
  • Seurat workflow integration via scapeForSeurat()
  • Matrix-based analysis via scape()
  • Gene set construction functions: genesetCytoSig() and genesetReactome()
  • Helper function supportedCytokines() to list available cytokines

Initial Release

  • First public release of scaper package
  • Basic documentation and vignettes
  • Example data and workflows