Constrained coding for error mitigation in nanopore-based DNA data storage

Area of Science:

• Biotechnology
• Bioinformatics
• Data Storage

Background:

• DNA data storage offers a high-density alternative to traditional digital storage.
• Nanopore sequencing enables real-time DNA data retrieval but suffers from lower accuracy.
• High error rates in nanopore sequencing pose a challenge for reliable DNA data storage.

Purpose of the Study:

• To develop a constrained coding system to mitigate nanopore sequencing errors.
• To improve the reliability and accuracy of data retrieval in DNA data storage systems.

Main Methods:

• Designed constrained codes utilizing de Bruijn graphs.
• Implemented a state-splitting encoder and a Viterbi-based decoder.
• Simulated data encoding and decoding, including image recovery.

Main Results:

• The novel coding system significantly reduces sequence-level errors compared to existing methods.
• Achieved up to a sixfold reduction in errors, enhancing data integrity.
• Successfully demonstrated image recovery, validating the system's effectiveness.

Conclusions:

• Constrained coding is a viable strategy to overcome nanopore sequencing limitations for DNA data storage.
• The developed system offers a substantial improvement in reliability for DNA-based digital data storage.
• This approach paves the way for more robust and practical DNA data storage solutions.