R Programming Foundations for Data Analysis

 

28 Oct - 1 November 2024

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The course is addressed to individuals with little or no experience in programming but who are enthusiastic about learning how to use R for data analysis and streamline their work.

The course covers fundamental concepts of programming and software design focusing on programming in R. We will go through various aspects of R scripting. After introductory lectures on good programming practices, basic software design theory and a brief overview of R, we will delve into programming. We start by learning how to use R as a basic calculator, what are variable types, how to use data structures, how to implement repeating actions with and without loops, and how to take actions based on certain conditions. We gradually proceed to loading data, importing data from common file formats, some basic matrix algebra and learning how to perform basic statistical tests and visualize results.

You will learn how to document your work and how to generate automatic reports using real-life datasets. During the course you will also be working on a small dataset to apply knowledge you learnt in the course and will present that in a report format towards the end of the workshop.

 

Audience National workshop open for PhD students, postdocs, researchers and other employees within Swedish academia, as well as individuals in non-academic positions. This course is run by the National Bioinformatics Infrastructure Sweden (NBIS).

Fee 3000 SEK for non-profit organizations or 15000 SEK for private companies. Please note that NBIS cannot invoice individuals. The fee covers lunches, coffee and a course dinner. Those who accept the spot and then do not attend without prior notification will also be invoiced. 

Note that travel and accommodation is not included in the fee and must be arranged by the participants. 

 

 

Covered topics

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• Variables and Operators
• Matrices, lists, and dataframes
• Data manipulation
• Visualization
• R packages
• Bioconductor

Application

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This is a national course. The course is open for PhD students, postdocs, group leaders and core facility staff. We do accept application from other countries (within EU zone), but give priority to applicants from Swedish universities prior to applicants from industry and academics from other countries.

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.

You can apply here.

Entry requirements

Good general computer literacy is expected, but no previous experience in programming or R is required. You are expected to know basic concepts in mathematics and statistics, but the emphasis of the course is to learn how to use R.

Participants are expected to use their own computers with pre-installed R and R Studio (detailed instructions will be given upon acceptance).

Due to our best practice to have a high teacher to student ratio we have set the number of 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.

Location

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Uppsala: Experimental room, Campus Blåsenhus, von Kraemers allé 1A, 2nd floor, Uppsala University

Lund: Retina D227, Biologihuset Lund University

 

Learning outcomes

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Upon completion of this course, you will be able to:

• Describe different data structures commonly used in R.
• Work with different data types. 
• Import and export data from and to R environment.  
• Manipulate data. 
• Work with dataframes and lists.
• Visualize the data. 
• Use R Markdown to create reports containing text, code, tables and/or figures

 

Schedule

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Course schedule can be found here,

Exercises

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All exercises can be found in here.

 

 

Precourse material

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Please read carefully the Precourse material before the course start.

 

Course Staff

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Nima Rafati - course leader (nima.rafati@nbis.se)

Guilherme Borges Dias - course leader (guilherme.borges.dias@icm.uu.se)

Miguel Redondo - course leader (miguel.redondo@icm.uu.se)

Marcin Kierczak - course teacher (marcin.kierczak@scilifelab.se)

Lokeshwaran Manoharan - course teacher (lokeshwaran.manoharan@nbis.se)

Louella Vasquez - teaching assistance (louella.vasquez@scilifelab.se)