Robust Composite DNA Storage under Sampling Randomness, Substitution, and Insertion-Deletion Errors

TL;DR

This paper models composite DNA data storage as a multinomial channel, introducing error correction methods that improve reliability under sampling randomness, substitutions, and insertion-deletion errors, leveraging practical coding schemes.

Contribution

It presents a novel multinomial channel model for composite DNA storage and develops error correction strategies that handle sampling randomness and ID errors.

Findings

Achieves reliable data retrieval with LDPC codes under complex errors.

Extends the model to account for substitution and ID errors.

Demonstrates performance improvements over prior limited-magnitude error schemes.

Abstract

DNA data storage offers a high-density, long-term alternative to traditional storage systems, addressing the exponential growth of digital data. Composite DNA extends this paradigm by leveraging mixtures of nucleotides to increase storage capacity beyond the four standard bases. In this work, we model composite DNA storage as a multinomial channel and draw an analogy to digital modulation by representing composite letters on the three-dimensional probability simplex. To mitigate errors caused by sampling randomness, we derive transition probabilities and log-likelihood ratios (LLRs) for each constellation point and employ practical channel codes for error correction. We then extend this framework to substitution and insertion-deletion (ID) channels, proposing constellation update rules that account for these additional impairments. Numerical results demonstrate that our approach achieves reliable performance with existing LDPC codes, compared to the prior schemes designed for limited-magnitude probability errors, whose performance degrades significantly under sampling randomness.