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
To save you the searching, here is what you need to do for the most common Linux
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
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.
Step 1: Please install the GTK+/gtkmm framework by
downloading it from the following location: GTK+ with gtkmm for Mac, version 2.14.X11
Simply double-click on the downloaded file to start the automatic installer.
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
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
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.