Assembly Method Selection Guide

This document is under development. The following sections are planned:

Table of Contents

1. Overview of Assembly Methods
2. Decision Tree
3. Data Type Considerations
4. Quality Requirements
5. Parameter Recommendations
6. Performance Comparisons
7. Use Case Examples

Overview of Assembly Methods

Available Methods

TODO: Add detailed method descriptions

1. Intelligent Assembly - Adaptive k-mer progression with error correction
2. Qualmer Assembly - Quality-aware probabilistic assembly
3. String Graph Assembly - N-gram based approach
4. External Tool Integration - SPAdes, Megahit, etc.

Decision Tree

TODO: Add interactive decision tree

graph TD
    A[Start: What type of data?] --> B[Short reads < 500bp]
    A --> C[Long reads > 1kb]
    A --> D[Mixed/Hybrid data]
    
    B --> E[High quality Q30+?]
    B --> F[Lower quality]
    
    C --> G[Error rate < 5%?]
    C --> H[Error rate > 5%]
    
    E --> I[Use: Intelligent Assembly]
    F --> J[Use: Qualmer Assembly]
    G --> K[Use: String Graph]
    H --> L[Use: Qualmer Assembly]

Data Type Considerations

Short Read Data

TODO: Add short read recommendations

• Illumina paired-end
• Quality score requirements
• Coverage recommendations

Long Read Data

TODO: Add long read recommendations

• PacBio vs Oxford Nanopore
• Error rate handling
• Coverage depth needs

Hybrid Approaches

TODO: Add hybrid assembly guidance

• Combining short and long reads
• Quality-length trade-offs
• Polishing strategies

Quality Requirements

Quality Score Thresholds

TODO: Add quality threshold guidance

• When quality scores matter
• Minimum quality requirements
• Quality-aware vs quality-agnostic methods

Coverage Depth

TODO: Add coverage recommendations

• Minimum coverage for reliable assembly
• Optimal coverage ranges
• Over-coverage problems

Parameter Recommendations

By Data Type

TODO: Add parameter tables

Fine-Tuning

TODO: Add fine-tuning guide

• K-mer size optimization
• Memory vs accuracy trade-offs
• Error correction parameters

Performance Comparisons

Accuracy Benchmarks

TODO: Add benchmark results

• Assembly completeness
• Error rates
• Misassemblies

Runtime Comparisons

TODO: Add runtime analysis

• Speed vs accuracy trade-offs
• Memory usage patterns
• Scalability characteristics

Use Case Examples

Bacterial Genome Assembly

TODO: Add bacterial genome example

# Recommended approach for bacterial genomes
results = mycelia_assemble(
    "bacterial_reads.fastq",
    max_k=101,
    memory_limit=16_000_000_000
)

Viral Genome Assembly

TODO: Add viral genome example

Metagenome Assembly

TODO: Add metagenome example

Large Genome Assembly

TODO: Add large genome example

Troubleshooting

Common Issues

TODO: Add troubleshooting section

• Assembly fails to complete
• Poor assembly quality
• Memory/performance issues

When to Switch Methods

TODO: Add method switching guidance

• Signs that current method isn't working
• How to try alternative approaches
• Combining results from multiple methods

This guide will be expanded with specific decision criteria, benchmarking results, and detailed parameter recommendations for different use cases.