Prerequisites for the BiATA 2020 MGnify training course

We have modified our in-person training to a virtual training course. The practical sessions are a mixture of web browser based hands-on and exercises using command-line tools. For the web browser hands-on, we are assuming that you have an up-to-date browser, such as Chrome or Firefox. The command-line practical sessions in this course require a basic understanding of the Unix command line and the R statistics package. If you are not already familiar with these then please ensure that you look at these free tutorials before you attend the course:

We will also require you to install and run Docker containers and RStudio Desktop. Below are some instructions for installing the Docker program and containers, and some basic configuration for you to test out. If you face problems, the internet is a great place to find solutions. We will also try to assist during the course.

Install the containers 


All the tools that we are going to use in this course are housed in Docker containers designed for each section. When you download and install the containers all the tools will be installed on your computer and you can use them immediately according to the steps listed in the following sections. For this you need sufficient RAM, 15 GB of free storage in your computer, and have admin permissions.

Downloading the Docker Program 

To use the container, you first need to download the Docker program by following these steps:

For Mac users:

  1. Download the program from this link:
  2. Follow the instructions listed in the aforementioned link. Basically, open the downloaded image disk and drag the whale icon to the Applications folder.
  3. Open the Docker icon to start it and authorize its use.
  4. After completing the previous steps you can start using Docker from the Terminal.

For Ubuntu users:

  1. Open the terminal and download the script as follows:
    curl -fsSL -o

  2. Run the script. For this you must have sudo or root permissions:
    sudo sh

  3. The program is installed and ready for use in DEB distributions. In RPM distributions you must use the systemctl or service command.

For other installation options, see

Next: Test running a container and opening a window 

To download the container from docker hub, run the following command in the terminal.

docker pull pegi3s/fastqc

 After the download has finished, run the following commands:

 xhost +

This should result in something like the following being printed in the terminal.

access control disabled, clients can connect from any host

On a Mac, you may need to modify your X11 preferences via the Quartz application:


To run the fastq container you will need to choose the appropriate command according to your operating system.

MacOS X:

docker run -it -d --rm -v /tmp/.X11-unix:/tmp/.X11-unix:rw --privileged -e DISPLAY=docker.for.mac.localhost:0 \
           --device /dev/dri --privileged --name fastqc pegi3s/fastqc


docker run -it -d --rm -v /tmp/.X11-unix:/tmp/.X11-unix:rw --privileged -e DISPLAY=unix$DISPLAY --device /dev/dri \
           --privileged --name fastqc pegi3s/fastqc

Regardless of the command, you should see a window similar to this appear:

The following two commands are useful.

docker ps

This list the current docker containers that are running

docker image list

This command lists all of the container images that have been built on this machine.

If for some reason you need to completely eliminate the container you must run the following commands. The value of CONTAINER_ID can be obtained by running the docker ps command. In the first column CONTAINER_ID you will see an alphanumeric string that you must copy to this field. The value of IMAGE_ID can be found by running the docker image list command. 

docker kill CONTAINER_ID
docker rmi IMAGE_ID

Verify that the container is not present by running the commands again:

docker ps

docker image list



You will also need to install RStudio Desktop – see here for instructions