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Viv: multiscale visualization of high-resolution multiplexed bioimaging data on the web

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Fig. 1: Overview of data flow and rendering approaches for web-based bioimage data visualization and Viv features.

Code availability

Viv is open source and available under an MIT license at https://github.com/hms-dbmi/viv and at https://www.npmjs.com/package/@hms-dbmi/viv.

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Acknowledgements

We would like to thank members of the OME community for their guidance, as well as M. deCaestecker, E. Neumann and M. Brewer from Vanderbilt University and Vanderbilt University Medical Center for their efforts generating the imaging mass spectrometry and microscopy data highlighted in the referenced the use cases. Viv was developed with funding from the US National Institutes of Health (NIH; OT2OD026677, T15LM007092, T32HG002295) and National Science Foundation (NSF; DGE1745303) and the Harvard Stem Cell Institute (CF-0014-17-03). The use cases in this manuscript were supported with additional funding from the NIH (U54DK120058, 2P41GM103391, OT2OD026671) and NSF (CBET1828299).

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Authors and Affiliations

Authors

Contributions

N.G., T.M. and I.G. conceived the project. N.G. coordinated the author team and oversaw the project. T.M. and I.G. developed the software. N.G., T.M., I.G., M.S.K., C.M., N.H.P., B.W.H., K.B. and J.M.S. tested and offered user feedback for the software. N.H.P. and J.M.S. provided datasets for testing the software. T.M., I.G., N.H.P., M.S.K., C.M. and B.W.H. developed applications with the software for supporting use cases. N.G., T.M., N.H.P. and I.G. wrote the manuscript. All authors approved the final manuscript.

Corresponding author

Correspondence to Nils Gehlenborg.

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Competing interests

N.G. is a co-founder and equity owner of Datavisyn. All other authors declare no competing interests

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Nature Methods thanks Ulrik Günther and Nikita Vladimirov for their contribution to the peer review of this work.

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Supplementary Information

Supplementary Note 1

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Manz, T., Gold, I., Patterson, N.H. et al. Viv: multiscale visualization of high-resolution multiplexed bioimaging data on the web. Nat Methods 19, 515–516 (2022). https://doi.org/10.1038/s41592-022-01482-7

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