1. Install Miniconda for all users of your machine - Nucleomics-VIB/16S_analysis_pipeline GitHub Wiki

The default miniconda installation is selfish and located in your home user folder. This is not right if you mean to share the tools with others users, we therefore show here a step by step CLI method to deploy miniconda3 on a linux machine (ubuntu20 in the example)

Note that you could also install it in a docker container and thereby avoid multiuser issues; this will be done later.

method

  • Get the correct miniconda installer shell script from https://docs.conda.io/en/latest/miniconda.html (documentation is also present on that site)

  • run the installer with the following command (you need be sudoer!):

    sudo bash ./Miniconda3-latest-Linux-x86_64.sh -f -p /opt/miniconda3

  • change ownership of the /opt/miniconda3 path recursively to be writable by all users of your machine (in order to later edit it as yourself)

  • add the final activation code block produced by the installer to a system-wide profile file in order for all users to activate conda in each new terminal session

    For ubuntu you can create a startup profile file for that called miniconda3.sh in /etc/profile.d/ and paste the code block into it (sudo!)

an example code block is shown here but use the code produced by your own installer:

  # >>> conda initialize >>>
  # !! Contents within this block are managed by 'conda init' !!
  __conda_setup="$('/opt/miniconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
  if [ $? -eq 0 ]; then
      eval "$__conda_setup"
  else
      if [ -f "/opt/miniconda3/etc/profile.d/conda.sh" ]; then
          . "/opt/miniconda3/etc/profile.d/conda.sh"
      else
          export PATH="/opt/miniconda3/bin:$PATH"
      fi
  fi
  unset __conda_setup
  # <<< conda initialize <<<

  • open a new terminal

  • update the base environment with the command conda update -n base -c defaults conda

  • add a few important channels with conda config --add channels conda-forge r bioconda

  • add a few key packages to your base env with conda install pip mamba

Note: Your base env should now be operational, do not add too many additional packages to it as you may create version bottlenecks, prefer instead creating new environments for each application or pipeline