Course overview

Course website Links to an external site.

GitHub repository Links to an external site.

7 - 11 April 2025

SciLifeLab Stockholm, Sweden Links to an external site.

One of the key principles of proper scientific procedure is the act of repeating an experiment or analysis and being able to reach similar conclusions. Published research based on computational analysis (e.g. bioinformatics or computational biology) have often suffered from incomplete method descriptions (e.g. list of used software versions); unavailable raw data; and incomplete, undocumented and/or unavailable code. This essentially prevents any possibility of reproducing the results of such studies. The term “reproducible research” has been used to describe the idea that a scientific publication should be distributed along with all the raw data and metadata used in the study, all the code and/or computational notebooks needed to produce results from the raw data, and the computational environment or a complete description thereof.

Reproducible research not only leads to proper scientific conduct, but also enables other researchers to build upon previous work. Most importantly, the person who organises their work with reproducibility in mind will quickly realize the immediate personal benefits: an organised and structured way of working. The person that most often has to reproduce your own analysis is your future self!

Course content and learning outcomes

The following topics and tools are covered in the course:

• Data management
• Project organisation
• Git
• Conda
• Snakemake
• Nextflow
• Quarto
• Jupyter
• Docker
• Apptainer

At the end of the course, students should be able to:

• Use good practices for data analysis and management
• Clearly organise their bioinformatic projects
• Use the version control system Git to track and collaborate on code
• Use the package and environment manager Conda
• Use and develop workflows with Snakemake and Nextflow
• Use Quarto and Jupyter Notebooks to document and generate automated reports for their analyses
• Use Docker and Apptainer to distribute containerized computational environments

Application

This is an NBIS / Elixir course. The course is open for PhD students, postdocs, group leaders and core facility staff. International applications are welcome, but we will give approximately half of the participant slots to applicants from Swedish universities, due to the national role NBIS plays in Sweden.

The only entry requirements for this course is a basic knowledge of Unix systems (i.e. being able to work on the command line) as well as at least a basic knowledge of either R or Python.

Due to limited space the course can accommodate maximum of 20 participants. If we receive more applications, participants will be selected based on several criteria. Selection criteria include correct entry requirements, motivation to attend the course as well as gender and geographical balance.

Please note that NBIS training events do not provide any formal university credits. The training content is estimated to correspond to a certain number of credits, however the estimated credits are just guidelines. If formal credits are crucial, the student needs to confer with the home department before submitting a course application in order to establish whether the course is valid for formal credits or not.

Course fee

A course fee of 3000 SEK will be invoiced to accepted participants. This includes lunches, coffee and snacks, and course dinner. Please note that NBIS cannot invoice individuals

Course material

All of the material for this workshop can be found at the course website Links to an external site., including both lectures, tutorials and other information.

Contact

To contact us, please send a mail to the follow address: edu.trr@nbis.se.