Software-specific documentation


Singularity is a container technology for HPC. If you’re familiar with Docker, Singularity will seem familiar. Singularity is a fine, but slightly more complicated, alternative to using Conda for managing software.

Singularity 2.6 is already installed and configured on GenomeDK, and you should be able to pull and run containers without any further setup. See the Singularity documentation for more details.


GATK 4 can be installed through Conda with:

$ conda install -c bioconda gatk4

GATK 3 cannot be installed this easily due to licensing restrictions. Instead, you must download a licensed copy of GATK from, for example:

[fe-open-01]$ conda activate myproject
(myproject) [fe-open-01]$ conda install -c bioconda gatk
(myproject) [fe-open-01]$ wget '' -O GenomeAnalysisTK-3.8-1-0-gf15c1c3ef.tar.bz2
(myproject) [fe-open-01]$ gatk3-register GenomeAnalysisTK-3.8-1-0-gf15c1c3ef.tar.bz2

You can now call GATK with the gatk3 command:

(myproject) [fe-open-01]$ gatk3 --help


Different Python versions can be installed through the Conda package manager. For example, for a project that needs Python 2.7, create an environment like this:

$ conda activate
$ conda create -n myproject python=2.7
$ conda activate myproject
$ python --version

If you need Python 3.6 for another project, just create another environment for that project:

$ conda deactivate # exit the myproject environment
$ conda create -n mynewproject python=3.6
$ conda activate mynewproject
$ python --version

Jupyter Notebook/Lab

Install the jupyter package in your environment.

One way to run a Jupyter Notebook on the cluster is to setup an SSH tunnel to the Jupyter instance.

Start an interactive job. Login to the cluster and start an interactive job where the notebook will run.

[local ~]$ ssh <user>
[me@genomedk ~]$ srun --pty bash
srun: job 3597082 queued and waiting for resources
srun: job 3597082 has been allocated resources
[me@node ~]$

Setup SSH tunnel. Back on your local computer open a second terminal to setup the port-forwarding from the computing node to your computer.

[local ~]$ ssh -L<UID>:<compute node>:<UID> <user>

You will need to replace <UID> with your user ID on the cluster, <compute node> with the name of the compute node you have your job on, and <user> with your username on the cluster. You can easily get those values by running following commands on your compute node inside the interactive job you started in the previous step.

[me@node ~]$ echo $UID
[me@node ~]$ hostname -s
[me@node ~]$ echo $USER

Resulting in a command that would look like this:

[local ~]$ ssh -L1234:node:1234

Start the notebook. Back on the computing node start a Jupyter notebook. For this you may have to first unset the environmental variable XDG_RUNTIME_DIR (this could also be included in ~/.bashrc).

[me@node ~]$ unset XDG_RUNTIME_DIR
[me@node ~]$ conda activate <jupyter-env>
[me@node ~]$ jupyter-notebook --no-browser --port=$UID --ip=

Run the notebook. Back on your local computer start a web browser and paste the URL from above. But replace the part in parenthesis with localhost to get:


Cleanup. When finished, remember to log out from both sessions.


RStudio is available on the cluster as a graphical application, which can be run on both compute nodes and the frontend node. Bare in mind, the frontend node must not be used for computation or analysis. RStudio needs X-forwarding to be enabled.

When logged in, you must either activate the environment where RStudio is installed or install it into an environment yourself (see Installing and using software):

[fe-open-01]$ conda install -n my-project rstudio-desktop
[fe-open-01]$ conda activate my-project
(my-project) [fe-open-01]$ rstudio

To run an analysis or computations in RStudio you will need to run RStudio in an interactive job on a compute node.

[fe-open-01]$ srun --mem=4g -c 1 --time=10:0:0 --pty bash
srun: job 3597082 queued and waiting for resources
srun: job 3597082 has been allocated resources
[s03n11]$ conda activate my-project
(my-project) [s03n11]$ rstudio

RStudio is automatically terminated if it allocates more than the reserved 4GB, the 10 hours expires or the connection is lost. So remember to save your work!


As of June 26, 2018 the old Perl module collection present in /com/extra/perl-cpan will not work and support for it has been dropped.

Perl and Perl modules can be installed through Conda, which is also the recommended method. The method described here should only be used in cases where no Conda package exists for the module or it has been decided that Conda should not be used at all. See Installing and using software for help with Conda.

For installation of Perl modules from CPAN a simple command line tool can be installed, and just one command will install it for you.

