henhao
Sign in
BioinformaticsBioinformatics
Peer-reviewed journal article

De Bruijn Graph Partitioning for Scalable and Accurate DNA Storage Processing

Florestan De Moor, Olivier BoulléiD, Dominique D. LavenieriD

PDFDOIPreprint

Abstract

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSMotivationC_ST_ABSDNA-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. ResultsWe 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.

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSong '20Gu '25Sabnis '25Chandak '19Zhang '25Ben-Ari '21
73% semantic matchSynthetic Biology
Lifu Song, Feng Geng, Zi-Yi Gong+9 more·bioRxiv·Dec 20, 2020· 1 citations