2. Configuring NeSI

Here we assume you created an NeSI account and you have a project allocation and an project code.

First, we need to configure NeSI in a way that we can run Snakemake on Mahuika (the cluster we are going to use for our analyses). This involves two steps:

  1. Load the conda module
  2. Install Snakemake into an environment


As of June 2019 a Snakemake module exists on NeSI that we can simply load with module load snakemake/5.5.0-gimkl-2018b-Python-3.7.3. Once loaded, the steps below are not needed anymore. They are still displayed here in case you need a particular Snakemake version installed.

2.1. Loading a module

A module on the cluster includes a software package into our path so that we are able to make use of the software. To load a module on the command-line, you only need to type:

$ module load Miniconda3/4.4.10

Once executed, the conda command should be readily available to you.

2.2. Installing Snakemake


Snakemake has now been installed as a module. If yopu are ok with the version you can just use module load snakemake/5.5.0-gimkl-2018b-Python-3.7.3 instead of the above process.

We will be using the workflow management software Snakemake here. We will create and activate a conda environment for Snakemake:

$ conda create -n my-base snakemake>5.5.0
$ conda activate my-base

Conda will create a .conda folder in your home directory and store environments in .conda/envs by default.

Install conda channels to be able to search for bioinformatics software:

$ conda config --add channels defaults
$ conda config --add channels bioconda
$ conda config --add channels conda-forge


On your own system you probably would install Snakemake in the base conda environment and not create a new environment specifically for Snakemake. However, on NeSI we are not allowed to write into the directory of the base environment, hence we create a new one.