Mahmoud Ahmed

Postdoc - Biomedicine

Introduction to data analysis in R

A gentle introduction to data analysis in R

Link to the GitHub repo


This is a short course on data analysis in R. The goal is to get the participants familiar with R code and to appreciate it as a tool to handle common experimental data. The materials are delivered in the form of transitional lectures and interactive exercises.


  • To get familiar with R as a tool for data analysis
  • To apply basic arithmetic and statistics in R
  • To learn to handle experimental data in R (qPCR and images)



Each module is delivered in three steps

  • lectures/: slides discussing the main concepts
  • practice/: interactive exercises for practicing purposes
  • homework/: more exercises to test understanding


  • Getting started in R
    • Lecture ([Slides](lectures/lecture_1.pdf))
    • Practice (Link)
    • Homework (Link)
  • Basic statistics in R
    • Lecture ([Slides](lectures/lecture_2.pdf))
    • Practice (Link)
    • Homework (Link)
  • Quantifying mRNA using the pcr package
    • Lecture ([Slides](lectures/lecture_3.pdf))
    • Practice (Link)
    • Homework (Link)
  • Quantifying protein co-localization in fluorescence images using the colocr package
    • Lecture ([Slides](lectures/lecture_4.pdf))
    • Practice (Link)
    • Homework (Link)


  • R studio cheatsheets (Link)
  • Tidy data by Hadley Wickham (Link)
  • Ahmed M, Kim DR. pcr: an R package for quality assessment, analysis and testing of qPCR data. PeerJ. 2018 Mar 16;6:e4473. doi: 10.7717/peerj.4473.
  • Ahmed M, Lai TH, Kim DR. colocr: an R package for conducting co-localization analysis on fluorescence microscopy images. PeerJ. 2019;7:e7255. doi:10.7717/peerj.7255

Resources (what to learn next?)