Study of the error correction capability of multiple sequence alignment algorithm (MAFFT) in DNA storage.

Area of Science:

• Bioinformatics
• Data Storage
• Computational Biology

Background:

• Synchronization errors, specifically insertions and deletions, pose significant challenges for reliable information retrieval in DNA data storage.
• Traditional error correction codes (ECC) rely on adding redundancy, which can be inefficient for DNA storage systems.

Purpose of the Study:

• To comprehensively evaluate the error correction capability of a typical multiple sequence alignment (MSA) algorithm, MAFFT, for DNA storage.
• To understand the performance of MSA in relation to error rates and sequencing depth.

Main Methods:

• Conducted a comprehensive simulation study using the MAFFT algorithm, a common MSA tool.
• Analyzed the error correction performance under varying error percentages and sequencing depths.

Main Results:

• MSA performance exhibits a phase transition around 20% error rate; below this, increasing sequencing depth improves recovery.
• With sequencing depth up to 70, MSA achieves complete recovery in low error regimes and corrects up to 90% of errors in medium error regimes.
• MSA demonstrates robustness to imperfect clustering and can be combined with ECC or other coding constraints.

Conclusions:

• Multiple sequence alignment (MSA) presents a competitive strategy for error correction in DNA data storage, offering an alternative to traditional ECC.
• Optimizing sequencing depth allows for a balance between cost and reading speed, making MSA a practical solution.
• The robustness and combinability of MSA with other methods enhance its potential for future DNA storage applications.