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Rare Event Detection Using Error-corrected DNA and RNA Sequencing
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Iterative Soft Decoding Algorithm for DNA Storage Using Quality Score and Redecoding.

Jaeho Jeong, Hosung Park, Hee-Youl Kwak

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    This study introduces a novel iterative soft decoding algorithm for DNA data storage, improving error correction capabilities. The new method enhances DNA storage system robustness by reducing read numbers and handling insertion/deletion errors.

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    Area of Science:

    • Biotechnology
    • Data Science
    • Bioinformatics

    Background:

    • Deoxyribonucleic acid (DNA) is a promising medium for next-generation data storage.
    • Error correcting codes (ECCs) are crucial for mitigating errors in DNA synthesis, storage, and sequencing.
    • Existing hard decoding algorithms have limitations in correcting complex errors.

    Purpose of the Study:

    • To enhance the error correction capability and robustness of DNA data storage systems.
    • To propose a novel iterative soft decoding algorithm for DNA data recovery.
    • To improve the accuracy of data retrieval from erroneous DNA sequences.

    Main Methods:

    • Developed an iterative soft decoding algorithm utilizing soft information from FASTQ files and channel statistics.
    • Introduced a new formula for log-likelihood ratio (LLR) calculation using quality scores (Q-scores).
    • Employed a redecoding method suitable for DNA sequencing error detection and correction, based on fountain code structures.

    Main Results:

    • Achieved a 2.3%–7.0% improvement in reading number reduction compared to state-of-the-art methods.
    • Demonstrated the algorithm's effectiveness across three different sets of sequenced data.
    • Successfully handled erroneous sequenced oligo reads, including insertion and deletion errors.

    Conclusions:

    • The proposed soft decoding algorithm offers significant improvements for DNA data storage systems.
    • This method enhances data integrity and retrieval efficiency in the presence of sequencing errors.
    • The algorithm shows potential for widespread adoption in DNA data storage applications.