Using soft information to improve error tolerance of motif-based DNA storage systems

—The surge in demand for cost-effective, durable long-term archival media, coupled with density limitations of contemporary magnetic media, has resulted in synthetic DNA emerging as a promising new alternative. Today, the limiting factors for DNA-based data archival are the high read/write cost and low throughput. New motif-based DNA storage solutions are being developed to address these limitations. However, these new techniques often reduce cost at the expense of reliability, as they introduce more errors during writing and reading data. In order to deal with such errors, it is important to design efficient pipelines that can carefully use redundancy to mask errors without amplifying overall cost. In this paper, we present OligoArchive-DSM (OA-DSM), an end-to-end, motifbased, DNA storage solution that provides high error tolerance at low read/write costs. The use of motifs as building blocks in OA-DSM creates new challenges related to the computation of soft information for improving error-correction decoding performance. Thus, we present heuristics for scaling LLR that rely on various design aspects of OA-DSM and demonstrate their utility using simulation studies and wet lab experiments.