A WebGL-powered toolkit for interactive visualization of high-resolution, multiplexed bioimaging datasets.

Viv is a JavaScript library for rendering OME-TIFF and OME-NGFF (Zarr) directly in the browser. The rendering components of Viv are packaged as deck.gl layers, making it easy to compose with existing layers to create rich interactive visualizations.

More details and related work can be found in our paper and original preprint. Please cite our paper in your research:

Trevor Manz, Ilan Gold, Nathan Heath Patterson, Chuck McCallum, Mark S Keller, Bruce W Herr II, Katy Börner, Jeffrey M Spraggins, Nils Gehlenborg, "Viv: multiscale visualization of high-resolution multiplexed bioimaging data on the web." Nature Methods (2022), doi:10.31219/10.1038/s41592-022-01482-7

Screenshot	Description
	Avivator A lightweight viewer for local and remote datasets. The source code is include in this repository under avivator/. See our 🎥 video tutorial to learn more.
	Vizarr A minimal, purely client-side program for viewing OME-NGFF and other Zarr-based images. Vizarr supports a Python backend using the imjoy-rpc, allowing it to not only function as a standalone application but also directly embed in Jupyter or Google Colab Notebooks.

• Vitessce visualization framework
• HuBMAP Common Coordination Framework Exploration User Interface (CCF EUI)
• OME-Blog OME-NGFF and OME-NGFF HCS announcements
• ImJoy I2K Tutorial
• Galaxy Project includes Avivator as default viewer for OME-TIFF files
• 10x Genomics uses Viv in their viewer for Xenium In Situ Analysis Technology: demo

Viv's data loaders support OME-NGFF (Zarr), OME-TIFF, and Indexed OME-TIFF*. We recommend converting proprietrary file formats to open standard formats via the bioformats2raw + raw2ometiff pipeline. Non-pyramidal datasets are also supported provided the individual texture can be uploaded to the GPU (< 4096 x 4096 in pixel size).

Please see the tutorial for more information.

*We describe Indexed OME-TIFF in our paper as an optional enhancement to provide efficient random chunk access for OME-TIFF. Our approach substantially improves chunk load times for OME-TIFF datasets with large Z, C, or T dimensions that otherwise may incur long latencies due to seeking. More information on generating an IFD index (JSON) can be found in our tutorial or documentation.

$ npm install @hms-dbmi/viv

You will also need to install deck.gl and other peerDependencies manually. This step prevent users from installing multiple versions of deck.gl in their projects.

$ npm install deck.gl @luma.gl/core

Breaking changes may happen on the minor version update. Please see the changelog for information.

Detailed API information and example sippets can be found in our documentation.

This repo is a monorepo using pnpm workspaces. The package manager used to install and link dependencies must be pnpm.

Each folder under packages/ are a published as a separate packages on npm under the @vivjs scope. The top-level package @hms-dbmi/viv exports from these dependencies.

To develop and test the @hms-dbmi/viv package:

1. Run pnpm install in viv root folder
2. Run pnpm dev to start a development server
3. Run pnpm test to run all tests (or specific, e.g., pnpm test --filter=@vivjs/layers)

To build viv's documentation and the Avivator website (under sites/), run:

pnpm build # all packages, avivator, and documentation
pnpm -r build --filter=avivator # build a specific package or site

For changes to be reflected in package changelogs, run npx changeset and follow the prompts.

Note not every PR requires a changeset. Since changesets are focused on releases and changelogs, changes to the repository that don't effect these won't need a changeset (e.g., documentation, tests).

The Changesets GitHub Action will create and update a PR that applies changesets versions of @vivjs/ packages to NPM.

Viv supports both WebGL1 and WebGL2 contexts, to provides coverage across Safari, Firefox, Chrome, and Edge. Please file an issue if you find a browser in which Viv does not work.