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Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software

Author

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  • Daniel L. Cameron

    (Walter and Eliza Hall Institute of Medical Research
    University of Melbourne)

  • Leon Stefano

    (Walter and Eliza Hall Institute of Medical Research)

  • Anthony T. Papenfuss

    (Walter and Eliza Hall Institute of Medical Research
    University of Melbourne
    Victorian Comprehensive Cancer Centre
    University of Melbourne)

Abstract

In recent years, many software packages for identifying structural variants (SVs) using whole-genome sequencing data have been released. When published, a new method is commonly compared with those already available, but this tends to be selective and incomplete. The lack of comprehensive benchmarking of methods presents challenges for users in selecting methods and for developers in understanding algorithm behaviours and limitations. Here we report the comprehensive evaluation of 10 SV callers, selected following a rigorous process and spanning the breadth of detection approaches, using high-quality reference cell lines, as well as simulations. Due to the nature of available truth sets, our focus is on general-purpose rather than somatic callers. We characterise the impact on performance of event size and type, sequencing characteristics, and genomic context, and analyse the efficacy of ensemble calling and calibration of variant quality scores. Finally, we provide recommendations for both users and methods developers.

Suggested Citation

  • Daniel L. Cameron & Leon Stefano & Anthony T. Papenfuss, 2019. "Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-11146-4
    DOI: 10.1038/s41467-019-11146-4
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    Cited by:

    1. Tingting Gong & Vanessa M Hayes & Eva K F Chan, 2020. "Shiny-SoSV: A web-based performance calculator for somatic structural variant detection," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-20, August.
    2. David E. Torres & H. Martin Kramer & Vittorio Tracanna & Gabriel L. Fiorin & David E. Cook & Michael F. Seidl & Bart P. H. J. Thomma, 2024. "Implications of the three-dimensional chromatin organization for genome evolution in a fungal plant pathogen," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    3. Ramesh Rajaby & Dong-Xu Liu & Chun Hang Au & Yuen-Ting Cheung & Amy Yuet Ting Lau & Qing-Yong Yang & Wing-Kin Sung, 2023. "INSurVeyor: improving insertion calling from short read sequencing data," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. Yoshitaka Sakamoto & Shuhei Miyake & Miho Oka & Akinori Kanai & Yosuke Kawai & Satoi Nagasawa & Yuichi Shiraishi & Katsushi Tokunaga & Takashi Kohno & Masahide Seki & Yutaka Suzuki & Ayako Suzuki, 2022. "Phasing analysis of lung cancer genomes using a long read sequencer," Nature Communications, Nature, vol. 13(1), pages 1-17, December.

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