NEWS
fastCNV 2.0.0
Major Improvements
Performance Optimization
- Vectorized CNV classification algorithm (O(n) complexity)
- Optimized sliding window computation with efficient matrix operations
- Improved memory management with strategic garbage collection
Code Quality
- Consistent use of
TRUE/FALSE instead of T/F
- Replaced
1:length() with seq_along() for safer iteration
- Fixed column reference in
regionToForce parameter handling
Compatibility
- Full compatibility with Seurat 4.x and 5.x
- Robust
CreateAssayObject handling across SeuratObject versions
- Fixed list subsetting (
[[]] vs []) for proper object access
Documentation
- Academic-style README with methodology description
- Comprehensive vignettes with algorithm explanations
- R-universe integration for easy installation
Bug Fixes
- Fixed
regionToForce using incorrect column name (chromosome_name → chromosome_num)
- Fixed potential dimension mismatch in
CNVCallingList
- Fixed color mapping in
plotCNVResultsHD for ComplexHeatmap
fastCNV 1.5.0
Bug Fixes
- Fixed subscript out of bounds in CNVCalling
- Fixed subscript out of bounds in CNVCallingList
- Fixed
.GetSeuratCompat() error
- Fixed
CreateAssayObject compatibility
Compatibility
- Works with Seurat 4.4.0 + SeuratObject 4.1.4
- Replaced SCTransform with standard workflow
- Added comprehensive error handling
fastCNV 1.0.0
Initial Release
- CNV inference from scRNA-seq and spatial transcriptomics data
- Sliding window-based algorithm
- Reference cell normalization
- Hierarchical clustering of CNV profiles
- Phylogenetic tree construction
- Heatmap and tree visualization
Credits
Original fastCNV developed by Gadea Cabrejas and Clarice Groeneveld.
Enhanced and maintained by Zaoqu Liu.