Sequencing coverage analysis for combinatorialDNA-based storage systems

Abstract

This study introduces a novel model for analyzing and determining the required sequencing coverage in DNA-based data storage, focusing on combinatorial DNA encoding. We explore the application of the coupon collector model for combinatorial-letter reconstruction, post-sequencing, which ensure efficient data retrieval and error reduction. We use a Markov Chain model to compute the probability of error-free reconstruction. We develop theoretical bounds on the decoding probability and use empirical simulations to validate these bounds. The work contributes to the understanding of sequencing coverage in DNA-based data storage, offering insights into decoding complexity, error correction, and sequence reconstruction. We provide a Python package that takes the code design and other message parameters as input, and then computes the required read coverage to guarantee reconstruction at a given desired confidence.