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

Qian Zhou, Fahu Ji, Dongxiao Lin, Xianming Liu, Zexuan Zhu () and Jue Ruan ()
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Qian Zhou: PengCheng Laboratory
Fahu Ji: Harbin Institute of Technology
Dongxiao Lin: Shenzhen University
Xianming Liu: PengCheng Laboratory
Zexuan Zhu: Shenzhen University
Jue Ruan: Chinese Academy of Agricultural Sciences

Nature Communications, 2024, vol. 15, issue 1, 1-7

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-47562-4

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