Workshop 5 Background Slides

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Ancient DNA Quality Challenges

• Ancient DNA is highly fragmented and chemically modified
• Common issues: short reads, high error rates, contamination

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QC Metrics and Tools

• Read length distribution: identifies fragmentation
• GC content: checks for expected nucleotide composition
• Damage patterns: reveals ancient DNA authenticity (e.g., C→T transitions)
• Tools: Python scripts, bash, specialized packages (e.g., mapDamage)

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Integrating QC into Workflows

• Automate QC steps with Snakemake
• Modular rules for each metric
• Output tables and plots for interpretation

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Using LLMs for QC and Interpretation

• LLMs can help write and debug QC scripts
• Effective prompts describe the QC metric and expected outputs
• Always review and interpret results critically