Anaconda

Anaconda is a distribution of the Python and R programming languages for scientific computing that aims to simplify package management and deployment. Package versions in Anaconda are managed by the package management system conda: an open source, cross-platform, language-agnostic package manager and environment management system that installs, runs, and updates packages and their dependencies.

Please follow the installation steps below to install the latest version of Anaconda on your local machine:

Install Dependencies

sudo apt-get install libgl1-mesa-glx \
    libegl1-mesa \
    libxrandr2 \
    libxss1 \
    libxcursor1 \
    libxcomposite1 \
    libasound2 \
    libxi6 \
    libxtst6

Download Installer

$ wget https://repo.anaconda.com/archive/Anaconda3-2021.05-Linux-x86_64.sh

Run Installer

$ bash Anaconda3-2021.05-Linux-x86_64.sh

Note

Follow the instructions in the terminal regarding your $PATH, default suggestions are fine.

Verify Installation

$ conda -v

Downloading packages

We will be using conda to create environments and install packages within our container.

You can achieve the same results by manually creating a Dockerfile or Singularity definition file, however you must explicitly download and compile every package within the instruction file, which can be extremely tedious. Conda alleviates this problem by pulling packages from the conda repository for you and installing them to the conda environment $PATH.

Creating Environments

The main advantage of conda is that one can create a ‘clean slate’ environment for a project - a directory that contains a specific collection of conda packages you have installed that will not interfere with other environments or your system.

To create a new environment, run the following command:

$ conda create -n test_env

Activate/deactivate the environment using:

$ conda activate test_env

$ conda deactivate test_env

Installing packages

There are 2 ways to install packages using conda:

$ conda activate test_env

$ conda install bioconda::fastqc

Or specify the package version:

$ conda activate test_env

$ conda install bioconda::fastqc=0.11.9

Warning

Be very careful using pinned versions of packages. In some scenarios a pinned package will require outdated dependencies, causing a conflict when compiling the environment.

YAML

The preferred, reproducible method for installing conda packages is to use a YAML file.

See below for a YAML file to recapitulate the test_env we created above:

Note

Delete test_env - we will recreate it using YAML files as a proof of concept: conda env remove --name test_env --all

name: test_env
channels:
 - bioconda
dependencies:
 - fastqc

Save the file and name it environment.yml. Now compile the environment using conda:

$ conda env create -f environment.yml && conda clean -a

$ conda activate test_env

$ fastqc -h

Executable directory

Where have the environments and packages been installed?

The environments are stored under:

$ ls -la ~/.conda/envs/

To take a look at the executables in the test_env environment:

$ ls -la ~/.conda/envs/test_env/bin/

Pip

Need a python head to write this section of the documentation for me. You can install pip and packages via pip in anaconda, but for the python purists out there..