Implement advanced visualization features for trait analysis

[murr2k]

Description

Enhance visualization capabilities to provide deeper insights into pleiotropic gene detection results and trait relationships.

Current State

• Basic Plotly/Matplotlib visualizations
• Static analysis plots
• Limited interactivity

Proposed Visualizations

Interactive Gene Networks

• Force-directed trait-gene graphs
• Hierarchical trait clustering
• Gene interaction networks
• Pathway overlay visualization
• 3D network exploration

Genome Browsers

• Linear genome visualization
• Circular genome plots (Circos-style)
• Multi-track annotations
• Zoom/pan navigation
• Comparative genomics views

Statistical Dashboards

• Real-time confidence scores
• Distribution analyses
• Correlation matrices
• PCA/t-SNE projections
• Time-series analysis

Advanced Features

• AR/VR genome exploration
• GPU-accelerated rendering
• Large-scale data visualization
• Collaborative annotation
• Export to publication formats

Integration Features

• IGV.js integration
• UCSC genome browser links
• Cytoscape.js networks
• D3.js custom charts
• WebGL performance views

Technical Implementation

• React component library
• WebAssembly acceleration
• Canvas/SVG hybrid rendering
• Progressive data loading
• Responsive design

Data Visualization Types

• Heatmaps with clustering
• Sankey diagrams for trait flow
• Upset plots for overlaps
• Ridge plots for distributions
• Animation timelines

Export Capabilities

• High-resolution images
• Vector graphics (SVG/PDF)
• Interactive HTML reports
• Video animations
• 3D model exports

Success Criteria

• Intuitive user interface
• <100ms interaction response
• Handle 1M+ data points
• Publication-ready outputs
• Accessibility compliance