GenEpi-BioTrain - Virtual training 18 - Empowering AMR Research through R: Analysis and Visualisation

Topic outline

• Welcome to the virtual training on "Empowering AMR Research through R: Analysis and Visualisation"!

  Welcome to the virtual training on "Empowering AMR Research through R: Analysis and Visualisation"!

  ℹ️ Please Note

  You are welcome to explore the available resources and video recordings. Please note that the resources in this course come from the Virtual Training 18 held in June 2025, and certificates are only issued to participants who attended the live webinar sessions.

  
  
  Aim

  This intermediate-level R course is designed for participants who have already completed the  GenEpi-BioTrain - Virtual training 14 - R data analysis and visualisation for beginners or who are comfortable with basic R syntax, data manipulation, and plotting.
  

  In this hands-on training, we’ll explore how to apply R to antimicrobial resistance (AMR) and whole genome sequencing (WGS) data using real-world examples. You’ll learn how to create publication-ready plots, heatmaps, and phylogenetic visualisations that support effective interpretation and communication of AMR trends.

  Target audience

  Whether you're working with national surveillance data or outbreak investigations, this course aims to provide you with the practical tools and confidence to explore, visualise, and share AMR insights using R.

  Pre-requisites

  This training (specifically the practical exercise) has several Prerequisites. In anticipation of the first session, we invite you to:

  1. Complete the 'Pre-requisites' checklist.
  2. Read carefully the 'Software requirements' and prepare your environment. 

  Format

  This virtual training takes place over two sessions that will be held on Wednesday, June 18 and June 25 from 9:00 to 12:30 (CEST).

  Session 1: AMR Data Visualisation in R (18 June)

  1. AMR Data Wrangling and Visualisation
  2. Advanced Plotting Techniques
  3. Heatmap Visualisation
  4. Practical Exercise Briefing and Q&A

  The practical exercises presented in Session 1 should be completed between sessions. The answers will be provided at the beginning of Session 2.

  Session 2: Phylogeny and AMR Integration in R (25 June)

  Practical Exercise Review and Recap Phylogenetic Tree Basics in R Annotating Trees with AMR Data Wrap-Up and Q&A		Shortcut

  
  

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  Pre-requisites

  Pre-requisites

  To actively participate in the hands-on practical sessions and meet the learning objectives of this course, participants should have:

  • • Ability to navigate the RStudio interface and run R code in the Console and Script panes
      

  • • Familiarity with basic R syntax (objects, vectors, data frames)
      

  • • Prior use of tidyverse tools such as dplyr and tidyr for filtering, selecting, and reshaping data

  • • Ability to import and explore .csv files in R
      

  • • Experience with basic plotting using ggplot2 (e.g., bar plots, faceting)

  • • R and RStudio installed and running prior to the course

  • • Ability to install R packages as needed during the session (e.g., ggplot2, pheatmap, ggtree)
      

  • Participants who do not yet meet these requirements are still welcome to join as observers. You’ll benefit from the demonstrations and discussions and can revisit the hands-on materials at your own pace afterward.

    If you're unsure about your R skills or would like a refresher on using R and RStudio, we encourage you to watch the recordings of the following virtual training:

  • • GenEpi-BioTrain - Virtual training 14 - R data analysis and visualisation for beginners
• Aim and Objectives

  Aim and Objectives

  This two-part training builds on foundational R skills from the initial R training  GenEpi-BioTrain - Virtual training 14 - R data analysis and visualisation for beginners. This training will introduce participants to advanced visualization techniques for antimicrobial resistance (AMR) and whole genome sequencing (WGS) data. The focus is on practical, hands-on applications using real-world datasets, including heatmaps and integrated analysis of phenotypic and genotypic resistance.

  By the end of this workshop, participants will be able to:

  • Create advanced AMR visualizations using ggplot2 and patchwork.
    
  • Summarise and visualise resistance data by location, organism, and time.
    
  • Generate clustered heatmaps using phenotypic and genotypic resistance data.
    
  • Integrate WGS-derived resistance gene data into AMR analyses.
    
  • Visualise phylogenetic trees using ggtree() and annotate them with AMR data using gheatmap().
    
  • Interpret and communicate trends in AMR using effective plots.
• Software Requirements

  Software Requirements

  To participate in this course, you’ll need both R and RStudio installed and functioning on your computer.

