Programming & Workflows
Introduction to Linux for bioinformatics
Trainer: Christof De Bo
Goal
After this training you will:
- feel comfortable using Linux
- know how software works on Linux and how to use it
- use bash to execute commands in Linux and know your way around the file system
- have an overview of Linux tools that are extremely useful for bioinformatics
Summary
This training is intended for all Linux novices who want to learn the basics of Linux without getting too much technical details. This hands-on session will show you how to effectively use Linux, a free operating system. Bioinformatics depends heavily on Linux-based computers and software. A lot of good scientific software is written specifically for Linux/Unix. Additionally, Linux has most popular programming languages (e.g.Python, Perl, C) already installed and ready to use! Data management happens swiftly with the dedicated text manipulation tools and file system properties. This training will teach you all you need to know to swiftly start using Linux, be it on the server of your department, or on your own computer (even if you're already running Windows or Mac OS).
Prerequisites
No skills required.
Gentle hands-on introduction to Python programming
Trainers: Nina Buchina, James Collier
Goal
Learning the basics of Python programming: different variables, reading files, writing files, conditional statements
Being able to write a basic Python script from scratch
Summary
This course is organised over two full days. With the help of plenty hands-on exercises, you will get introduced into the different types of variables in python, the peculiarities of python and good programming habits. This course will provide you an ideal stepping stone for further developing programming skills in Python.
Prerequisites
Aimed for people with no programming skills whatsoever.
Python for downstream data analysis
Teacher: James Collier
Goals
- Use libraries for advanced data manipulation and visualization
- Working with biological data using Biopython
- Being able to write scripts and functions from scratch for specific bioinformatics problems
Required skills
If you have no experience with Python you should follow our Python introduction course.
Docker and Singularity for reproducible and automated data analysis
Teacher: Alexander Botzki
Material https://elearning.bits.vib.be/courses/introduction-to-docker/
Goals
- Learn the concept of and the difference between Docker & Singularity containers
- Write a Docker recipe, build and run a Docker image and containers
- Pull and push Docker container to / from Docker hub
- Docker files and layers; Docker cashing
- Working with volumes
- Build Singularity images from Docker images
Required skills
If you have no experience with command line you should follow our Linux initiation training.
Nextflow for reproducible and automated data analysis
Teacher: Tuur Muyldermans, Steff Taelman
Goals
- Understand Nextflow's basic concepts: channels, processes, modules, workflows, etc.
- Write and run a Nextflow pipeline
- Write and modify config files for storing parameters related to computing hardware as well as pipeline dependent parameters
Required skills
If you have no experience with command line you should follow our Linux initiation training.
If you have no experience with Docker you should follow our Docker training.
Introduction to Git & GitHub
Teacher: James Collier
Goals
Get you started with Git from zero. We'll explore Git on the command-line and its interaction with GitHub.
- Introduction, set-up & configurations
- Working locally: Create a repository, clone, edit, staging commits, commit & push
- Working with your history & logs
- Working in a project: Forking, branching & pull requests
- How to version control your code in RStudio with GitHub
- How to set up a collaboration project