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

View ORCID ProfileShubham Chandak, Kedar Tatwawadi, Billy Lau, Jay Mardia, Matthew Kubit, Joachim Neu, Peter Griffin, Mary Wootters, Tsachy Weissman, Hanlee Ji
doi: https://doi.org/10.1101/770032
Shubham Chandak
Stanford University
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  • For correspondence: schandak@stanford.edu
Kedar Tatwawadi
Stanford University
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Billy Lau
Stanford University
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Jay Mardia
Stanford University
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Matthew Kubit
Stanford University
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Joachim Neu
Stanford University
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Peter Griffin
Stanford University
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Mary Wootters
Stanford University
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Tsachy Weissman
Stanford University
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Hanlee Ji
Stanford University
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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.

The code, data, and Supplementary Material is available at https://github.com/shubhamchandak94/LDPC_DNA_storage.

Footnotes

  • Corrected error in coverage variance calculation

  • https://github.com/shubhamchandak94/LDPC_DNA_storage

  • https://github.com/shubhamchandak94/LDPC_DNA_storage_data

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted September 27, 2019.
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Improved read/write cost tradeoff in DNA-based data storage using LDPC codes
Shubham Chandak, Kedar Tatwawadi, Billy Lau, Jay Mardia, Matthew Kubit, Joachim Neu, Peter Griffin, Mary Wootters, Tsachy Weissman, Hanlee Ji
bioRxiv 770032; doi: https://doi.org/10.1101/770032
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Improved read/write cost tradeoff in DNA-based data storage using LDPC codes
Shubham Chandak, Kedar Tatwawadi, Billy Lau, Jay Mardia, Matthew Kubit, Joachim Neu, Peter Griffin, Mary Wootters, Tsachy Weissman, Hanlee Ji
bioRxiv 770032; doi: https://doi.org/10.1101/770032

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