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KSNP: a fast de Bruijn graph-based haplotyping tool approaching data-in time cost

Author

Listed:
  • Qian Zhou

    (PengCheng Laboratory)

  • Fahu Ji

    (Harbin Institute of Technology)

  • Dongxiao Lin

    (Shenzhen University)

  • Xianming Liu

    (PengCheng Laboratory
    Harbin Institute of Technology)

  • Zexuan Zhu

    (Shenzhen University
    Shenzhen University)

  • Jue Ruan

    (Chinese Academy of Agricultural Sciences)

Abstract

Long reads that cover more variants per read raise opportunities for accurate haplotype construction, whereas the genotype errors of single nucleotide polymorphisms pose great computational challenges for haplotyping tools. Here we introduce KSNP, an efficient haplotype construction tool based on the de Bruijn graph (DBG). KSNP leverages the ability of DBG in handling high-throughput erroneous reads to tackle the challenges. Compared to other notable tools in this field, KSNP achieves at least 5-fold speedup while producing comparable haplotype results. The time required for assembling human haplotypes is reduced to nearly the data-in time.

Suggested Citation

  • Qian Zhou & Fahu Ji & Dongxiao Lin & Xianming Liu & Zexuan Zhu & Jue Ruan, 2024. "KSNP: a fast de Bruijn graph-based haplotyping tool approaching data-in time cost," Nature Communications, Nature, vol. 15(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47562-4
    DOI: 10.1038/s41467-024-47562-4
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    References listed on IDEAS

    as
    1. Peter Edge & Vikas Bansal, 2019. "Longshot enables accurate variant calling in diploid genomes from single-molecule long read sequencing," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    2. Shilpa Garg, 2023. "Towards routine chromosome-scale haplotype-resolved reconstruction in cancer genomics," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
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