Overview of py4cytoscape¶
py4cytoscape is a Python package that communicates with Cytoscape via its REST API, providing access to a set over 250 functions that enable control of Cytoscape from within standalone and Notebook Python programming environments. It provides nearly identical functionality to RCy3, an R package in Bioconductor available to R programmers.
functions that can be leveraged from Python code to implement network biology-oriented workflows;
logging and debugging facilities that enable rapid development, maintenance, and auditing of Python-based workflow;
execute Python code on the Cytoscape workstation or in Jupyter Notebooks on local or remote servers.
With py4cytoscape, you can leverage Cytoscape to:
load and store networks in standard and nonstandard data formats;
visualize molecular interaction networks and biological pathways;
integrate these networks with annotations, gene expression profiles and other state data;
analyze, profile, and cluster these networks based on integrated data, using new and existing algorithms.
py4cytoscape enables an agile collaboration between powerful Cytoscape, Python libraries, and novel Python code so as to realize auditable, reproducible and sharable workflows.
Look to the Tutorials section to get started with py4cytoscape.
Look to the Install section for installation instructions.
Look to the Reference section to see details on py4cytoscape functions.
Look to the Concepts section to see read about important py4cytoscape topics, including how to use py4cytoscape from a Jupyter Notebook running on a remote server.
Note that py4cytoscape and RCy3 functions implement a common interface called the Cytoscape Automation API Definition.
A broad set of Cytoscape Automation samples and tutorials is available on the Cytoscape Automation Wiki.
The audience for py4cytoscape includes biologists, mathematicians, physicists, biologists, computer scientists, and social scientists. A running sample of research based on Cytoscape can be found on Tumblr. Cytoscape provides tutorials, videos, and automation vignettes.
Google Scholar reports that Cytoscape was cited in over 10,000 in academic papers in 2019, most of which executed Cytoscape via the traditional mouse and keyboard. py4cytoscape can automate these results as a means of achieving reproducible science.
Python is a powerful programming language that allows simple and flexible representations of networks as well as clear and concise expressions of network algorithms. Python has a vibrant and growing ecosystem of packages that can be used in combination with py4cytoscape to integrate with traditional workflow engines (e.g., Gene Pattern and Galaxy) to produce robust end-to-end workflows.
The py4cytoscape team welcomes questions posted as GitHub issues.
Please note that someone may have already had the same question that has already been answered. You may find an instant answer to your question by perusing both open and closed issues.
The original Python libraries for Cytoscape were written by Keiichiro Ono in 2015 as an interface to the then-new CyREST automation interface. Its original name was py2cytoscape. It was further evolved through 2019 by Kozo Nishida and Jorge Bouças.
In late 2019, py4cytoscape was undertaken by Barry Demchak as a replacement for py2cytoscape. It implemented the API defined by RCy3, an R package in Bioconductor developed by a Cytoscape Automation working group consisting of Alex Pico (primary author), Mark Grimes, Julia Gustavsen, Shraddha Pai, Ruth Isserlin, and Barry Demchak. RCy3 was based on prior work contributed by Paul Shannon, Tanja Muetze, Georgi Kolishkovski and Keiichiro Ono.
We intend to keep the function definitions available through py4cytoscape and RCy3 consistent and synchronized going forward, and to re-integrate unique features found only in py2cytoscape. This common interface is called the Cytoscape Automation API Definition.
Jun 28, 2022