Posts Tagged ‘cytoscape’

General SPARQL app for Cytoscape

Saturday, March 21st, 2015

We can now easily solve the problem of bioinformatics data integration. But how do we put that data in the hands of scientists?

At General Bioinformatics we put data in triple stores, and use SPARQL to query that data. Triple stores are great for data integration, but you still have to figure out how to put that data in the hands of scientists. Integrating data is only half of the problem, we also have to present that data. The problem isn’t that SPARQL is hard to use per se (it’s really rather plain and sensible). The problem is that SPARQL is supposed to be only a piece of plumbing at the bottom of a software stack. We shouldn’t expect scientists to write SPARQL queries anymore than we expect them to carry adjustable pliers to a restroom visit.

The General SPARQL app is one of the new ways to present triple data.

How do you use it?

The app lets you build a network step by step. Nodes and edges can be added to a network in a piecemeal fashion. Nodes can represent various biological entities, such as: a pathway, a protein, a reaction, or a compound. Edges can represent any type of relation between those entities.

For example, you can start by searching for a protein of interest. The app places a single node in your network. You can then right-click on this node to pull in related entities. For example, all the pathways that are related to your protein. Or all the Gene Ontology annotations. Or all the reactions that your protein is part of. Or the gene that encodes for your protein. And you can continue this process, jumping from one entity to the next.

Watch this screencast and it will start to make sense:

How does it work?

In the background, the General SPARQL app maintains a list of SPARQL queries. Each item in the search menu, and each item in the context (right-click) menu, is backed by one SPARQL query. When you click on them, a query is sent off in the background, and the result is mapped to your network according to certain rules.

When you first install the app, it comes pre-configured with a basic set of SPARQL queries, although it’s possible to provide your own set. The initial set is designed to work with public bioinformatics SPARQL endpoints provided by the EBI and Bio2RDF. But as great as these resources are, public triple stores can sometimes be overloaded. The app works with privately managed triple stores just as well.

Where can I find it?

The easiest way to get the app is simply from the Cytoscape App manager. Just install Cytoscape 3.0, start it, and go to menu->Apps->App Manager and search for “General SPARQL”. Or download it on from the app store website. What’s even better is that the source code is available on github.

Also, if you have a chance, come see my poster at Vizbi 2015 in Boston.

Proxy configuration for Cytoscape

Tuesday, June 11th, 2013

In large companies, you often find that direct web access is blocked: you have to ask a proxy server to request web pages on your behalf (The proxy also does stuff like scanning for viruses and malware). As a consequence, all the software on your computer needs to be configured to be proxy-aware. This is usually done for you, but Bioinformaticians tend to use “non-standard” software that you’ll have to configure yourself.

If you are using Cytoscape 2.X or 3.0 behind a proxy, and you know your proxy settings, you may find the following useful.

Cytoscape has a “proxy server settings” dialog, as described in the manual. The problem is that it doesn’t work – it stores the proxy settings in a special way that only some bits of Cytoscape are aware of. It does not work for plug-ins (sorry, “apps”) that make use of off-the-shelf Java libraries.

Instead, go to your Cytoscape installation directory, and look for a file named Cytoscape.vmoptions. Enter the following lines at the top. Substitute the dummy host ( and port (8080) values for the appropriate values of your proxy.


This method works for Cytoscape internally as well as plug-ins and libraries, so you can just ignore the internal Proxy configuration dialog. I’ve tested this for Cytoscape 2.8.2 and 2.8.3, and it’s also relevant for Cytoscape 3.0. People from the Cytoscape mailinglist inform me that this will be changed in the upcoming Cytoscape 3.1.

I recommend putting the options at the top, because Cytoscape.vmoptions has a maximum of 9 options. Any more are quietly ignored.

In case you want to delete some to make space, I’ll explain the meaning of the default Cytoscape.vmoptions. The first three options increase the memory available to Cytoscape, and are potentially useful to keep if you deal with large networks:


The next two deal with anti-aliasing for font rendering. That’s ancient stuff, I can’t remember the last time I saw a Java application without anti-aliased fonts. I think you can remove them safely, and in the worst case you’ll just get some ugly text.


Finally, a note for Java developers: if you are trying to debug proxy issues, use the following snippet of code just before you make a web request. Sometimes the values of system properties are not what you think they are – with this you can confirm them.

// print out proxy settings for debugging purposes
for (String key : new String[] { "proxySet", "http.proxyHost",
        "http.proxyPort", "https.proxyHost", "https.proxyPort" })
    System.out.printf ("%30s: %40s\n", key, System.getProperty(key));

Notes from Vizbi: automation in Cytoscape

Monday, March 5th, 2012

Cytoscape is a popular network visualisation and analysis tool. It’s great because it’s so easy to create plug-ins. Today I was fortunate enough to be attending the Cytoscape developer workshop at Vizbi 2012, where I learned a few new things.

Firstly, one of my goals was to find out about the current state of Cytoscape development. Cytoscape is a great tool as long as you don’t look too closely at what’s going on inside. The upcoming third version promises to fix all the minor and major problems that exist under the hood. But Cytoscape 3 has been in the making for a long time. As a plug-in developer, you have to choose between something that works right now, but will go away eventually, or something that is clearly the future, but might take a long time to materialise.

The feeling I got from the workshop is that there is light at the end of the Cytoscape 3 tunnel. For a plug-in developer with a deadline, it’s probably best to stick with the current version for now. But if you’re not under pressure to release, it’s definitely possible to write for Cytoscape 3 and make use of a nicer and more pleasant working environment.

Besides that news, I learned some cool new tricks. Using Cytoscape Commands you can write simple macros for repetitive tasks. For example, to generate the network below, first you have to import a SIF (Simple Interaction Format) file, then import a file with node attributes, then apply a layout, and then apply a visual style. If you have to do this a couple of times it gets quite tedious. But here is how all that can be automated:

Take the following SIF data, and save it using a text editor as network.sif

Martijn is_involved_with    LibSBGN
Chaouiya    is_involved_with    SBML-qual
Martijn is_involved_with    SBML-qual
Martijn is_involved_with    BioPreDyn
Emanuel is_involved_with    LibSBGN
Emanuel is_funded_by    Erasmus
Martijn is_funded_by    FP7

Here are the Node attributes, saved it as node_types.txt


For the visual style, I created one in Cytoscape and saved it as style.props, using Export->Vizmap property file. And here is the magic bit: If you save the above three files in your work directory, then you can generate that picture with the script below.

network import file=network.sif
layout force-directed
node import attributes file=node_types.txt
vizmap import file=style.props

Run it from within Cytoscape with Plugins->Command Tool->Run script…, or from the command line with

./ -S scriptfile

Logic modeling with CellNOptR in Cytoscape

Monday, February 27th, 2012

A few months ago, I started work as a post-doc at the Systems Biomedicine group of the EBI. Our group makes heavy use of logical modelling as a means to understand how pathways work. For me, the most interesting thing about logical modelling is that it shows a very dynamic picture of how a pathway changes over time. By comparison, the pictures that you get from WikiPathways are very static.

We have our own logical modelling software called CellNetOptimizer (a.k.a CellNOptR). One of my current projects is to make the CellNOptR software more interoperable with popular tools such as Cytoscape. To this end, Emanuel Gonçalves, a master student in our group, has implemented a plug-in that makes CellNOptR available from Cytoscape. Work on the plug-in is progressing nicely. Below you see the video that he made, to show off some of the features of this new plug-in.

In the video, you see how you can:

  • open a network
  • Start the CellNOptR wizard
  • Import and view experimental data
  • Train the network against the data
  • View the optimized network in Cytoscape