NBIS/ELIXIR-SE Tools for Reproducible Research
Date: 22 - 26 April 2024
Timezone: Stockholm
Duration: 5 days
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 organizes their work with reproducibility in mind will quickly realize the immediate personal benefits: an organized and structured way of working. The person that most often has to reproduce your own analysis is your future self!
Important dates and information
Application opens: 2024-02-19
Application closes: 2024-03-18
Confirmation to accepted students: 2024-03-22
Course fee
A course fee* of 3000 SEK will be invoiced to accepted participants. The fee includes lunches, coffee/tea and snacks as well as a course dinner.
*Please note that NBIS cannot invoice individuals
Contact: To contact the course providers, please send a mail to the follow address: edu.trr@nbis.se.
Venue: Air&Fire, SciLifeLab Stockholm
City: Stockholm
Country: Sweden
Prerequisites:
The following is a list of skills required for being able to follow the course and complete the exercises:
- Familiarity with using the terminal (e.g. be familiar with commands such as ls, cd, touch, mkdir, pwd, wget, man, etc.)
- Some knowledge in R and/or python is beneficial but not strictly required
Learning objectives:
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 Singularity to distribute containerized computational environments
Event types:
- Workshops and courses
Activity log
