I assume you just got a fresh clean BCF account to our system. What follows is a step by step guide on how to set up your account to work through our jupyter hub/lab and one or multiple conda environments:

1. ssh into our system
2. you might have to set proxy information

   export http_proxy="http://proxy.computational.bio.uni-giessen.de:3128" && export https_proxy="http://proxy.computational.bio.uni-giessen.de:3128" && export ftp_proxy="http://proxy.computational.bio.uni-giessen.de:3128"

   to be able to connect to the internet

3. install Miniconda3: https://docs.conda.io/en/latest/miniconda.html
   1. using default install prefix is fine
   2. allow conda to initialize your shell, which should be bash
4. either log out and ssh into the system again OR reload environment via

   . ~/.profile

   to let the system know about the newly installed conda.

5. install nb_conda_kernels
   1. create a new subdirectory

      mkdir -p $HOME/Git/Anaconda-Platform

   2. change into this new directory

      cd $HOME/Git/Anaconda-Platform

   3. clone the repository

      git clone https://github.com/Anaconda-Platform/nb_conda_kernels.git

   4. change into the newly cloned directory

      cd nb_conda_kernels

   5. install necessary dependencies and make sure you do so for the system python version

      /usr/bin/pip install traitlets jupyter_client --user

   6. install nb_conda_kernels

      /usr/bin/python3 setup.py develop --user

6. install Qiime2
   1. change into your home directory

      cd

   2. follow https://docs.qiime2.org/2021.8/install/native/#install-qiime-2-within-a-conda-environment
7. install “ggmap”: https://github.com/sjanssen2/ggmap
8. create a jupyter configuration file

   touch `jupyter --config-dir`

   with following content. Should you encounter issues, read up more details at https://github.com/Anaconda-Platform/nb_conda_kernels. Most likely, a subdirectory like .jupyter does not exist yet in your home dir.

   {
     "CondaKernelSpecManager": {
       "kernelspec_path": "--user"
     }
   }

9. in your base environment execute

   /usr/bin/python3 -m nb_conda_kernels list

10. you should be done! Log in to https://www.computational.bio.uni-giessen.de/jupyter/