Stepping Stone IDIBAPS R ggplot2 Data Vizualization workshop 2026
1
Welcome
2
Setup
2.1
Install R and RStudio/Posit
2.2
Install R packages
2.3
Check setup
3
R
3.1
What is R ?
3.2
Functions & packages
3.2.1
Functions
3.2.2
Packages
4
What is RStudio (Posit)?
4.1
RStudio interface
4.2
The R console
5
Paths and directories
5.1
Path and home directory
5.2
RStudio “Projects”
5.2.1
Advantages
5.2.2
Project for the course
5.2.3
Leave the project
5.2.4
Re-open the project
6
R basics
6.1
Arithmetic operators
6.2
Objects in R
6.3
Assigning data to an object
6.4
Data types
7
Import data / read files / scripts
7.1
Fetch workshop files
7.1.1
Download files from GitHub repository
7.1.2
Dataset description
7.2
Import / read in data
7.2.1
Load package into environment
7.2.2
from CSV
7.2.3
from Excel
7.3
Scripts
8
ggplot2: get started
8.1
Base structure
9
Scatter plots: focus on individual data points
9.1
Base plot
9.2
Customize the points
10
Additional layers
10.1
ggtitle()
10.2
Backgrounds
11
Export graphs
11.1
From the RStudio interface
11.2
From the console
11.3
Exercise 1 - scatter plots
12
Scatter plots: more features
12.1
Labels
12.2
Mapping variables
12.3
Additional ticks
12.4
Density estimates
12.5
Regression line
13
Barplots: visualize categorical data
13.1
Exercise 2 - Barplots
13.2
Bar positions
14
Boxplots: visualize data distribution
15
Text fine-tuning
16
Data wrangling: select and filter
16.1
filter()
16.2
select()
16.3
rename()
16.4
Exercise 3
17
Dotplots
18
Colors
18.1
All R colors
18.2
Base R palettes
18.3
RColorBrewer
18.4
ggsci
19
Faceting
19.1
Exercise 4 - Scatter plots
20
Additional graphs
20.1
Histograms and density plots
20.1.1
Histogram
20.1.2
Density plot
20.1.3
Histogram + density
20.2
Marginal plots
21
More advanced data manipulation
21.1
The pipe operator
21.2
From wide to long format
21.3
Join tables
22
Interactive plots with {plotly}
23
Selected non-ggplot packages
23.1
Heatmaps with {pheatmap}
23.2
Volcano plots with EnhancedVolcano package
24
Resources
Published with bookdown
R for beginners: Introduction to data visualization with R and ggplot2: from data to publication-quality figures
Part12
Scatter plots: more features
We will learn how to add extra levels of customizations to the plot.