Cytoscape 3.2.1 User Manual

Overview

A Cytoscape App for Cancer Biomarker Identification Using Network Constrained Support Vector Machines (2) 1409 downloads Cyni Toolbox: Cytoscape Network Inference Toolbox puts together several tools that allow infering networks from bio data (For Cytoscape 3.1+) Cyni Toolbox: Cytoscape Network Inference Toolbox puts together several tools that. I have to use Cytoscape on a regular basis. One problem I face often is that I have to color the nodes individually. It is not possible to select multiple nodes and color them at one go.Are there any plugins available for this purpose or is there a way around this problem? Kindly let me know if there are any other network biology software which can support this kind of thing.

This step describes the process of installing the latest release of Cytoscape.

Prerequisites

Cytoscape is a Java application verified to run on the Linux, Windows, and Mac OS X platforms. Although not officially supported, other UNIX platforms such as Solaris or FreeBSD may run Cytoscape if Java version 7 or later is available for the platform.

The system requirements for Cytoscape depend on the size of the networks you want to load, view and manipulate.

Note that as of Cytoscape v3.2, networks are loaded faster and in less memory than with previous versions. While this is good news, networks created on v3.2 on a given memory configuration (e.g., 1GB) may not be loadable by prior Cytoscape versions on the same memory configuration.

Component	Small Network Visualization	Large Network Analysis/Visualization
Processor	1GHz	As fast as possible, with multiple cores
Memory	512MB	2GB+
Graphics Card	Integrated video	High-end graphics Card
Monitor	XGA (1024X768)	Wide or Dual Monitor

Specific system requirements, limitations, and configuration options apply to each platform, as described in the Release Notes available on the Cytoscape website.

Process

Install Java

Cytoscape requires Java 7 or later.

You need to install Java Development Kit (JDK), instead of JRE.
While Cytoscape versions prior to v3.2 run on Java 6, Oracle and other JVM suppliers have dropped Java 6 support. Consequently, Cytoscape v3.2 and later don't support Java 6 either.
We recommend a 64 bit JDK. While Cytoscape runs with 32 bit Java versions, using a 64 bit Java allows the largest networks to be loaded and enables the fastest network processing. For Windows, the default JRE download provided at java.com is 32 bits regardless of the Windows version. While Cytoscape will run with a 32 bit JRE, it will be limited to loading only small networks.
Cytoscape 3.2.1 and later versions fully support Java 8. We currently recommend Java 8 because Java 7 will not be supported by Oracle after April, 2015. Java 8 Oracle distribution can be found here.

For additional information, select the Release Notes button on the Cytoscape web site (http://cytoscape.org).

Install Cytoscape

Downloading and installing

There are a number of options for downloading and installing Cytoscape. See the download page at the http://cytoscape.org website for all options.

Automatic installation packages exist for Windows, Mac OS X, and Linux platforms -- best for most users.
You can install Cytoscape from a compressed archive distribution.
You can build Cytoscape from the source code.
You can check out the latest and greatest software from our Git repository.

Cytoscape installations (regardless of platform) containing the following files and directories:

File/Directory	Description
`p/Cytoscape_v3.2.0`	Cytoscape program files, startup scripts, and default location for session files
`p/Cytoscape_v3.2.0/Cytoscape.vmoptions`	Cytoscape memory configuration settings
`p/Cytoscape_v3.2.0/sampleData`	Preset networks as described in the embedded README.txt file
`p/Cytoscape_v3.2.0/framework`	Cytoscape program files
`u/CytoscapeConfiguration`	Cytoscape properties and program cache files
`u/CytoscapeConfiguration/cytoscape3.props`	Cytoscape configuration settings

The p/ directory signifies the program directory, which varies from platform to platform. For Cytoscape to work properly, all files should be left in the directory in which they were unpacked. The core Cytoscape application assumes this directory structure when looking for the various libraries needed to run the application.

The u/ directory signifies the user's home directory, which varies from user to user and from platform to platform. To change the user home directory from the default, one can set the Java environment variable user.home to the desired directory -- this is useful when Cytoscape is installed on a workstation, but the home directory is stored on a central file server. user.home can be set by adding the following option to the Cytoscape.vmoptions file or the _JAVA_OPTIONS environment variable, substituting the desired path as appropriate:

-Duser.home=/path/to/desired/home

Your operating system may have other mechanisms for setting environment variables -- see your operating system documentation for further details.

