Escher is a web-based tool to build, view, share, and embed metabolic maps. The easiest way to use Escher is to browse or build maps on the Escher website.
Visit the documentation to get started with Escher and explore the API.
Check out the developer docs, the Gitter chat room, and the Development Roadmap for information on Escher development. Feel free to submit bugs and feature requests as Issues, or, better yet, Pull Requests.
Follow @zakandrewking for Escher updates.
You can help support Escher by citing our publication when you use Escher or EscherConverter:
Zachary A. King, Andreas Dräger, Ali Ebrahim, Nikolaus Sonnenschein, Nathan E. Lewis, and Bernhard O. Palsson (2015) Escher: A web application for building, sharing, and embedding data-rich visualizations of biological pathways, PLOS Computational Biology 11(8): e1004321. doi:10.1371/journal.pcbi.1004321
Escher was developed at SBRG. Funding was provided by The National Science Foundation Graduate Research Fellowship under Grant no. DGE-1144086, The European Commission as part of a Marie Curie International Outgoing Fellowship within the EU 7th Framework Program for Research and Technological Development (EU project AMBiCon, 332020), and The Novo Nordisk Foundation through The Center for Biosustainability at the Technical University of Denmark (NNF10CC1016517)
First, install dependencies with npm (or you can use yarn):
npm install
Escher uses webpack to manage the build process. To run typical build steps, just run:
npm run build
You can run a development server with:
npm run start
# or for live updates when the source code changes:
npm run watch
To test the JavaScript files, run:
npm run test
Escher has a Python package for generating Escher visualizations from within a Python data anlaysis session. To learn more about using the features of the Python package, check out the documentation:
https://escher.readthedocs.io/en/latest/escher-python.html
You can install it with pip:
pip install escher
To install the Jupyter lab extension, simply install Escher with pip then install the extension:
pip install escher
jupyter labextension install @jupyter-widgets/jupyterlab-manager
jupyter labextension install escherTo install the Jupyter notebook extension, run the following:
pip install escher
# you'll need version >=5 of the `notebook` package
pip install "notebook>=5"
jupyter nbextension install --py escher
jupyter nbextension enable --py escherNote: depending on you environment, you might want to add the --sysprefix flag
to the nbextension commands. You might also need to use sudo to get around
permissions issues.
For development of the Python package, first build the JavaScript package and
copy it over to the py directory with these commands in the Escher root:
npm install
npm run build
npm run copy
Then in the py directory, install the Python package:
cd py
pip install -e . # installs escher in develop mode and dependencies
For Python testing, run this in the py directory:
cd py
pytest
To develop the Jupyter notebook and Jupyter Lab extensions, you will need install them with symlinks (the typical installation is describe in the docs).
First, install the Python package for development as described above.
For the Jupyter notebooks, run:
cd py
jupyter nbextension install --py --symlink escher
jupyter nbextension enable --py escher
If you are using virtualenv or conda, you can add the --sys-prefix flag to
those commands to keep your environment isolated and reproducible.
When you make changes, you will need to yarn copy and refresh notebook browser
tab.
For Jupyter Lab, run (in the root directory):
yarn watch # keep this running as a separate process
jupyter labextension install @jupyter-widgets/jupyterlab-manager
jupyter labextension link
jupyter lab --watch
If you don't see changes when you edit the code, try refreshing or restarting
jupyter lab --watch.
Build and run the docs::
cd docs
make html
cd _build/html
python -m SimpleHTTPServer # python 2
python -m http.server # python 3