To start just run:

[fe-open-01]$ cpan App::cpanminus requires configuration, but most of it can be done automatically. If you answer no below, you will enter an interactive dialog for each configuration option instead.

Would you like to configure as much as possible automatically? [yes]
and just answer 'yes'


Warning: You do not have write permission for Perl library directories.

To install modules, you need to configure a local Perl library directory or
escalate your privileges.  CPAN can help you by bootstrapping the local::lib
module or by configuring itself to use 'sudo' (if available).  You may also
resolve this problem manually if you need to customize your setup.

What approach do you want?  (Choose 'local::lib', 'sudo' or 'manual')
here you want local::lib

Autoconfigured everything but 'urllist'.

Now you need to choose your CPAN mirror sites.  You can let me
pick mirrors for you, you can select them from a list or you
can enter them by hand.

Would you like me to automatically choose some CPAN mirror
sites for you? (This means connecting to the Internet) [yes]

For this, just answer yes. Then a lot of output follows, what is actually important is:

local::lib is installed. You must now add the following environment variables
to your shell configuration files (or registry, if you are on Windows) and
then restart your command line shell and CPAN before installing modules:

PATH="/home/xjk/perl5/bin${PATH:+:${PATH}}"; export PATH;
PERL5LIB="/home/xjk/perl5/lib/perl5${PERL5LIB:+:${PERL5LIB}}"; export PERL5LIB;
PERL_MB_OPT="--install_base "/home/xjk/perl5""; export PERL_MB_OPT;
PERL_MM_OPT="INSTALL_BASE=/home/xjk/perl5"; export PERL_MM_OPT;

You need to put these lines into you ~/.bashrc file.

After all that you need to start a new session, and you can install new modules with cpanm command, for example:

[fe-open-01]$ cpanm DBD::mysql
--> Working on DBD::mysql
Fetching ... OK
Configuring DBD-mysql-4.046 ... OK
==> Found dependencies: Test::Deep
--> Working on Test::Deep
Fetching ... OK
Configuring Test-Deep-1.128 ... OK
==> Found dependencies: Test::Tester
--> Working on Test::Tester
Fetching ... OK
Configuring Test-Simple-1.302136 ... OK
Building and testing Test-Simple-1.302136 ... OK
Successfully installed Test-Simple-1.302136
Building and testing Test-Deep-1.128 ... OK
Successfully installed Test-Deep-1.128
Building and testing DBD-mysql-4.046 ... OK
Successfully installed DBD-mysql-4.046
3 distributions installed
[fe-open-01]$ perldoc -l DBD::mysql


TeXLive is available on GenomeDK in the form of TinyTex, which is a stripped down version of TeXLive. See TinyTex for more details.

The conda provided package is for CLI or script usage, the R integration has not been tested and should probably be done using the guide described on the TinyTex home page found above.

To install TinyTex with conda in a new environment:

[fe-open-01]$ conda create <name of project> -c genomedk tinytex

or if you have an existing environment where you want TinyTex installed:

[fe-open-01]$ conda activate <existing project>
[fe-open-01]$ conda install -c genomedk tinytex

Compiling documents is done using the normal TexLive commands, i.e.:

[fe-open-01]$ pdflatex test.tex

To install LaTeX packages from CTAN:

[fe-open-01]$ tlmgr install <package>

Example for installing some packages:

[fe-open-01]$ tlmgr install txfonts enumitem titlesec newpx

Search for packages using tlmgr:

[fe-open-01]$ tlmgr search <package name>

Search for specific file inside package using tlmgr (example):

[fe-open-01]$ tlmgr info t1xtt.tfm

SSH-agent with password protected keys

An SSH agent is a program which caches your decrypted private keys and provides them to SSH client programs on your behalf. In this arrangement, you must only provide your passphrase once, when adding your private key to the agent’s cache. This facility can be of great convenience when making frequent SSH connections.

To avoid problems when running starting new sessions when the ssh-agent is already running, add the following to your .bashrc

if [ ! -S ~/.ssh/ssh_auth_sock ]; then
   eval "$(ssh-agent)"
   ln -sf "$SSH_AUTH_SOCK" ~/.ssh/ssh_auth_sock
export SSH_AUTH_SOCK=~/.ssh/ssh_auth_sock
ssh-add -l > /dev/null || ssh-add ~/.ssh/id_rsa

The above snippet checks if a softlink to the ssh auth socket is valid, if not it will run a ssh-agent process, and save the output thereof. It will then create a softlink to socket, which will be used for the session.

Adjust the last line of the above code to fit the name of your password protected private key.