A note on upgrading your Cytoscape installation

If you have a previous Cytoscape installation you have two options:

Starting with a clean slate. For this you should delete your previous installation directory and the CytoscapeConfiguration directory (see below for the location of this directory).
Just keep what you have and simply pick a distinct, new directory for installation of the latest version. In the unlikely event that you should encounter any problem, delete the .props files in your CytoscapeConfiguration directory. If that doesn't help try deleting the CytoscapeConfiguration directory. This latter step will cause you to lose all of the apps that you have installed via the App Store, so only do that if you are having problems or if you don't mind reinstalling your apps. The core apps will not be affected by this step.

Launch the application

As with any application, launch it by double-clicking on the icon created by the installer, by running cytoscape.sh from the command line (Linux or Mac OS X) or by double-clicking cytoscape.bat or the Program Launch icon (Windows).

Note on Memory Consumption

For most regular users, Cytoscape will estimate and reserve the proper amount of memory. An incorrect estimate may result in Cytoscape hanging at startup or Cytoscape being unable to load your network. Unless Cytoscape fails to start or open your network, it has likely estimated the available memory correctly. If Cytoscape misjudges the memory size or can't allocate enough memory, it could be that you're running with a 32 bit JRE and could get better results by installing a 64 bit JRE -- see the above.

When Cytoscape starts, it displays the current memory usage in the lower right corner of the main interface. You can click on the Memory button at any time to access an option to Free Unused Memory. While most users won't need to use this option, it can be useful for users who have multiple large networks loaded.

Overall Memory Size for Cytoscape

By default, Cytoscape uses an estimate for initial and maximum memory allocation based on your operating system, system architecture (32 or 64 bit), and installed memory. You can change Cytoscape's initial and/or maximum memory size by editing the Cytoscape.vmoptions file, which resides in the same directory as the Cytoscape executable. The file contains one option per line, with each line terminated by a linefeed, and an extra linefeed at the end of the file. Note that for the MacOS platform, the situation is slightly different -- if you are launching Cytoscape by clicking on the Cytoscape icon, you must edit the .../Cytoscape.app/Contents/Info.plist file instead.

For example, if you want Cytoscape to initially allocate 2GB of memory and use up to a maximum of 4GB, edit the Cytoscape.vmoptions file to contain the following lines (... do not forget the linefeed at the end of each line, and an extra linefeed at the end of the file!):

-Xms2GB

-Xmx4GB

Stack Size

Cytoscape 3.7.1

There is one more option related to memory allocation. Some of the functions in Cytoscape use larger stack space (a temporary memory for some operations, such as Layout). Since this value is set independently from the values above, sometimes layout algorithms fail due to an out of memory error. To avoid this, you can set larger heap size for Cytoscape tasks by using the taskStackSize option in the cytoscape3.props file (located in the CytoscapeConfiguration directory). This can be edited within Cytoscape using the Preferences Editor (Edit-Preferences-Properties...) - look for taskStackSize. The value should be specified in bytes.

Cytoscape Manual

MetScape App for Cytoscape: Creating and Viewing Correlation Networks

NARRATOR: Hello, my name is Marci Brandenburg, and I am the Bioinformationist at the University of Michigan Taubman Health Sciences Library. Today, we learn about building correlation networks using MetScape, a Cytoscape app. MetScape can be used to visualize and interpret metabolomics and expression profiling data in the context of human metabolic networks. It can be used to visualize compound networks and display related information about reactions, enzymes, and pathways. Although not covered in this tutorial, you can also use this app to view pathway-based networks. MetScape uses data from the Edinburgh Human Metabolic Network and KEGG Compound Database. This image shows you the various workflows included in this app. This tutorial will focus on the correlation calculator and correlation networks. Currently, between 40% and 60% of experimentally measured compounds can be mapped to canonical metabolic pathways when using untargeted assays. For those compounds that do not map to a pathway, correlation-based networks are useful. For this tutorial, I will be using Cytoscape version 3.2.1 and MetScape version 3.1.1.

To install the MetScape app, you can find MetScape on the Cytoscape App Store webpage and click the Install button, or use the App Manager directly in the Cytoscape software. For this tutorial, I will use the App Manager in the Cytoscape software. First, open Cytoscape and go to the Apps Menu. Choose the first option, “App Manager”. An App Manager window should now appear. In the search box, enter “MetScape”. MetScape should now appear in the second column. Click on MetScape and then click on “Install” at the bottom of the window. Installation of the app will now occur. Once the app is successfully installed, it will appear in the Apps Menu.

The first time you open MetScape, a registration page will appear. This is a one-time, free registration.

