Skip to main content

Thank you for visiting 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.

Genuage: visualize and analyze multidimensional single-molecule point cloud data in virtual reality


Experimentally recorded point cloud data, such as those generated by single-molecule localization microscopy, are continuously increasing in size and dimension. Gaining an intuitive understanding and facilitating the analysis of such multidimensional data remains challenging. Here we report a new open-source software platform, Genuage, that enables the easy perception of, interaction with and analysis of multidimensional point clouds in virtual reality. Genuage is compatible with arbitrary multidimensional data extending beyond single-molecule localization microscopy.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type



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

Fig. 1: An overview of the Genuage platform.

Data availability

Data are available in the GitHub repository ( and upon request. The data that were used in Supplementary Video 6 can be found at the following links: MNIST data (, flocking birds data (; Flock1) and LiDAR data (; marketsquarefeldkirch4).

Code availability

The reviewed source code for Genuage is available as Supplementary Software. Updated versions can be found at The repository includes scripts for reading JSON files in MATLAB and for data exchange with Python and MATLAB.


  1. Betzig, E. et al. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313, 1642–1645 (2006).

    Article  CAS  Google Scholar 

  2. Hajj, B., El Beheiry, M., Izeddin, I., Darzacq, X. & Dahan, M. Accessing the third dimension in localization-based super-resolution microscopy. Phys. Chem. Chem. Phys. 16, 16340–16348 (2014).

    Article  CAS  Google Scholar 

  3. Hajj, B. et al. Whole-cell, multicolor superresolution imaging using volumetric multifocus microscopy. Proc. Natl Acad. Sci. USA 111, 17480–17485 (2014).

    Article  CAS  Google Scholar 

  4. Valades Cruz, C. A. et al. Quantitative nanoscale imaging of orientational order in biological filaments by polarized superresolution microscopy. Proc. Natl Acad. Sci. USA 113, E820–E828 (2016).

    Article  CAS  Google Scholar 

  5. El Beheiry, M. et al. A primer on the Bayesian approach to high-density single-molecule trajectories analysis. Biophys. J. 110, 1209–1215 (2016).

    Article  CAS  Google Scholar 

  6. Balo, A. R., Wang, M. & Ernst, O. P. Accessible virtual reality of biomolecular structural models using the Autodesk Molecule Viewer. Nat. Methods 14, 1122–1123 (2017).

    Article  Google Scholar 

  7. El Beheiry, M. et al. Virtual reality: beyond visualization. J. Mol. Biol. 431, 1315–1321 (2019).

    Article  CAS  Google Scholar 

  8. Spark, A. et al. vLUME: 3D virtual reality for single-molecule localization microscopy. Preprint at bioRxiv (2020).

  9. El Beheiry, M. & Dahan, M. ViSP: representing single-particle localizations in three dimensions. Nat. Methods 10, 689–690 (2013).

    Article  CAS  Google Scholar 

  10. Saredakis, D. et al. Factors associated with virtual reality sickness in head-mounted displays: a systematic review and meta-analysis. Front. Hum. Neurosci. 14, 96 (2020).

  11. El Beheiry, M., Dahan, M. & Masson, J. B. InferenceMAP: mapping of single-molecule dynamics with Bayesian inference. Nat. Methods 12, 594–595 (2015).

    Article  CAS  Google Scholar 

Download references


We acknowledge funding from the Fondation pour la recherche médicale (FRM; DEI20151234398) (B.H.), the Agence National de la recherche (ANR-19-CE42-0003-01) (B.H.), the LabEx CelTisPhyBio (ANR-10-LBX-0038, ANR-10-IDEX-0001-02) (B.H.) and the Institut Curie (B.H.). We recognize the support of France-BioImaging infrastructure grant ANR-10-INBS-04 (Investments for the future) (B.H.). We acknowledge the financial support of the Agence pour la Recherche sur le Cancer (ARC Foundation), ARC (B.H.) and DIM ELICIT (B.H.). We acknowledge funding from the Pasteur Institute (J.-B.M.), the sponsorships of CRPCEN, Gilead Science and foundation EDF (J.-B.M.), the ANR-17-CE23-0016 TRamWAy (J.-B.M.), the INCEPTION project (PIA/ANR- 16-CONV-0005, OG) (J.-B.M.), the programme d’investissement d’avenir supported by L’Agence Nationale de la Recherche ANR-19-P3IA-0001 Institut 3IA Prairie (J.-B.M.) and the support of the AVIRON grant from the Région Ile-de-France (DIM-ELICIT).

Author information

Authors and Affiliations



T.B., M.E.B. and C.C. coded the software. J.-B.M. and B.H. coded the analysis routines. B.H. provided super-resolution and single-particle tracking data. M.E.B., J.-B.M. and B.H. conceived the idea, directed the project and wrote the paper. All authors read the paper and contributed to and approved the content.

Corresponding authors

Correspondence to Jean-Baptiste Masson or Bassam Hajj.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Rita Strack was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Notes 1–3.

Reporting Summary

Supplementary Video 1

General overview of the Genuage interface. Example of loading and manipulating two-color point cloud data followed by distance measurement. The two colors are obtained by sequential super-resolution STORM imaging of fission yeast cell wall during division labeled with Alexa 647, followed by PALM imaging of tubulin fibers expressing tdEOS fluorescent protein in multifocus microscopy (MFM).

Supplementary Video 2

Example of selection of a complex 3D form of point clouds in VR. The data were obtained by 3D STORM imaging of mitochondria using MFM.

Supplementary Video 3

Clipping plane tool in VR to explore the complex fiber network of point clouds generated by 3D super-resolution imaging of tubulin fibers of HeLa cells in MFM.

Supplementary Video 4

Using the profiler tool to measure the histogram of point clouds along a segment in 3D. The data correspond to 3D localizations obtained by STORM super-resolution imaging of TOM20 labeled with Alexa 647 dye. Such a task is commonly performed to check the real resolution power of a super-resolution experiment and to verify separation between point cloud features.

Supplementary Video 5

Trajectory analysis performed on localizations of beads injected in the nucleus of U2OS cells and imaged by MFM. Local analysis and diffusion coefficient calculation in a dense 4D point cloud.

Supplementary Video 6

Visualizing different types of point cloud data using Genuage. Show cases: 4D (3D with color) embedding of MNIST dataset (i), visualization of the trajectories of flocking birds (ii) and LiDAR point cloud data (iii).

Supplementary Software

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Blanc, T., El Beheiry, M., Caporal, C. et al. Genuage: visualize and analyze multidimensional single-molecule point cloud data in virtual reality. Nat Methods 17, 1100–1102 (2020).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing