EasyFigAssembler: Enhance Omics Data Storytelling through Effective Figure Assembly
An effective figure helps communicate the data and findings clearly. The assembly of multi-panel omics-based figures for scientific publications is a time-consuming and error-prone process that often requires specialized software and skills. There is a lack of a quick and effective tool for assembling complex omics-based figures. We present EasyFigAssembler, a user-friendly web application that significantly simplifies and accelerates the making of multi-panel omics-based figures. The app supports nondestructive panel editing, multi-figure project management, and high-resolution export to TIFF, PDF, PNG, and JPEG formats, providing a complete solution for figure assembly without requiring programming expertise. Its Smart Layout feature automates the initial arrangement of panels into optimal, publication-ready grids. The advanced controls for column and row spanning enable the rapid assembly of complex, non-uniform layouts that are typically time-consuming to create. The workflow is ensured by an integrated Quality Advisor module that provides real-time feedback on effective resolution and color-blind-friendly palettes to warrant journal compliance. Finally, users can manage multiple figures and save their projects effortlessly. The source code of EasyFigAssembler is available at https://github.com/Pharmaco-OmicsLab/EasyFigAssembler. The web interface for users can be accessed at https://easyverse.app/easyfig/.
Authors
- Nguyen Phuoc Long (ORCID: https://orcid.org/0000-0002-4678-0546)
- Nguyen Quang Thu
Institutions
- Chang Gung University (TW)
- Molecular Medicine Research Institute (US)
- Institute of Biomedical Science (GB)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2026-03-04
- DOI
- https://doi.org/10.1021/acs.jproteome.5c01022
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00