  While the course demonstrations will be performed on a Mac laptop, the course is fully compatible with Windows, macOS, and Linux. All participants should ensure they have the following installed in advance:

  • R version: 4.4.2 or later
    
  • RStudio version: 2024.12.0+467 or another recent stable release
    

  How to Install R

  1. Go to the CRAN website.

  2. Select your operating system:

  • “Download R for Windows”
    
  • “Download R for macOS”
    
  • “Download R for Linux”
    

  3. Download the most recent version:

  • For Windows: choose “Install R for the first time”
    
  • For macOS: download the .pkg file under Latest release
    

  4. Run the installer and follow the setup instructions. (It’s fine to keep the default installation settings).

  How to Install RStudio

  1. Visit the RStudio download page.

  2. Download the free Desktop version (Open Source Edition) for your operating system.

  3. Follow the installation instructions for your platform.

  
  

  
  
• Session 1: AMR Data Visualization in R

  Session 1: AMR Data Visualization in R
   This session will cover: 

  1. AMR Data Wrangling and Visualization
  2. Advanced Plotting Techniques
  3. Heatmap Visualization
  4. Practical Exercise Briefing and Q&A

  Click the "Go to event" button below for the detailed agenda.

  • PageRecording of session 1

    S1 - Select the checkbox to the right once you have completed watching the recorded session
    

     

     
    

  • Additional Resources

  • FileSession 1 presentation

    Presentation titled Session 1: AMR data Visualisation in R during the first session on the 18th June 2025.

  • Fileamr_phenotype_eu.csv

    This dataset will be used in Session 1 to introduce basic data cleaning and visualization techniques for antimicrobial resistance (AMR) data in R. It contains a small, manageable number of bacterial isolates collected from various European countries, along with their phenotypic resistance results to selected antibiotics.
    

  • Fileamr_phenotype_larger.csv

    This larger dataset is used in Session 1 to practice working with more realistic AMR data containing a wider range of bacterial species, countries, and resistance profiles. It includes over 300 isolates and expands the number of countries and timepoints compared to the smaller EU dataset.
    

  • Fileday1_amr_visualization_blank_exercises.Rmd

    Template R Markdown file to use during Session 1. Includes code chunks and exercises to follow along with the instructor.

  • Fileday1_amr_visualization_filled_in_exercises

    The R Markdown file presented during Session 1. Includes code chunks with the exercises filed in. 
    

• Exercise between sessions

  Exercise between sessions
  • Practical

    Here you can find the practical exercises that should be completed before Session 2. Answers will be given at the beginning of Session 2.
    

    Your Task:

    •Download the "dirty" dataset.

    
    

    •Data Cleaning:

    •Clean the species column to harmonize values like "E. Coli", "e.coli", "Salmonella sp.", etc.

    •Handle missing or empty resistance values ("", NA), and recode:

    –"R" → 1

    –"S" → 0

    
    

    Matrix Preparation:

    •Create a resistance matrix with rows = isolate_id, columns = antibiotics.

    •Make sure row names are unique.

    
    

    Heatmap Visualization:

    •Create a basic heatmap with no clustering or annotations.

    •Then add annotations for:

    –species (color-coded)

    –country (color-coded)

    •Optionally, arrange the heatmap by country or species.

    
    

  • Fileamr_phenotypes_dirty.csv

    This dataset is presented in Session 1 as the take-home exercise. It simulates common real-world challenges in AMR data analysis by including inconsistent formatting, missing values, and unstandardized species names.
    

• Session 2: Phylogeny and AMR Integration in R

  Session 2: Phylogeny and AMR Integration in R

  This session will cover the following:

  1. Practical Exercise Review and Recap
  2. Phylogenetic Tree Basics in R
  3. Annotating Trees with AMR Data
  4. Wrap-Up and Q&A

  Click the "Go to event" button below for the detailed agenda.

  • PageRecording of session 2

     S2 - Select the checkbox to the right once you have completed watching the recorded session

     

     
    

    
    

  • Additional resources

  • Fileday2_phylogeny_blank_exercises.Rmd

    Template R Markdown file to use during Session 2. Includes code chunks and exercises to follow along with the instructor.
    

  • Fileresfinder_results.csv
  • Filephenotypic_data.csv
  • Filemetadata.csv
  • Filetree.nwk
  • Fileday2_case_study_diphtheria.pptx
  • Fileday2_case_study_diphtheria.Rmd
  • Filepredicted_amr_data_genes_377_cgMLST.tsv
  • Filet377b_rooted.nwk
  • FileZipped_tree_newick_file
• Contacts

  Contacts

  For any questions regarding the this webinar series, please use the discussion forum.

  If you have questions regarding other training initiatives please contact: courses@ecdc.europa.eu.

  If you have technical issues please contact ECDC Helpdesk - ICT Front Office ICT.FrontOffice@ecdc.europa.eu.

  • ForumQuestions and Answers (Q&A) Forum