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HistoJS is a new web-based interactive tool designed to overcome the challenges of using highly-multiplexed immunofluorescence (HMIF) images for spatial biology research. HistoJS provides open-source and extensible tools for analyzing spatial-molecular patterns, offering a deeper understanding of single-cell spatial relationships. It also features machine learning algorithms in a user-friendly interactive interface for the biomedical community.

The tool can manage, store, and analyze the multi-channel OME-Tiff files using Digital Slide Archive as a backbone to update the image metadata remotely or locally.

HistoJS Demo hosted by Github pages shows most core functionalities.

The analysis mode needs running of the Flask RestAPIs as the steps described here.

• HistoJS abstract is accepted for poster presentation in the SIAM 2024 Conference on Imaging Science (IS24) in Atlanta, GA.

• HistoJS paper is published in the Journal of Open Source Software (JOSS) on Feb 07, 2024.

• HistoJS abstract is accepted for poster presentation in the OHBM 2024 Annual Meeting in Seoul, Korea.

HistoJS paper for v1.1.0 is published on Feb 07, 2024, in the Journal of Open Source Software (JOSS)

For APA style, the paper can be cited as:

Masoud, M., Gutman, D., & Plis, S. (2024). HistoJS: Web-Based Analytical Tool for Advancing Multiplexed Images. Journal of Open Source Software, 9(94), 6317. https://doi.org/10.21105/joss.06317

For BibTeX format that is used by some publishers, please use:

@article{Masoud_HistoJS_Web-Based_Analytical_2024,
   author = {Masoud, Mohamed and Gutman, David and Plis, Sergey},
   doi = {10.21105/joss.06317},
   journal = {Journal of Open Source Software},
   month = feb,
   number = {94},
   pages = {6317},
   title = {{HistoJS: Web-Based Analytical Tool for Advancing Multiplexed Images}},
   url = {https://joss.theoj.org/papers/10.21105/joss.06317},
   volume = {9},
   year = {2024}
}