HilbertVis: Visualization of genomic data with the Hilbert curve

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Standalone version: Download and Installation

(for the R package, see here.)

Mailing list for announcements

If you would like to stay informed about new releases of HilbertVis, please subscribe to the (low-volume) HilbertVis announcements mailing list.


Linux and other GNU/Unix systems

Binary files are provided for Linux systems based on Intel/AMD processors. If these do not work for your system, you can also install from source.


Follow these instructions if you have an x86 or x86_64 processor (i.e., a usual PC) with Linux.
  • Step 1: Please install the gtkmm package. On most Unix distributions, you can just use your usual package manager, search for it and select it for installation.

    To save you the searching, here is what you need to do for the most common Linux distributions:

    • Ubuntu Linux: type sudo apt-get install libgtkmm-2.4-1c2a in a terminal window or select libgtkmm-2.4-1c2a in Ubuntu's Synaptic package manager.
    • Redhat, Fedora, and CentOS Linux: Use the Yum package manager to install the gtkmm24 package. You can do this with the graphical tool from the system menu or by typing sudo yum install gtkmm24 in a terminal window.
    • SuSE Linux: Use SuSE's Yast package manager to install the gtkmm2 package.
    • On other Linux distributions, the package has probably a quite similar name.

  • Step 2: Download one of the following two tarballs:

    Usually, you can simply click on the icon of the downloaded file to unpack it. It contains a single file, the executable binary. Copy it to some suitable location (e.g., to /usr/local/bin) and start it with a double-click of by typing hilbertvis.

    Note that these binaries will only run on a reasonably recent version of your Linux distribution (last update after spring 2008). Especially, you will need at least version 2.10 [or 2.14?] of gtkmm-2.4.


[For advanced users]

For the moment, the source code is integrated in the source code of the R package in the Bioconductor SVN repository.

Check out (with SVN)
(no password asked by SVN; for the web interface, use username readonly and password readonly), go into the sub-directory standalone-src and run make.

Before attempting to build, make sure that you have installed the developer version of the gtkmm libraries as described here.


MS Windows

Example data

If you want to try out HilbertVis, you can use the following data:

   MAQ output for the H3K4meX data


  • These files are derived from the raw data described in the 2007 Cell paper by Barski et al. on ChIP-Seq profiling of histone modifications. I have aligned the raw reads (which the authors have deposited in the NCBI Short Read Archive under accession number SRA000206) for the histone modifications H3K4me1 and H3K4me3 with Maq.
  • This is the same data that was used for the ChIP-Seq example plots in the Gallery and the paper.
  • The output from Maq is in the subdirectories H3K4me1 and H3K4me3. These *.map files can be read directly with HilbertVis.
  • The mapping was done with Maq 0.6.3. Hence, when HilbertVis asks whether an old or new Maq version was used, click "Old Maq".
  • Each sub-directory contains the individual Solexa lanes as well as a file merging the reads from all lanes.
  • These are large files. You need enough RAM (4 GB at least, better more) and some patience while loading.

Simon Anders, EMBL-EBI,; last change: 2009-02-12