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Setup Environment
Basically, HistoJS has a front-end, Flask as the back-end framework, and a images database (i.e. Digital Slide Archive) —it can be conceptualized as having three layers:
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JavaScript UI Layer (Front-End): This is the layer that the end-users interact with, and can handle the browsing and OME-TIFF channels grouping phase.
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Flask (Back-End) Layer: This Python layer, powered by Flask handles the analysis phase.
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Data Layer (Digital Slide Archive): This is where OME-TIFF data is stored, retrieved, and managed. It includes a data management system and Rest APIs to handle the requests.
- Install requirements
3.4 < python < 3.8 is recommendedFor deploying HistoJS on a cluster or a local client-side machine, first download or clone HistoJS repository:
git clone https://github.com/Mmasoud1/HistoJS.gitThen create histojs conda env
conda env create -f histojs.ymlAfter creating the histojs environment, from the root level of the repository open a new terminal, activate the env and run the python ResApi file:
source activate histojs
python RestApi.pyTo run the local host in the browser, just start up a simple local server from the root level of the repository with any available port number 8xxx (e.g., 8020)
python -m http.server 8xxx-In the browser URL open the local host with the selected port number (e.g., 8020):
http://localhost:8020/For using the backbone Digital Slide Archive (DSA) server (e.g., Styx ), you need to create a user account on any DSA servers and upload your OME-TIFF image, cells mask (Optional), and the channels metadata CSV file to your collection as in this link:
https://styx.neurology.emory.edu/girder/#folder/658d5f2ca45554f5d9171e01Please note: if the name of the OME image file is

The Channel metadata CSV file must have at least two columns: 'channel_number' and 'channel_name' :
