Welcome to the home of OmniPath, a comprehensive collection of literature curated human and rodent signaling pathways. And pypath, a powerful Python module for molecular networks and pathways analysis.
Illustration by Spencer Phillips, EMBL-EBI. This cover artwork is the result of a collaboration between Spencer Phillips, Mary Todd-Bergman, Denes Turei, Tamas Korcsmaros and Julio Saez-Rodriguez, starting with the initial idea of using lenses by Jakob Wirbel (RWTH-Aachen). A modified version of this figure appeared in the Cover of Nature Methods Dec 2016
Since our last paper we added quite some new resources and features. For example homology translation to mouse and rat, transcriptional regulation from DoRothEA and other databases, miRNA-mRNA interactions, a number of ligand-receptor databases, improved processing of enzyme-substrate interactions and Gene Ontology, many other things. We even got a Cytoscape plug-in thanks to Francesco Ceccarelli . With Nicolàs Palacio and Olga Ivanova we improve pypath code quality, documentation and tests. On the figure below you can see the new parts highlighted by violet. Almost every couple of weeks we add new ones, stay tuned and follow our Twitter!
Overview of resources in pypath and OmniPath. New additions since Nov 2016 highlighted in violet. Expanded from Fig 1 of Turei et al. Nature Methods (2016). For high resolution PDF click here .
D Turei, T Korcsmaros and J Saez-Rodriguez (2016) OmniPath: guidelines and gateway for literature-curated signaling pathway resources. Nature Methods 13(12)
OmniPath is available via a web service, an R package , a Cytoscape plug-in and a Python module . For the web service see example queries here.
For old versions of the web service content see the archive .
In the webservice you can access not only OmniPath but also TF-gene interactions from DoRothEA . See example queries in the readme at the DoRothEA git repo.
pypath is a Python module for building molecular interaction networks. It is able to combine multiple resources, process custom files, and convert between different identifiers. Undirected and directed networks are supported. Once the network is constructed, you can load additional annotations and perform analysis tasks. A large collection of these are already included in pypath. Thanks to the flexibility and power of Python, you can handle and process many ways your network.
Pypath is available under GPLv3 license. For the git repository, click here.
Forks, pull requests, bug reports and feature requests are welcome!
OS X: Installation on Mac might be challenging, mainly because of cairo. Follow the scripts below, go step-by-step and watch out for errors. We tested these methods on several computers, but every system is different. We appreciate if you report any error you experience, and we will do our best to find a solution. Please contact firstname.lastname@example.org.
For the reference documentation of the pypath module click here.
Find here a comprehensive list of signaling pathway resources.
Pypath allows to access and integrate dozens of bioinformatics resources in an easy way. Using the capabilities of Python you can handle them with a lot of flexibility. Just pop up a Python shell, and type:
Special thanks for Luis Tobalina for providing some of the tutorials.
If you have a question or experiencing issues with the data or pypath please open an issue in the git repo of pypath . We closed our support channel in Google Groups to eliminate the redundancy with the issues on github. If you have a private message which is not of public interest you can send us an email to the address below.
Contact us with private messages at email@example.com. If you have a question or issue which might be of public interest please open an issue on github .
Dénes Türei, Nicolàs Palacio, Olga Ivanova, Saez Lab 2016-2019. Feedback: firstname.lastname@example.org