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Bioweek 2017 R intro

Bioweek: Introduction to base R
Date: 05.02.2018 9:00 - 05.02.2018 17:00
Location details: The event is organised at the CSC Training Facilities located in the premises of CSC at Keilaranta 14, Espoo, Finland. The best way to reach us is by public transportation; more detailed travel tips are available.
Language: english-language
lecturers: Seija Sirkiä Maria Lehtivaara
  • 60 for-finnish-academics
  • 280 for-others
The fee covers all materials, lunches as well as morning and afternoon coffees.
The seats are filled in the registration order. If a cancellation is received five (5) business days prior to the course, the course fee will be refunded with the exception of a handling fee of 10 €. For no-shows and cancellations after the cut of date no refunds will be made. Registration can be transferred to someone else from the same organization without additional charge.

Payment can be made with electronic invoicing, credit card, or direct bank transfer. Note that for electronic invoicing you need the operator and e-invoicing address (OVT code) of your organization. Please also note that invoice reference is needed for electronic invoicing in your organization, so please have this available when registering.
Additional Information

R is a language and an environment that has become one of the most popular tools for data analysis. There are plenty of online courses and other learning material available but the learning curve can still be rather steep, especially for people with no experience in programming. This course aims to help with this initial difficulty, so that further learning using other sources becomes possible.

Who should join this course?

The whole content of the course day is available as Jupyter notebook at The notebook is a standalone interactive document that you can use for learning the whole content of the course day on your own. A non-interactive pdf version is also provided for review. Please take a look at either the pdf or try the notebook. See directions for starting the notebook below. If the contents seem easy you will probably find the course very easy as well. In that case consider working through the notebook, or any other online course, on your own time. If on the other hand it looks like the notebook would pose a challenge, or while trying to work through it you run in to problems, then the course should prove useful.


No programming background using R or any other language is expected. General IT knowledge and skills in working with files etc. should be enough.

Learning outcomes

After the course the participant should be able to understand R syntax, read in data and perform preliminary analyses on it. Most importantly the participant is prepared to start learning proper data analysis and wrangling with ease.

Directions for starting the notebook

The Jupyter notebook for the course is used through a web browser. To reach it, follow these steps:

  1. Go to and log in using the Haka authentication. If you do not have a Haka account and password, please contact the course staff.
  2. Find the course blueprint titled "R for beginners" in the Blueprints dashboard, and click on "Launch new".
  3. Wait a moment for the virtual machine to start: click on "Open in browser" once the link appears.
  4. Your browser should open a new tab with Jupyter home: click on the R-for-beginners folder and then on the baseRintro.ipynb file
  5. Your browser should now open the notebook in a new tab and you can start working on it. Further instructions are given in the notebook itself.


…is a weeks worth of courses assembled especially with bioscientists in mind. Participate in all of them, or just pick the ones you find most interesting!

5.2. Introduction to base R

6.2. Data visualisation using RStudio and ggplot 

7.2. Computing intensive bioinformatics analysis on Taito  

8.2. Using cPouta cloud in bioinformatics 

9.2. Single cell RNA-seq data analysis using Chipster 


9:00-10:30 Lecture & exercises

10:30-10:45 Coffee break

10:45-12:15 Lecture & exercises

12:15-13:00 Lunch break

13:00-14:30 Lecture & exercises

14:30 -14:45 Coffee break

14:45-16:30 Lecture & exercises