Visualizing Volumetric and Segmentation Data using Mol* Volumes & Segmentations 2.0

Ever-increasing availability of experimental volumetric data (e.g., in .ccp4, .mrc, .map, .rec, .zarr, .ome.tif formats) and advances in segmentation software (e.g., Amira, Segger, IMOD) and formats (e.g., .am, .seg, .mod, etc.) have led to a demand for efficient web-based visualization tools. Despite this, current solutions remain scarce, hindering data interpretation and dissemination. Previously, we introduced Mol* Volumes & Segmentations (Mol* VS), a web application for the visualization of volumetric, segmentation, and annotation data (e.g., semantically relevant information on biological entities corresponding to individual segmentations such as Gene Ontology terms or PDB IDs). However, this lacked important features such as the ability to edit annotations (e.g., assigning user-defined descriptions of a segment) and seamlessly share visualizations. Additionally, setting up Mol* VS required a substantial programming background. This article presents an updated version, Mol* VS 2.0, that addresses these limitations. As part of Mol* VS 2.0, we introduce the Annotation Editor, a user-friendly graphical interface for editing annotations, and the Volumes & Segmentations Toolkit (VSToolkit) for generating shareable files with visualization data. The outlined protocols illustrate the utilization of Mol* VS 2.0 for visualization of volumetric and segmentation data across various scales, showcasing the progress in the field of molecular complex visualization. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: VSToolkit-setting up and visualizing a user-constructed Mol* VS 2.0 database entry Basic Protocol 2: VSToolkit-visualizing multiple time frames and volume channels Support Protocol 1: Example: Adding database entry idr-13457537 Alternate Protocol 1: Local-server-and-viewer-visualizing multiple time frames and volume channels Support Protocol 2: Addition of database entry custom-tubhiswt Basic Protocol 3: VSToolkit-visualizing a specific channel and time frame Basic Protocol 4: VSToolkit-visualizing geometric segmentation Basic Protocol 5: VSToolkit-visualizing lattice segmentations Alternate Protocol 2: "Local-server-and-viewer"-visualizing lattice segmentations Basic Protocol 6: "Local-server-and-viewer"-visualizing multiple volume channels Support Protocol 3: Deploying a server API Support Protocol 4: Hosting Mol* viewer with VS extension 2.0 Support Protocol 5: Example: Addition of database entry empiar-11756 Support Protocol 6: Example: Addition of database entry emd-1273 Support Protocol 7: Editing annotations Support Protocol 8: Addition of database entry idr-5025553.

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Publication Details

Journal
Current Protocols
Published
2024-12-01
DOI
https://doi.org/10.1002/cpz1.70070
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Visualizing Volumetric and Segmentation Data using Mol* Volumes & Segmentations 2.0

David Sehnal, Alessio Cantara, Aliaksei Chareshneu, Dominick Tichý
Current Protocols
Cell Image Analysis Techniques
article

Visualizing Volumetric and Segmentation Data using Mol* Volumes & Segmentations 2.0

David Sehnal, Alessio Cantara, Aliaksei Chareshneu, Dominick Tichý
article en

Abstract

Ever-increasing availability of experimental volumetric data (e.g., in .ccp4, .mrc, .map, .rec, .zarr, .ome.tif formats) and advances in segmentation software (e.g., Amira, Segger, IMOD) and formats (e.g., .am, .seg, .mod, etc.) have led to a demand for efficient web-based visualization tools. Despite this, current solutions remain scarce, hindering data interpretation and dissemination. Previously, we introduced Mol* Volumes & Segmentations (Mol* VS), a web application for the visualization of volumetric, segmentation, and annotation data (e.g., semantically relevant information on biological entities corresponding to individual segmentations such as Gene Ontology terms or PDB IDs). However, this lacked important features such as the ability to edit annotations (e.g., assigning user-defined descriptions of a segment) and seamlessly share visualizations. Additionally, setting up Mol* VS required a substantial programming background. This article presents an updated version, Mol* VS 2.0, that addresses these limitations. As part of Mol* VS 2.0, we introduce the Annotation Editor, a user-friendly graphical interface for editing annotations, and the Volumes & Segmentations Toolkit (VSToolkit) for generating shareable files with visualization data. The outlined protocols illustrate the utilization of Mol* VS 2.0 for visualization of volumetric and segmentation data across various scales, showcasing the progress in the field of molecular complex visualization. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: VSToolkit-setting up and visualizing a user-constructed Mol* VS 2.0 database entry Basic Protocol 2: VSToolkit-visualizing multiple time frames and volume channels Support Protocol 1: Example: Adding database entry idr-13457537 Alternate Protocol 1: Local-server-and-viewer-visualizing multiple time frames and volume channels Support Protocol 2: Addition of database entry custom-tubhiswt Basic Protocol 3: VSToolkit-visualizing a specific channel and time frame Basic Protocol 4: VSToolkit-visualizing geometric segmentation Basic Protocol 5: VSToolkit-visualizing lattice segmentations Alternate Protocol 2: "Local-server-and-viewer"-visualizing lattice segmentations Basic Protocol 6: "Local-server-and-viewer"-visualizing multiple volume channels Support Protocol 3: Deploying a server API Support Protocol 4: Hosting Mol* viewer with VS extension 2.0 Support Protocol 5: Example: Addition of database entry empiar-11756 Support Protocol 6: Example: Addition of database entry emd-1273 Support Protocol 7: Editing annotations Support Protocol 8: Addition of database entry idr-5025553.

Current ProtocolsVol. 4(12)
European Bioinformatics Institute (GB), Masaryk University (CZ)
Masarykova Univerzita
Openalex Percentile: Top 86%
Cell Image Analysis Techniques
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