Log out and log in to Elja again. Your conda is now ready.
Create environments (and install packages):
This will create an environment called “env_mimir” and install bowtie2 (and some dependencies). All binaries go into /hpcdata/Mimir/<uname>/env_mimir
When installation is complete activate your environment:
This environment contains bowtie2:
You can install additional packages into this environment:
After the installation the environment contains macs2 in addition to bowtie2:
To leave the environment type:
You can always start a new environment and install different packages into it, e.g.:
This allows you to have separate environments for different tasks.
If you are not using a particular environment anymore please remove it like this:
This removes the installed binaries, and saves up space for other users.
A specialized version of Python - Biopython - is available for use on Elja. The base version of Python is 3.9.6. It includes pip 21.2.2.
In order to install your own Python packages with pip the flag --user must be included to install the packages locally (in your homespace), for example:
The Python package alfpy is installed, and is located in /users/home/<uname>/.local/lib/python3.9/site-packages/:
Mimir users! It is recommended that the user creates a directory called “.local/R/library” in their /hpcdata/Mimir/<uname> directory.
and uses this directory to install additional R packages via CRAN. For R packages installed with release binaries (.tar.gz files for example), another directory is created:
To make use of these directory it is further recommented to create a small bash script (for example .bashrc_R) which includes these lines:
Sourcing this bash script loads in the R module, and appends your local directory to the R-library list.
The ordering of the library paths is important, since it will first look in your local libraries when loading an R packages.
To install a package via CRAN to this library type, for example :
To load the package type:
To install R packages from a source directory (release binaries), we first download the package. For example:
Run the command below to install the package to your “R_libs” directory. If we do not specify the path, installation will fail since by default the package will be installed in root directory which you do not have write priviliges to.
Open the R console and load the package with the following command: