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Literate Programming (in R)

Authors

Elisa Pierfederici

Elisa Pierfederici

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PhD Candidate, Research advisor, University of Oslo (UiO), Norway

Clement Lee

Clement Lee

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Lecturer, School of Maths, Stats and Physics, Newcastle University

Saad Arif

Saad Arif


Saad Arif, Senior Lecturer, Dept. of BMS, Oxford Brookes University

Mark Fernandes

Mark Fernandes

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Mark Fernandes, Teaching Associate, Bioinformatics Training Facility, Dept. of Genetics, University of Cambridge

Lesson overview

Description
A course to introduce the theory, advantages and implementation of Literate Programming practices for R users working in RStudio to enhance the students abilities to produce reproducible code.

Prerequisites
To be able to follow this course, learners should have knowledge in:
 1. Basic programming skills in R
 2. A familiarity in using the RStudio Integrated Development Environment

Learning Outcomes:
By the end of the course, learners will be able to:
 1. Have an understanding of the principles and goals of Literate Programming (LP)
 2. Practically implement LP in their R programs using Markdown in Quarto/Rstudio

Target Audience: Researchers, undergraduate students, postgraduate students, etc…

Level: Beginner to Intermediate

License: Creative Commons Attribution 4.0 International License

Funding: This project has received funding from [name of funders].

Contributors

Your name here!

Your name here!

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Citing this lesson

Please cite as:

  1. Saad Arif, Mark Fernandes, Clement Lee, & Elisa Pierfederici. (2024). Literate Programming in R. Zenodo. https://doi.org/10.5281/zenodo.11259813
  2. Geert van Geest, Elin Kronander, Jose Alejandro Romero Herrera, Nadja Žlender, & Alexia Cardona. (2023). The ELIXIR Training Lesson Template - Developing Training Together (v1.0.0-alpha). Zenodo. https://doi.org/10.5281/zenodo.7913092.

Setup

Data setup

To run this lesson you need to download the data here; the GitHub repository at which the csv file is situated also contains the scripts that generate the page you are looking at. To ensure that the code in Chapter 4 works, it is recommended that you put the downloaded csv file a (sub-)directory called data/ on your machine; see the example structure in Chapter 2.

Software setup

The following is consistent with the installation guide in Chapter 4. To run this lesson you need to install the following:

  • R - follow the instructions here. You will need R for everything that follows.
  • RStudio - follow the instructions here. You will need RStudio (and R) for Chapters 2 and 3.
  • Quarto - follow the instructions here. You will need Quarto (and R and RStudio) for Chapters 4 and 5.
  • TinyTex (R package) - required if you want to use LaTeX and/or render PDFs. This is an R package, more info and installation instructions here.