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GAMAviewer: a tool for combined visualization of genome annotation and microarray data

Introduction

GAMAviewer is a Java-based software tool for the simultaneous visualization of annotated genome features and functional genomics data, particularly microarray data. This tool is largely based on the Artemis genome annotation tool developed at the Sanger Centre [web page; publication].

System requirements

GAMAviewer requires a recent verion of Java.

  • UNIX and Windows users should get the latest Java version from the Sun JDK download page.
  • GNU/Linux users should install the Blackdown.org latest Java release.
  • MacOSX comes complete with a suitable version of version of Java so GAMAviewer should work "out of the box". MacOS prior to OSX is not supported.

Distribution

The current release of GAMAviewer can be downloaded as a JAR file. GAMAviewer is free software and is distributed under the terms of the GNU General Public License.

During the download, some browsers on certain systems will automatically give this file a .zip extension instead of the .jar extension that it should have. This can be corrected by changing the extension of the downloaded file from GAMAviewer.zip to GAMAviewer.jar.

Download GAMAviewer

Demo files

Genome file: B. bronchiseptica RB50 (determined by Parkhill, et al.)
Microarray data: Bordetella CGH data (excerpted from Cummings, et al.; gzip compressed)

Running GAMAviewer

If Java is properly installed, GAMAviewer can be launched simply by double-clicking its icon. You may find that the program runs very slowly or hangs when loading a large dataset. This is due to insufficient memory allocation to the Java Virtual Machine. If you run into these memory issues you should increase the memory available to the JVM by making the changes suggested at the Artemis FAQs page.

In order to map microarray data to genome features, you will need to provide an identifier in the data file that matches a unique identifier in the annotation. For example, rows of the microarray data file could be indexed by the values of the 'locus_id' or 'gene' tags of their corresponding features. If multiple rows of the microarray data file map to a single feature, the values are averaged for display. This behavior may not be desired, especially if multiple independent probes represent each feature. If the goal is to map data to individual probes, the solution is to create a feature table describing the coordinates of each probe, read this entry into GAMAviewer, then map the microarray data to the probes via a unique probe identifier.

  1. When the exectuable JAR file is launched, the first menu window opens.
  2. Use the File menu to select a sequence file, which can also contain annotation (e.g., EMBL file).
    The BB.art genome file, which can be downloaded above, may be used as a demo.
  3. After the sequence is loaded, the main window opens. The functions in the menus of this window are largely inherited from Artemis.
  4. At this point, additional annotation may be loaded as "entries" using the "File->Read an entry" dialogue in the menu. For example, one could load the coordinates of their microarray probes for visualization on the genome. If microarray data is to be mapped to a different entry, that entry should be loaded before proceeding.
  5. To load microarray data, select "Load microarray data..." from the File menu.
    1. When prompted for the name of the entry to map microarray data to, select the appropriate entry.
      If using the Bord_CGH.tab file as a demo, map it to the BB.art entry.
    2. When prompted for the microarray data file select it.
      The Bord_CGH.tab file, which can be downloaded above, may be used as a demo.
    3. When prompted for the name of the column in the microarray file to be used for mapping, select it from the pulldown menu.
      For the demo file, select UNIQID.
    4. When prompted for the name of the annotation field to be used for mapping, type it in the box. This will often be 'gene', 'label', or 'locus_tag' for an annotated genome file.
      If using the demo files, enter 'gene'.
    5. A new pane depicting the microarray data will be added to the main window.
  6. Feature selection:
    • Double clicking on a vertical column in the microarray data selects the corresponding feature and displays the full annotation of that feature in the pane below the microarray data.
    • Double clicking on a feature selects the corresponding column of data.
  7. Microarray display settings can be adjusted using the control panel in the Settings-->Pixel settings menu.
Because GAMAviewer is basically a modification of Artemis, much of the information in the Artemis documentation, including the installation instructions also applies to this application.

Mailing list

Bug reports, help requests, comments, and contributions may be submitted by joining the gamaviewer-users mailing list. You may subscribe by sending an e-mail to majordomo@lists.stanford.edu with the text "subscribe gamaviewer-users".

Contact information

For comments or assistance, e-mail Craig Cummings at craigc@stanford.edu.

Authors

Acknowledgements

GAMAviewer employs open source code from Artemis and Java Treeview. Development of GAMAviewer was supported by the Stanford University Office of Technology and Licensing and the National Institute of Allergy and Infectious Diseases (5R21AI057188).