All notable changes to this modified version of wf-assembly-snps are documented in this file.
- Scalable Mode: Divide-and-conquer approach for large datasets (hundreds to thousands of genomes)
- Mash-based pre-clustering for distance estimation
- Per-cluster analysis with SKA alignment and IQ-TREE2
- Global integration with backbone phylogeny
- Support for UShER incremental updates
- Recombination-Aware Mode: Enhanced analysis with Gubbins integration
- Automatic recombination detection and masking
- Improved phylogenetic accuracy for highly recombinogenic species
- Clustering-based analysis for improved scalability
- Optimized Gubbins parameters (reduced iterations: 3 vs default 5)
- Hybrid tree building approach for better performance
- Resume optimization with checksum-based caching
- Comprehensive parameter system with clear defaults
- Multiple compute environment profiles
- Flexible alignment methods (Snippy, Parsnp)
- Configurable clustering thresholds and cluster sizes
graft_trees.py: Standalone Python script for tree grafting when the main workflow fails- Robust leaf-expansion grafting algorithm using Biopython
- Detailed logging and error reporting
- Conflict resolution for tip label collisions
- Dry-run capability for testing
- Memory-efficient alternative to Nextflow-based grafting
--scalable_mode: Enable scalable clustering workflow--recombination_aware_mode: Enable recombination detection--mash_threshold: Distance threshold for clustering (default: 0.028)--max_cluster_size: Maximum genomes per cluster (default: 50)--merge_singletons: Merge singleton clusters (default: true)--mash_sketch_size: Sketch size for large datasets (default: 50,000)--gubbins_iterations: Maximum Gubbins iterations (default: 3)--integrate_results: Integrate cluster results (default: true)--build_usher_mat: Build UShER mutation tree (default: false)
- Pre-configured profiles for institutional HPC systems
- UGE (Univa Grid Engine) execution scripts
- Optimized resource allocation for different compute environments
- Comprehensive README with parameter tables and examples
- Detailed scalable mode documentation
- Usage guides for different analysis modes
- Complete parameter reference with defaults
- Modular workflow design with three distinct analysis modes
- Enhanced process organization and dependency management
- Improved error handling and logging
recombination_aware_mode:true(wasfalse)integrate_results:true(new parameter)mash_threshold:0.028(optimized for bacterial genomes)max_cluster_size:50(balanced for performance)merge_singletons:true(improved clustering)run_gubbins:true(enabled by default)
- Enhanced SNP distance calculation with cluster integration
- Improved phylogenetic tree construction workflow
- Better handling of large datasets through clustering
- Updated manifest information for modified version
- Enhanced container and environment management
- Improved reproducibility features
- Nextflow ≥22.04.3
- Support for Docker, Singularity, and Conda
- Enhanced tool integration (Mash, SKA, IQ-TREE2, Gubbins, UShER)
- Maintains backward compatibility with original workflow parameters
- Supports all original input formats and methods
- Compatible with existing compute environment configurations
This modified version builds upon the excellent foundation of the original bacterial-genomics/wf-assembly-snps workflow, adding significant enhancements for scalability and recombination-aware analysis while maintaining full compatibility with existing usage patterns.