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Longshot enables accurate variant calling in diploid genomes from single-molecule long read sequencing

Author

Listed:
  • Peter Edge

    (University of California, San Diego)

  • Vikas Bansal

    (University of California, San Diego)

Abstract

Whole-genome sequencing using sequencing technologies such as Illumina enables the accurate detection of small-scale variants but provides limited information about haplotypes and variants in repetitive regions of the human genome. Single-molecule sequencing (SMS) technologies such as Pacific Biosciences and Oxford Nanopore generate long reads that can potentially address the limitations of short-read sequencing. However, the high error rate of SMS reads makes it challenging to detect small-scale variants in diploid genomes. We introduce a variant calling method, Longshot, which leverages the haplotype information present in SMS reads to accurately detect and phase single-nucleotide variants (SNVs) in diploid genomes. We demonstrate that Longshot achieves very high accuracy for SNV detection using whole-genome Pacific Biosciences data, outperforms existing variant calling methods, and enables variant detection in duplicated regions of the genome that cannot be mapped using short reads.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12493-y
    DOI: 10.1038/s41467-019-12493-y
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    Cited by:

    1. M. Mahmoud & Y. Huang & K. Garimella & P. A. Audano & W. Wan & N. Prasad & R. E. Handsaker & S. Hall & A. Pionzio & M. C. Schatz & M. E. Talkowski & E. E. Eichler & S. E. Levy & F. J. Sedlazeck, 2024. "Utility of long-read sequencing for All of Us," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Anna Zimmermann & Julian E. Prieto-Vivas & Charlotte Cautereels & Anton Gorkovskiy & Jan Steensels & Yves Peer & Kevin J. Verstrepen, 2023. "A Cas3-base editing tool for targetable in vivo mutagenesis," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Xiao Luo & Xiongbin Kang & Alexander Schönhuth, 2022. "VeChat: correcting errors in long reads using variation graphs," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    4. Charlotte Cautereels & Jolien Smets & Peter Bircham & Dries De Ruysscher & Anna Zimmermann & Peter De Rijk & Jan Steensels & Anton Gorkovskiy & Joleen Masschelein & Kevin J. Verstrepen, 2024. "Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    5. Cheng-Kai Shiau & Lina Lu & Rachel Kieser & Kazutaka Fukumura & Timothy Pan & Hsiao-Yun Lin & Jie Yang & Eric L. Tong & GaHyun Lee & Yuanqing Yan & Jason T. Huse & Ruli Gao, 2023. "High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Sina Majidian & Mohammad Hossein Kahaei & Dick de Ridder, 2020. "Minimum error correction-based haplotype assembly: Considerations for long read data," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-12, June.
    7. 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.

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