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Rescuing low frequency variants within intra-host viral populations directly from Oxford Nanopore sequencing data

Author

Listed:
  • Yunxi Liu

    (Rice University)

  • Joshua Kearney

    (Rice University)

  • Medhat Mahmoud

    (Human Genome Sequencing Center, Baylor College of Medicine)

  • Bryce Kille

    (Rice University)

  • Fritz J. Sedlazeck

    (Rice University
    Human Genome Sequencing Center, Baylor College of Medicine)

  • Todd J. Treangen

    (Rice University)

Abstract

Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost. Tracking low frequency intra-host variants provides important insights with respect to elucidating within-host viral population dynamics and transmission. However, given the higher error rate of ONT, accurate identification of intra-host variants with low allele frequencies remains an open challenge with no viable computational solutions available. In response to this need, we present Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from ONT data alone. We evaluate Variabel on both synthetic data (SARS-CoV-2) and patient derived datasets (Ebola virus, norovirus, SARS-CoV-2); our results show that Variabel can accurately identify low frequency variants below 0.5 allele frequency, outperforming existing state-of-the-art ONT variant callers for this task. Variabel is open-source and available for download at: www.gitlab.com/treangenlab/variabel .

Suggested Citation

  • Yunxi Liu & Joshua Kearney & Medhat Mahmoud & Bryce Kille & Fritz J. Sedlazeck & Todd J. Treangen, 2022. "Rescuing low frequency variants within intra-host viral populations directly from Oxford Nanopore sequencing data," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28852-1
    DOI: 10.1038/s41467-022-28852-1
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    References listed on IDEAS

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    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. Fatemeh Mohebbi & Alex Zelikovsky & Serghei Mangul & Gerardo Chowell & Pavel Skums, 2024. "Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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