NEWS
scPAS 1.0.4
API Compatibility
- Full compatibility with both Seurat v4 (4.0.0+) and Seurat v5 (5.0.0+)
- Added internal helper functions for version-aware API calls:
.getAssayData(): Auto-detects slot vs layer parameter.getGraphs(): Compatible graph data access.getMisc() / .setMisc(): Compatible misc slot access.createAssayObject(): Compatible assay creation
- Updated all vignettes to use Seurat-version-aware code patterns
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
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
scPAS 1.0.1
Bug Fixes
- Fixed cross-platform compatibility issues (Windows, macOS, Linux)
- Fixed DLL/SO loading on different platforms
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