Changelog

Source: NEWS.md

scPAS 1.0.3

Bug Fixes

• Fixed p-value calculation to use proper two-tailed test (multiplied by 2)
• Improved numerical stability in sparse.cor() function with handling of zero-variance columns
• Fixed division-by-zero protection in C++ code for zero standard deviation columns
• Fixed parameter name conflict (imputation → do_imputation) to avoid collision with function name
• Fixed tag parameter handling when NULL in binomial family
• Fixed loop variable scope issues in main scPAS function

Improvements

• Added parallel computing support via n_cores parameter
• Enhanced input validation with informative error messages
• Improved sparse matrix operations in sparse_row_scale()
• Cleaned up code comments and naming conventions
• Added comprehensive test suite (57 tests)

Documentation

• New vignettes:
  • Quick Start Guide (quick-start.Rmd)
  • Algorithm and Methodology (algorithm.Rmd)
  • Visualization Gallery (visualization.Rmd)
  • Case Study: Cancer Survival Analysis (case-survival.Rmd)
  • Case Study: Binary Classification (case-binary.Rmd)
• Added pkgdown website support
• Updated README with detailed usage examples

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scPAS 1.0.2

Bug Fixes

• Fixed sparse matrix transpose issues in sparse.cor() function
• Fixed rowMeans() and colMeans() handling for sparse matrices
• Fixed FindNeighbors() rownames requirement
• Improved logical indexing to avoid which() errors with sparse matrices
• Enhanced NA handling in correlation calculations

Improvements

• Added parallel computing support for permutation tests
• Improved documentation and examples

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scPAS 1.0.1

Bug Fixes

• Fixed cross-platform compatibility issues (Windows, macOS, Linux)
• Fixed DLL/SO loading on different platforms

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scPAS 1.0.0

• Initial release
• Network-regularized sparse regression for phenotype-associated cell identification
• Support for Gaussian, binomial, and Cox regression families
• Integration with Seurat v4
• KNN and ALRA imputation methods