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A survey of algorithms for the detection of genomic structural variants from long-read sequencing data

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Abstract

As long-read sequencing technologies are becoming increasingly popular, a number of methods have been developed for the discovery and analysis of structural variants (SVs) from long reads. Long reads enable detection of SVs that could not be previously detected from short-read sequencing, but computational methods must adapt to the unique challenges and opportunities presented by long-read sequencing. Here, we summarize over 50 long-read-based methods for SV detection, genotyping and visualization, and discuss how new telomere-to-telomere genome assemblies and pangenome efforts can improve the accuracy and drive the development of SV callers in the future.

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Fig. 1: An illustration of different types of SVs.
Fig. 2: The general framework of SV detection using long-read sequencing.
Fig. 3: Ribbon plot of HG002 ONT and PB reads for a 36,400-bp inversion at chr10:4,7023,408 (GRCh37), identified by cuteSV, Sniffles and SVIM.

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Acknowledgements

We thank several readers who worked on SVs to provide valuable feedback on our preprint, including A. Gouru, Y. Zhou and Y. Hu. We thank the developers of the various software tools described in the text for making their tools available with detailed documentation. The survey is in part supported by NIH grant GM132713 and the CHOP Research Institute.

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Authors and Affiliations

  1. Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Mian Umair Ahsan, Qian Liu, Jonathan Elliot Perdomo, Li Fang & Kai Wang

  2. School of Biomedical Engineering, Drexel University, Philadelphia, PA, USA

    Jonathan Elliot Perdomo

  3. Department of Genetics and Biomedical Informatics, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China

    Li Fang

  4. Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Kai Wang

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  1. Mian Umair Ahsan
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  4. Li Fang
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Contributions

Q.L. and K.W. conceived the study. M.U.A., Q.L. and K.W. wrote the initial version. J.P. and L.F. wrote several sections in the text and prepared figures. All authors read and approved the final manuscript.

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Correspondence to Kai Wang.

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Ahsan, M.U., Liu, Q., Perdomo, J.E. et al. A survey of algorithms for the detection of genomic structural variants from long-read sequencing data. Nat Methods 20, 1143–1158 (2023). https://doi.org/10.1038/s41592-023-01932-w

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