Setup guidelines
Here, you’ll find the guidelines for using the “Introduction to GWAS” module from our genomics app, developed by the Health Data Science sandbox. We build our training modules as Docker images for easy deployment and use. This Docker container includes course tutorials, datasets, and tools for research or self-learning. The genomics app consists of several modules, with each course item built on JupyterLab. JupyterLab is a web-based integrated development environment for Jupyter notebooks, code, and data.
Available material
Items are periodically added to this app and can be accessed differently depending on the platform/system. Each item can be a course, a setup to work with specific software, or a research workflow example. They come with all necessary packages installed, notebooks with computer code and explanations, and a dedicated webpage with additional material (notes, slides, recordings, etc.).
Courses
The available modules are:
| Course name | Description | Links | Programming language |
|---|---|---|---|
| Introduction to NGS data analysis | A one-week course to introduce NGS data, from data alignment to bioinformatics analysis | Webpage | Python, R, bash |
| Introduction to Population genomics | A course introducing and applying bioinformatics tool to perform a whole population genomics analysis | Webpage | bash, R, python |
| Introduction to GWAS | An introductory course in Genome-Wide Association Studies | Webpage | bash, R |
Download the course data and notebooks
Each course is open-source, and the data is freely available. Here is the link to all repositories, where you can download the datasets and the notebooks.
| Course name | Data Repository | Notebooks repo |
|---|---|---|
| Introduction to NGS data analysis | Zenodo Link | GitHub repo |
| Introduction to Population genomics | Zenodo Link | GitHub repo |
| Introduction to GWAS | Zenodo Link | GitHub repo |
Select your system
Select the appropriate system and follow the corresponding instructions: