De Bruijn Graph Partitioning for Scalable and Accurate DNA Storage Processing
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Motivation
DNA-based data storage offers a compelling solution for long-term, high-density archiving. In this framework, accurately reconstructing high-quality encoded sequences after sequencing is critical, as it has a direct impact on the design of error-correcting codes optimized for DNA storage. Furthermore, efficient and scalable processing is essential to manage the large volumes of data expected in such applications.
Results
We introduce a novel method based on de Bruijn graph partitioning, enabling fast and accurate processing of sequencing data regardless of the underlying sequencing technology and without requiring prior knowledge of the information encoded in the oligonucleotides. Evaluated on both synthetic and real datasets, the method achieves excellent precision and recall. It is implemented in C++ within the software ConCluD and optimized for multi-core servers. Our experiments demonstrated that a dataset of 55 million reads, corresponding to a 135 MB binary file, can be processed in less than 10 minutes on a 16 hyper-threaded core server.
