v1.0.0
MetaQuest v1.0.0 - First Stable Release
A Comprehensive Metagenomics Analysis Pipeline
This is the official stable release of MetaQuest - an integrated bioinformatics pipeline that addresses the complex challenges of metagenomic data analysis.
๐ Key Features
Core Analysis Capabilities
- Advanced File Validation: Comprehensive FASTQ/FASTA quality control with contamination detection and N50 metrics
- Taxonomic Classification: Species-level taxonomic profiling with diversity metrics for both FASTQ and FASTA inputs
- Pathogen Detection: Clinical-grade pathogen screening with risk assessment and comprehensive recommendations
- Machine Learning Integration: Pre-trained ML models for pathogen prediction with feature extraction and model artifacts
- Statistical Analysis: Alpha/beta diversity analysis with PERMANOVA, ANOSIM, and differential abundance testing
Analysis Workflows
- FASTQ Analysis: Rapid Kraken2/Bracken classification optimized for clinical applications
- FASTA Analysis: High-accuracy BLAST classification with ML enhancement for research applications
- Comparative Analysis: Multi-sample statistical comparison with publication-ready visualizations
๐ Statistical Testing & Machine Learning
- Alpha Diversity: Shannon, Simpson, Chao1, and Observed Species metrics with statistical testing
- Beta Diversity: Bray-Curtis dissimilarity with PCoA visualization
- Statistical Tests: PERMANOVA and ANOSIM for group comparisons
- Differential Abundance: Mann-Whitney U tests with FDR and Bonferroni correction
- ML Biomarker Discovery: Random Forest classification with cross-validation and feature importance
๐ Reporting & Visualization
- Interactive HTML dashboards with dynamic visualizations
- Alpha diversity box plots with statistical significance
- Beta diversity PCoA plots with group clustering
- Differential abundance volcano plots
- Interactive taxonomic heatmaps and abundance bar plots
- Comprehensive statistical comparison summaries
๐ Installation & Usage
Quick Installation
git clone https://github.com/your-org/metaquest.git
cd metaquest
conda env create -f environment.yml
conda activate metaquest
pip install -e .
metaquest checkBasic Usage Examples
# Validate files
metaquest validate fastq --single sample.fastq.gz
metaquest validate fasta genome.fasta
# Run analysis
metaquest analyze fastq --single sample.fastq.gz -o results/
metaquest analyze fasta genome.fasta -o results/ -s 100
# Compare samples
metaquest compare -i sample1_results/ sample2_results/ -m metadata.tsv -o comparison/๐ฌ System Requirements
- Linux/macOS operating system
- Conda package manager
- Minimum 8GB RAM (16GB recommended)
- 50GB available disk space for databases
๐ Documentation
- [Installation Guide](installation.md) - Detailed setup instructions
- [Usage Guide](usage.md) - Comprehensive usage examples and command reference
- Interactive help system:
metaquest --help
๐ฏ Target Applications
- Clinical Diagnostics: Pathogen detection and antimicrobial resistance screening
- Research Applications: Microbiome analysis and comparative genomics
- Public Health: Outbreak investigation and surveillance
- Environmental Studies: Microbial community characterization
๐ฎ Coming Soon (Future Releases)
- Virulence Factor Analysis (Q3 2025)
- Enhanced AMR Analysis (Q4 2025)
- Additional ML models and statistical methods
- Extended database support
๐ค Contributing
We welcome contributions! See our contributing guidelines for:
- Machine learning model enhancement
- Clinical validation studies
- Additional statistical methods
- Documentation improvements
๐ Support
- Bug Reports: Submit via GitHub issues
- Feature Requests: Use GitHub discussions
- Documentation: [installation.md](installation.md) and [usage.md](usage.md)
๐ Acknowledgments
MetaQuest Development Team - Advancing metagenomics through integrated computational solutions
Release Date: August 2025
Version: 1.0.0 (Stable)
License: TBD
Citation: Information will be provided upon publication
This release represents a major milestone with all core functionality complete and thoroughly tested. MetaQuest is ready for production use in both clinical and research environments.