Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Correspondence
  • Published:

Chromoscope: interactive multiscale visualization for structural variation in human genomes

Nature Methods volume 20, pages 1834–1835 (2023)Cite this article

Subjects

With the wider adoption of whole-genome sequencing (WGS) for genome analysis, researchers can profile structural variants (SVs)1 in addition to smaller insertions, deletions and point mutations. Somatic SVs — such as copy number variants, translocations, transposable element insertions and complex rearrangements — have been shown to play a critical role in cancer development and therapy selection2,3. Germline SVs can also perturb disease-associated genes4, with WGS leading to increased diagnostic yields in rare disease cohorts5. However, the size and complexity of the data, combined with the difficulty of obtaining accurate SV calls, pose challenges in the interpretation of SVs, often requiring laborious visual inspection of potentially pathogenic variants using multiple visualization tools. To facilitate the identification of functionally relevant SVs and the characterization of genome-wide SV patterns, efficient browsing of candidate variants and visual assessment at multiple resolutions — from the whole genome to base-pair resolution at the sequencing-read level — are vital.

Chromoscope was developed using the Gosling library8, a grammar-based framework that offers building blocks for scalable, interactive and customizable genomics visualizations. The use of Gosling not only enhances the flexibility of Chromoscope but also helps the user to incorporate Chromoscope into different workflows through the Gosling specification (see documentation). For example, Chromoscope can export Gosling specifications (JSON)8 for usage within the Gosling online editor for further customization. A Chromoscope Python package is also available to visualize SV datasets in computational notebooks (for example, Jupyter Notebooks).

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The Chromoscope interface.

Data availability

The demonstration cancer genome data was obtained from the publicly available ICGC/TCGA PCAWG Consortium9 repository available at https://dcc.icgc.org/releases/. Demonstration data are limited to somatic mutation calls, which are publicly available, as opposed to germline mutation calls or raw sequencing reads. Additional data from cell lines were obtained from the SRA archive (project SRP162370), which is public, allowing us to showcase Chromoscope’s display of raw sequencing reads.

Code availability

The entire source code is publicly available at https://github.com/hms-dbmi/chromoscope under an MIT license (https://doi.org/10.5281/zenodo.7665959). The Chromoscope web application is available at https://chromoscope.bio.

References

  1. Cortés-Ciriano, I., Gulhan, D. C., Lee, J. J.-K., Melloni, G. E. M. & Park, P. J. Nat. Rev. Genet. 23, 298–314 (2022).

    Article  Google Scholar 

  2. Samsom, K. G. et al. J. Pathol. 258, 179–188 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Villani, A. et al. Nat. Cancer 4, 203–221 (2023).

    Article  CAS  PubMed  Google Scholar 

  4. Collins, R. L. et al. Nature 581, 444–451 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. 100,000 Genomes Project Pilot Investigators et al. N. Engl. J. Med. 385, 1868–1880 (2021).

  6. Robinson, J. T., Thorvaldsdottir, H., Turner, D. & Mesirov, J. P. Bioinformatics 39, btac830 (2023).

    Article  CAS  PubMed  Google Scholar 

  7. Diesh, C. et al. Genome Biol. 24, 74 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  8. L’Yi, S., Wang, Q., Lekschas, F. & Gehlenborg, N. IEEE Trans. Vis. Comput. Graph. 28, 140–150 (2022).

    Article  PubMed  Google Scholar 

  9. ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Nature 578, 82–93 (2020).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the US National Institutes of Health (R01HG011773, U01CA200059).

Author information

Authors and Affiliations

  1. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    Sehi L’Yi, Dominika Maziec, Victoria Stevens, Trevor Manz, Alexander Veit, Michele Berselli, Peter J. Park, Dominik Głodzik & Nils Gehlenborg

Authors
  1. Sehi L’Yi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dominika Maziec
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victoria Stevens
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Trevor Manz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alexander Veit
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Michele Berselli
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Peter J. Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Dominik Głodzik
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nils Gehlenborg
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.L. developed Chromoscope in close collaboration with D.G.; D.G., P.P. and N.G. conceived and supervised the project. D.M., V.S. and D.G. assisted with case studies. T.M. developed the Python package. D.M., M.B. and A.V. suggested critical improvements for the tool. The draft manuscript was written by S.L. and D.G. and all authors edited and gave feedback on the manuscript.

Corresponding authors

Correspondence to Peter J. Park, Dominik Głodzik or Nils Gehlenborg.

Ethics declarations

Competing interests

N.G. is a co-founder and equity owner of Datavisyn. D.G. is a consultant for Repare Therapeutics. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Methods thanks Tobias Rausch and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Supplementary information

Supplementary Information

Supplementary Notes, Supplementary Figure 1 and Supplementary Tables 1 and 2.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

L’Yi, S., Maziec, D., Stevens, V. et al. Chromoscope: interactive multiscale visualization for structural variation in human genomes. Nat Methods 20, 1834–1835 (2023). https://doi.org/10.1038/s41592-023-02056-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41592-023-02056-x

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer