Implement real-time streaming analysis for continuous genome processing

[murr2k]

Description

Add capability to process genome data as a continuous stream, enabling real-time analysis of sequencing data as it is generated.

Use Cases

• Oxford Nanopore real-time sequencing
• Large genome analysis without full loading
• Continuous monitoring of mutations
• Live visualization during analysis
• Early detection of significant patterns

Implementation Requirements

Streaming Architecture

• Implement async stream processing
• Add buffered window analysis
• Create event-driven pipeline
• Support backpressure handling
• Implement stream multiplexing

Data Sources

• FASTQ stream reader
• Network socket support
• Named pipe integration
• Kafka/RabbitMQ connectors
• MinION direct integration

Processing Features

• Sliding window analysis
• Incremental statistics
• Progressive confidence scores
• Early termination on findings
• Adaptive window sizing

Real-time Features

• Live dashboard updates
• WebSocket notifications
• Progressive visualizations
• Alert thresholds
• Stream recording/replay

Technical Components

• Tokio async runtime
• Stream combinators
• Lock-free data structures
• Zero-copy processing
• SIMD optimizations

Performance Targets

• Latency < 100ms per window
• Throughput > 1 Mb/s
• Memory bounded by window size
• CPU utilization < 80%
• Support 10+ concurrent streams

Integration Points

• WebSocket API for live updates
• Prometheus metrics export
• Stream persistence options
• Checkpoint/resume capability
• Multi-stream coordination

Success Criteria

• Process MinION output in real-time
• Detect patterns within seconds
• Scale to multiple streams
• Maintain accuracy vs batch
• Provide meaningful live insights