Project Overview
Phenonaut is a Python software package that revolutionizes multiomics data integration by providing a robust framework for processing and analyzing high-content imaging, proteomics, metabolomics, and other omics data. Our solution addresses critical challenges in data workflow management, including:
- Migration and version control of large datasets
- Quality control and preprocessing pipelines
- Integration of heterogeneous data types
- Auditability and reproducibility of analyses
Technical Implementation
Phenonaut’s workflow visualization showing data integration and analysis pipeline
Key Features
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Data Source Agnostic Integration
- Support for multiple file formats (CSV, HDF5, parquet)
- Custom data source adapters
- Automated schema validation
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Workflow Management
- Pipeline versioning
- Checkpoint saving
- Parallel processing support
- Error handling and recovery
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Analysis Capabilities
- Dimensionality reduction (PCA, t-SNE, UMAP)
- Statistical testing frameworks
- Visualization tools
- Custom analysis plugins
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Quality Control
- Automated outlier detection
- Missing value handling
- Batch effect correction
- Data normalization
Case Studies
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High-Content Imaging Integration
- Processing of 100,000+ cellular images
- Feature extraction using deep learning
- Integration with proteomics data
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Multi-omics Data Analysis
- Integration of proteomics and metabolomics
- Pathway enrichment analysis
- Network analysis
- Results: Identified novel pathway interactions
Documentation & Resources