Correlations are measures between pairs of metabolites. The Correlation Calculator is a standalone Java application that provides methods of calculating pairwise correlations among repeatedly measured entities. It is designed for use with quantitative metabolite measurements, such as Mass Spectrometry data, on a set of samples. The workflow allows inspection and/or saving of results at various stages, and the final correlation results can be dynamically imported into version 3.1 or higher of MetScape as a correlation network. This chapter will cover the Correlation Calculator.

The Correlation Calculator can be downloaded from the MetScape website. The input data file is a CSV file that contains a table of measurements across multiple samples. Although metabolites must be labeled, sample labels are optional. Samples may be in rows or columns.

After launching the calculator, click the Browse button. Select the appropriate data file and click Open. This data file includes labeled samples in rows, so I will make sure that Samples Labeled is checked and Samples in Rows is selected. Next, under Data Normalization, select Log2-Transform Data and Autoscale Data. Under Normalize Data, click Run. Click View Normalized Data to view the results. To save the data, click the Save button. If the data are already normalized before loading it into the calculator, this normalization step can be skipped. Now, I will use Pearson’s Correlations to filter out metabolites; this step is optional. To use Pearson’s Correlations, click Run under Calculate Pearson’s Correlations. You can click View Histogram to view a histogram of the maximum Pearson’s Correlation by metabolite. You can click View Heatmap to view the results as a heatmap. The View CSV File and Save buttons can be used to perform these functions.

The slider and text fields can be used to filter metabolites to those with correlation coefficients within a specified range. The last step is to use a Partial Correlation Method, either Debiased Sparse Partial Correlation or Basic Partial Correlation. I will select Debiased Sparse Partial Correlation, or DSPC, and then click Run. The Correlation Calculator calculates the partial correlation values, p-values, and q-values for each compound pair. You can click the View CSV File and/or Save buttons to perform these functions. You can click View in MetScape to view the correlation network in MetScape, where interactive visualization and exploration can be performed.

To learn more about the correlation network in MetScape, please refer to Chapter 6.

This portion of the tutorial will cover the data file formats for building a correlation network in MetScape. Two types of data file formats are accepted. The first data file format is column-based; this is the recommended format. The first row of the column-based file must have column headings of the user’s choosing. The first two columns must contain metabolite names or ids. Additional columns contain values, such as p-values and correlation values.

The second data file format is a matrix format, where the first row and first column contain metabolite names, and the rest of the rows and columns contain correlation values.

The next chapter will discuss building a correlation network in MetScape.

To build a correlation network using MetScape, go to the Apps menu and click on MetScape. You will get a menu of options. Select “Build Network” and then “Correlation-based.” Now a MetScape tab displays on the left side of your screen, in the Control Panel. Under the Input section, click the Select button. Select the location of the correlation file and click Open. A new window will appear showing potential matches, found in the MetScape database, for each compound in the input file. Use the dropdown arrows for each compound to choose the best match. If the compound is not found in the system, it will say “Not Found.” Your mapping selection will be saved, so that it will appear as the default option in the future. Next, select OK.

Under Edge Mapping, use the dropdown menu next to “Base Edges on” and select the appropriate column from your data file. For today’s example, I will select the correlation values column, labeled pcor. I will then use the dropdown menu next to Tooltip Labels and select the p-values column, labeled pval. This will allow me to see the p-values by simply mousing over an edge in the built network.

Loading a Group Definition file is optional. This is a simple 2-column file with metabolite names in the first column and group names in the second column. Group names can be anything that you choose. For today’s example, I will not load a Group Definition file.

Under Range for Edges, I can drag the blue arrows to filter the range. For this example, I will use the full range of values, negative 1 to 1. Below the edge range is the number of edges and nodes that will be in the built network. Next, I will click “Build Network”.

To learn more about the correlation network in MetScape, please refer to Chapter 6.

The MetScape correlation network consists of nodes of varying colors, and edges of varying colors and widths. To view a legend, go to the Cytoscape Apps Menu, go down to MetScape, and select Show Legend. The purple hexagons represent compounds that mapped to a known compound in the MetScape database. The white hexagons represent compounds that did not map to a known compound in the MetScape database. Pink edges represent a positive correlation, while blue edges represent a negative correlation. The thicker the edge, the stronger the correlation.

For more information, here are two citations for articles published on MetScape. In addition, there is a MetScape webpage that contains a user manual and additional videos on using MetScape. I would like to acknowledge the following people and organizations for their contributions to this tutorial.