Improved read/write cost tradeoff in DNA-based data storage using LDPC codes

Abstract

With the amount of data being stored increasing rapidly, there is significant interest in exploring alternative storage technologies. In this context, DNA-based storage systems can offer significantly higher storage densities (petabytes/gram) and durability (thousands of years) than current technologies. Specifically, DNA has been found to be stable over extended periods of time which has been demonstrated in the analysis of organisms long since extinct. Recent advances in DNA sequencing and synthesis pipelines have made DNA-based storage a promising candidate for the storage technology of the future.Recently, there have been multiple efforts in this direction, focusing on aspects such as error correction for synthesis/sequencing errors and erasure correction for handling missing sequences. The typical approach is to use separate codes for handling errors and erasures, but there is limited understanding of the efficiency of this framework. Furthermore, the existing techniques use short block-length codes and heavily rely on read consensus, both of which are known to be suboptimal in coding theory.In this work, we study the tradeoff between the writing and reading costs involved in DNA-based storage and propose a practical scheme to achieve an improved tradeoff between these quantities. Our scheme breaks with the traditional separation framework and instead uses a single large block-length LDPC code for both erasure and error correction. We also introduce novel techniques to handle insertion and deletion errors introduced by the synthesis process. For a range of writing costs, the proposed scheme achieves 30-40% lower reading costs than state-of-the-art techniques on experimental data obtained using array synthesis and Illumina sequencing.

Processing DNA Storage through Programmable Assembly in a Droplet‐Based Fluidics System

“…DNA information storage through hybridization and enzymatic reactions in the DCF can serve as a multi-bit DNA storage system [37,38] and as digital DNA molecular data storage. [39]…”

“…In digital DNA data storage, primer sequences are pre-defined information and can access DNA data in pools through PCR. Additionally, the primer address sequences, used for programmable data connections through splint ligation, can align with the DNA data file as a synchronization marker [39] to improve the data fidelity and define the data in series and parallel. The data size and position can easily recover original digital data.…”

Coding for DNA data storage

“…To further improve the information density, in 2019, two research teams from Israel and South Korea independently proposed using composite DNA characters for encoding data, breaking through the capacity limitation of the traditional quaternary DNA data system [24], [25]. Recently, researchers from Stanford University have also implemented two DNA data storage systems with advanced codes and algorithms, reducing the cost [26], [27]. Owing to the explosion of research works happening in this area, the competitiveness of DNA as a medium for data storage has been significantly increased.…”

“…Since that, most works like [9], [17], [23], [26]- [28] proposed and implemented error correction coding schemes in DNA storage, achieving error-free data recovery. This proves that error correction mechanism is of importance to DNA data storage.…”

“…Particularly, the codes proposed are generally designed based on the channel model. For instance, researchers in [23], [26] regard DNA data storage system with Illumina sequencing as an erasure channel, and they used fountain code and low-density parity-check (LDPC) code to correct errors. To recover data in DNA data storage using Nanopore sequencing, researchers in [9], [10] used additional consensus algorithms to reduce the high error rates in raw data from sequencing while researchers in [27] used convolutional codes and soft decoding leveraging the information provided by the unique mechanism of Nanopore sequencing.…”