Tools for Reproducible Research


National course open for PhD students (prioritized), postdocs, researchers and other employees within all Swedish universities with interest in making their computational analysis more reproducible.

Apply here

Course homepage

Important dates

Application opens:  2018-09-01

Application closes: 2018-10-26

Confirmation to accepted students:  2018-11-09

Responsible teachers:  Rasmus Ågren (rasmus.agren@scilifelab.se) and Leif Wigge (leif.wigge@scilifelab.se)

If you do not receive information according to the above dates please contact:  Rasmus Ågren

Course fee

A course fee* of 1300 SEK will be invoiced to accepted participants. This includes lunches, dinner, coffee and snacks.

*Please note that NBIS cannot invoice individuals

 

Course content

In this course you will learn how to make your data analyses reproducible.

 

In particular, you will learn:

  • good practices for data analysis
  • how to use the version control system git to track edits and collaborate on coding
  • how to use the package and environment manager Conda
  • how to use the workflow manager Snakemake
  • how to use R Markdown to generate automated reports
  • how to use Jupyter notebooks to document your ongoing analysis
  • how to use Docker to distribute containerized computational environments

Entry requirements

Required for being able to follow the course and to complete computer exercises:

  • familiarity with using the terminal (e.g. be familiar with commands such as ls, cd, touch, mkdir, pwd, etc.)
  • bring your own laptop running Linux or Mac OS (if you run Windows and are interested in participating, please contact the course leaders by email, see above, before applying)
  • some knowledge in R and/or Python is beneficial but not strictly required