R Beginners Course 2025

Introduction to R and Basic Programming Concepts

Dr. Debasish Mukherjee, Dr. Ulrike Goebel, Dr. Ali Abdallah

Bioinformatics Core Facility CECAD

2025-05-13

Session 1 :: Background & R Basics

The Lifeline of R

  • R is an offspring of the S programming language
  • S was a pioneer in making exploratory data analysis easy
    • make existing algorithms available in user friendly functions
    • provide accessible function documentation
    • provide interactive graphics devices

The Lifeline of R

  • R was born as an implementation of S in 1993, because native S had gone commercial
  • Being free and encouraging contributions by the user community, R can easily "evolve" to adapt to new needs and trends
  • Data driven science , including the genome projects, was the perfect “niche” which R could successfully claim for itself
  • Indeed the Bioconductor project was initiated by one of the founders of R

The Lifeline of R

  • The RStudio (now: Posit) company is gaining increasing influence on the evolution of the language
    • its Integrated Development Environment (IDE) is increasingly used by people doing data analysis with R
    • Posit is actively developing and promoting the tidyverse, which is both a special style and a code repository for the analysis of data tables
  • Currently there is quite some evolutionary pressure for change of the language!

The Iris Data of Edgar Anderson and Ronald A. Fisher

– Some Background Information on Our Practice Dataset

We will use the iris dataset of floral traits for practicing throughout the course:

data("iris") ## Load the data
head(iris, n=3)   ## glimpse at the first 3 lines
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species
1          5.1         3.5          1.4         0.2  setosa
2          4.9         3.0          1.4         0.2  setosa
3          4.7         3.2          1.3         0.2  setosa


It contains data on three species, 
with 50 observations each:  

table(iris$Species) ## species in dataset

    setosa versicolor  virginica 
        50         50         50


(see source page)

The Iris Data of Edgar Anderson and Ronald A. Fisher

– Some Background Information on Our Practice Dataset

  • Data published by Ronald A. Fisher in 1936
  • Statistician and co-founder of population genetics
  • Plants collected by Edgar Anderson
    • I. setosa and I. versicolor in 1935,  
      in the same natural habitat
    • I. virginica likely in 1926, 
      at a different place
  • Field botanist with a focus on speciation mechanisms


The Iris Data of Edgar Anderson and Ronald A. Fisher

– Some Background Information on Our Practice Dataset

  • Both men were involved in the making of the Modern/Evolutionary Synthesis, with complementary central tenets: 

    • R. A. Fisher: Model evolutionary processes from the known facts of genetics
    • E. Anderson: Observe the real dynamics of (plant) populations, in order to understand the role of genetics in evolution


The Iris Data of Edgar Anderson and Ronald A. Fisher

– Some Background Information on Our Practice Dataset

  • Edgar Anderson suspected that I. versicolor may be an allopolyploid hybrid: 
    I. versicolor =  
    I. setosa (2n) x I. virginica (4n)  
    (confirmed by Lim et al. 2007)

  • This may have supported the establishment of the species, by preventing back-crossing to its parents. 

  • Fisher applied his Linear Discriminant Analysis technique to Anderson’s data, in order to test the hypothesis of additive gene action: 
    if true, versicolor should be twice as similar to virginica than to sertosa!


Digression: Software is Usually Built From Bits and Pieces


  • … they come under the names of subroutines, macros, functions …
  • … in code, they are used like ’commands’:


  • Actually the function name invokes a piece of hidden code
  • … hiding complexity
  • … yet allowing to easily access complex algorithms
  • … and to make local extensions of a language