MoBIE: a Fiji plugin for sharing and exploration of multi-modal cloud-hosted big image data
Constantin Pape, Kimberly Meechan, Ekaterina Moreva, Martin Schorb, Nicolas Chiaruttini, Valentyna Zinchenko, Hernando Martínez Vergara, Giulia Mizzon, Josh Moore, Detlev Arendt, Anna Kreshuk, Yannick Schwab, Christian Tischer · Nature Methods · 2023
Modern microscopy produces massive image datasets that enable detailed multi-scale analysis and can combine several modalities. Visualizing, exploring and sharing such data are challenges both during the execution of a research project and after publication to enable open access. To this end we have developed MoBIE, a Fiji 1 plugin for multi-modal big image data sharing and exploration. It supports visualization of multi-scale data of heterogeneous dimensionality (that is, combined 2D, 3D or 4D data) and several-terabyte image data, as well as the exploration of image segmentations, corresponding measurements and annotations. MoBIE uses next-generation image file formats, such as OME-Zarr 2 , that enable access to multi-scale data on local or cloud storage, permitting the transparent sharing and publication of data without the need to run a web service. In addition, MoBIE allows users to easily configure and share fully reproducible ‘views’ of their data. MoBIE has enabled integration of multiple modalities and open access for data from different domains of the life sciences. This includes data from studies in developmental biology 3 (Fig. 1a ), correlative microscopy, high-throughput screening microscopy 4 , plant biology and spatial transcriptomics 5 (all Fig. 1c ). Further applications can be found in Supplementary Note 8 and Supplementary Figs. 1 – 4 . Video tutorials for MoBIE are available at https://www.youtube.com/@MoBIE-Viewer and documentation at https://mobie.github.io/ . Fig. 1: An overview of MoBIE. a , MoBIE user interface. Image data, tables and views can be accessed from local and/or cloud storage. The image viewer (BigDataViewer) shows the image data and the interactive tables display features associated with segmented objects, image regions or spot data. Scatter plots visualize table columns; segmented objects can be rendered in 3D. Navigation and selection are synchronized between all four viewer elements. Here, we show gene clustering on top of the electron microscopy data from the Platynereis atlas 3 . The cells corresponding to a cluster are selected in each viewer element. b , MoBIE workflow. After data collection users can create a MoBIE project with the Fiji plugin or the python library. More data can be added continuously after the project is created. The MoBIE Fiji plugin can access this data either through the file system or object storage. Users can save any viewer configuration as a view and share the saved views with collaborators or use them to build interactive and reproducible figures. c , Example applications. MoBIE can represent data from many different modalities, including published data from correlative light-electron microscopy, high throughput screening microscopy 4 , light microscopy time series and spatial transcriptomics 5 . The panels from a and c are available as views within MoBIE and can be opened via the “Open Published MoBIE View” command in Fiji. Full size image