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Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing

Author

Listed:
  • Zaka Wing-Sze Yuen

    (EMBL Australia Partner Laboratory Network, Australian National University
    Australian National University)

  • Akanksha Srivastava

    (EMBL Australia Partner Laboratory Network, Australian National University
    Australian National University)

  • Runa Daniel

    (Victoria Police Forensic Services Department)

  • Dennis McNevin

    (University of Technology Sydney)

  • Cameron Jack

    (Australian National University)

  • Eduardo Eyras

    (EMBL Australia Partner Laboratory Network, Australian National University
    Australian National University
    Catalan Institution for Research and Advanced Studies (ICREA)
    Hospital del Mar Medical Research Institute (IMIM))

Abstract

DNA methylation plays a fundamental role in the control of gene expression and genome integrity. Although there are multiple tools that enable its detection from Nanopore sequencing, their accuracy remains largely unknown. Here, we present a systematic benchmarking of tools for the detection of CpG methylation from Nanopore sequencing using individual reads, control mixtures of methylated and unmethylated reads, and bisulfite sequencing. We found that tools have a tradeoff between false positives and false negatives and present a high dispersion with respect to the expected methylation frequency values. We described various strategies to improve the accuracy of these tools, including a consensus approach, METEORE ( https://github.com/comprna/METEORE ), based on the combination of the predictions from two or more tools that shows improved accuracy over individual tools. Snakemake pipelines are also provided for reproducibility and to enable the systematic application of our analyses to other datasets.

Suggested Citation

  • Zaka Wing-Sze Yuen & Akanksha Srivastava & Runa Daniel & Dennis McNevin & Cameron Jack & Eduardo Eyras, 2021. "Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-23778-6
    DOI: 10.1038/s41467-021-23778-6
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    Cited by:

    1. Zhen-Dong Zhong & Ying-Yuan Xie & Hong-Xuan Chen & Ye-Lin Lan & Xue-Hong Liu & Jing-Yun Ji & Fu Wu & Lingmei Jin & Jiekai Chen & Daniel W. Mak & Zhang Zhang & Guan-Zheng Luo, 2023. "Systematic comparison of tools used for m6A mapping from nanopore direct RNA sequencing," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Peng Ni & Neng Huang & Fan Nie & Jun Zhang & Zhi Zhang & Bo Wu & Lu Bai & Wende Liu & Chuan-Le Xiao & Feng Luo & Jianxin Wang, 2021. "Genome-wide detection of cytosine methylations in plant from Nanopore data using deep learning," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    3. P Acera Mateos & A J Sethi & A Ravindran & A Srivastava & K Woodward & S Mahmud & M Kanchi & M Guarnacci & J Xu & Z W S Yuen & Y Zhou & A Sneddon & W Hamilton & J Gao & L M Starrs & R Hayashi & V Wick, 2024. "Prediction of m6A and m5C at single-molecule resolution reveals a transcriptome-wide co-occurrence of RNA modifications," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    4. Yilei Fu & Sergey Aganezov & Medhat Mahmoud & John Beaulaurier & Sissel Juul & Todd J. Treangen & Fritz J. Sedlazeck, 2024. "MethPhaser: methylation-based long-read haplotype phasing of human genomes," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Dominik Stanojević & Zhe Li & Sara Bakić & Roger Foo & Mile Šikić, 2024. "Rockfish: A transformer-based model for accurate 5-methylcytosine prediction from nanopore sequencing," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    6. Peng Ni & Fan Nie & Zeyu Zhong & Jinrui Xu & Neng Huang & Jun Zhang & Haochen Zhao & You Zou & Yuanfeng Huang & Jinchen Li & Chuan-Le Xiao & Feng Luo & Jianxin Wang, 2023. "DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    7. Xue Yue & Zhiyuan Xie & Moran Li & Kai Wang & Xiaojing Li & Xiaoqing Zhang & Jian Yan & Yimeng Yin, 2022. "Simultaneous profiling of histone modifications and DNA methylation via nanopore sequencing," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

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