NBIS/ELIXIR-SE Tools for Reproducible Research
Date: 25 - 29 November 2024
Timezone: Stockholm
NBIS / ELIXIR-SE course open for PhD students, postdocs, group leaders and core facility staff at all Swedish universities interested in making their computational analysis more reproducible.
Important dates and information
- Application opens: 2024-08-26
- Application closes: 2024-10-18
- Confirmation to accepted students: 2024-10-25
Course content
This course will introduce best practices in making research reproducible – from code tracking to software packaging and documentation – via short lectures and hands-on tutorials.
Topics covered will include:
- Good practices for data analysis
- Version control and collaborative code development
- Package and environment management
- Workflow management
- Documentation and reporting
- Containerized computational environments
Due to limited space the course can accommodate a maximum of 20 participants. If we receive more applications, participants will be selected based on selection criteria, including (but not limited to) correct entry requirements, motivation to attend the course, as well as gender and geographical balance.
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: This course is led by: John Sundh (CL), Erik Fasterius (CL) Contributors: Estelle Proux-Wéra, Lokeshwaran Manoharan, Tomas Larsson, Cormac Kinsella, Mahesh Binzer-Panchal In case you miss information on any of the above dates, please contact: edu.trr@nbis.se
Keywords: bioinformatics, reproducible research
Venue: SciLifeLab Solna, Air&Fire, SciLifeLab Stockholm
City: Solna
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:
Upon completion of this course, you will be able to:
Organize and structure computational projects
Track changes and collaborate on code using Git
Install packages and manage software environments using Conda
Structure computational steps into workflows with Snakemake and Nextflow
Create automated reports and document their analyses with Quarto and Jupyter
Package and distribute computational environments using Docker and Singularity
Host institutions: NBIS
Target audience: group leaders, PhD Students, postdocs, core facility staff
Event types:
- Workshops and courses
Activity log
