The WILDS WDL Library is a centralized collection of bioinformatics WDL infrastructure providing reusable, well-tested components that can be combined to create powerful computational pipelines for genomics research.
The WILDS WDL Library consolidates bioinformatics workflows into a single, well-organized repository that serves as both a collection of production-ready tools and a demonstration of WDL best practices. Rather than maintaining separate repositories for each workflow, this library promotes modularity and reusability through a three-tier architecture.
The library is organized into three complementary levels:
Tool-specific collections of reusable WDL tasks with comprehensive testing.
- Purpose: Foundational building blocks for larger workflows
- Content: Individual bioinformatics tools (STAR, BWA, GATK, etc.)
- Testing: Unit tests ensure each task functions correctly over time
- Usage: Import tasks into custom workflows or run demonstration workflows
Compact workflows demonstrating common bioinformatics patterns.
- Purpose: Educational examples of module integration
- Content: 2-3 modules combined into standard analysis patterns
- Testing: Integration tests verify modules work together seamlessly
- Usage: Templates for common workflows or learning examples
Complete, publication-ready analysis pipelines.
- Purpose: End-to-end analyses suitable for research publications
- Content: Complex workflows combining multiple modules and custom logic
- Testing: Comprehensive validation with realistic datasets
- Usage: Production analyses requiring minimal customization
# Clone the repository
git clone https://github.com/getwilds/wilds-wdl-library.git
cd wilds-wdl-library
# Run a module demonstration (update inputs json as needed)
cd modules/ww-star
miniwdl run ww-star.wdl -i inputs.json
# Run a complete vignette (update inputs json as needed)
cd ../vignettes/ww-sra-star
miniwdl run ww-sra-star.wdl -i inputs.jsonimport "https://raw.githubusercontent.com/getwilds/wilds-wdl-library/refs/heads/main/modules/ww-sra/ww-sra.wdl" as sra_tasks
import "https://raw.githubusercontent.com/getwilds/wilds-wdl-library/refs/heads/main/modules/ww-star/ww-star.wdl" as star_tasks
workflow my_analysis {
call sra_tasks.fastqdump { input: sra_id = "SRR12345678" }
call star_tasks.star_align_two_pass {
input: sample_data = { "name": "sample1", "r1": fastqdump.r1_end, "r2": fastqdump.r2_end }
}
}WILDS vignettes and workflows use GitHub URLs for imports, providing several advantages:
- No local cloning required: Use modules directly without downloading the repository
- Version control: Pin to specific commits or tags for reproducibility
- Easy updates: Switch between versions by changing the URL
- Modular usage: Import only the modules you need
| Module | Tool | Container | Description |
|---|---|---|---|
ww-annovar |
Variant Annotator | getwilds/annovar:GRCh38 |
Annotate genetic variants with ANNOVAR |
ww-annotsv |
Structural Variant Annotator | getwilds/annotsv:3.4.4 |
Annotate structural variants with AnnotSV |
ww-bcftools |
Utilities for Variant Calls | getwilds/bcftools:1.19 |
Call and analyze variants with BCFtools |
ww-bedtools |
Utilities for Genomic Intervals | getwilds/bedtools:2.31.1 |
Work with genomic intervals |
ww-bwa |
BWA Aligner | getwilds/bwa:0.7.17 |
Alignment with the Burrows-Wheeler Aligner |
ww-delly |
Structural Variant Caller | getwilds/delly:1.2.9 |
Call structural variants with Delly |
ww-gatk |
GATK Variant Calling | getwilds/gatk:4.6.1.0 |
Variant calling and processing with GATK |
ww-ichorcna |
Tumor Fraction Estimator | getwilds/ichorcna:0.2.0 |
Estimate tumor fraction with ichorCNA |
ww-manta |
Structural Variant Caller | getwilds/manta:1.6.0 |
Call structural variants with Manta |
ww-samtools |
Utilities for SAM/BAM/CRAM Files | getwilds/samtools:1.11 |
Work with Sequence Alignment/Map (SAM) format files |
ww-smoove |
Structural Variant Caller | brentp/smoove:latest |
Call structural variants with Smoove |
ww-sra |
SRA Toolkit | getwilds/sra-tools:3.1.1 |
Download sequencing data from NCBI SRA |
ww-star |
STAR Aligner | getwilds/star:2.7.6a |
RNA-seq alignment with two-pass methodology |
ww-testdata |
Test Data Downloader | getwilds/awscli:2.27.49 |
Download reference genomes and test datasets |
| Vignette | Modules | Description |
|---|---|---|
ww-sra-star |
ww-sra + ww-star |
Complete RNA-seq pipeline from SRA download to alignment |
| Workflow | Description |
|---|---|
ww-leukemia |
Consensus variant calling workflow for targeted DNA sequencing. |
All components are tested with multiple WDL executors:
- Cromwell: Production-grade workflow engine
- miniWDL: Lightweight local execution
- Sprocket: Modern WDL executor with enhanced features
Fred Hutch researchers can use PROOF to submit workflows directly to the on-premise HPC cluster. This provides a user-friendly interface for researchers unfamiliar with command-line tools while leveraging the power of the institutional computing resources.
- Continuous Integration: All components tested on every pull request
- Multi-Executor Validation: Ensures compatibility across different WDL engines
- Real Data Testing: Uses authentic bioinformatics datasets for validation
- Scheduled Monitoring: Weekly checks detect infrastructure changes
- Standardized Structure: Consistent organization across all components
- Container Management: Versioned, tested Docker images from the WILDS Docker Library
- Documentation Standards: Comprehensive README files and inline documentation
- Version Control: Semantic versioning and careful dependency management
We welcome contributions at all levels:
- Focus on high-utility bioinformatics tools
- Follow the standard module structure
- Include comprehensive tests and validation
- Provide detailed documentation
- Combine existing modules (no new tasks)
- Demonstrate common analysis patterns
- Include realistic test datasets
- Document integration approaches
- Enhance existing README files
- Add usage examples and tutorials
- Improve inline code documentation
- Contribute to the WILDS documentation site
See our Contributing Guidelines and the WILDS Contributor Guide for detailed information.
- Expanding the module collection with high-priority tools (GATK variant calling, additional alignment tools)
- Converting existing WILDS workflows to the modular architecture
- Enhancing testing infrastructure and validation
- Complete workflow tier with publication-ready pipelines
- Enhanced integration with Fred Hutch computing infrastructure
- Community-contributed modules and workflows
- Advanced documentation and tutorial content
- Issues and Bug Reports: GitHub Issues
- General Questions: Contact the Fred Hutch Data Science Lab at [email protected]
- Documentation: WILDS Guide
- Fred Hutch Users: Scientific Computing Wiki
- WILDS Docker Library: Container images used by WDL workflows
- WILDS Documentation: Comprehensive guides and best practices
- Fred Hutch SciWiki: Institutional computing resources and tutorials
Distributed under the MIT License. See LICENSE for details.
