Data visualization with R and ggplot2: from data to publication-quality graphics
2023-10-22
Part1 Welcome
Dates, time & location
- Dates:
- First edition: September 27-28
- Second edition: October 18-19
- Time:
- 9:30-13:30
- 9:30-13:30
- Location:
- IDIBAPS
Instructor
Bioinformatics consultant at Clarivate.
Prerequisites
The workshop is open to anyone with no (or little) prior programming experience.
Attendees must however feel comfortable enough with their own computer to install programs (and debug their installation, when needed) and locate folders and files.
Learning objectives
Attendees will:
- Gain a high-level understanding of data import, manipulation and graphing with R and RStudio.
- Be able to produce and save a variety of publication-quality graphs (among others: boxplots, scatter plots, barplots).
Learning outcomes
- Identify and use RStudio panels (console, scripts, folders and files panels).
- Locate useful resources to learn more and know where to seek help.
- Import data from files into R.
- Manipulate and prepare (filter, select) data.
- Produce graphs:
- Create a plot from “recipes”.
- Change basic parameters (color, font size, point shape, title, etc.).
- Export high-quality graphs in different formats (pdf, jpeg, png).
What this workshop is NOT:
- A programming class.
- A design class.
What this workshop is:
- An introduction to R and to RStudio software.
- An introduction to data visualization.
- A teaser to - hopefully - make you want to learn how to program in R!
Approximate agenda
Day 1 & 2: 9:30-13:30.
~20’ break around 11:30.
- Welcome and set up
- Introduction to R and RStudio (Posit)
- Paths and directories
- R basics
- Data import
- ggplot2:
- Introduction, concept
- Scatter plots
- Barplots
- Boxplots
- Fine-tuning font
- Colors
- Faceting
- Data filtering and wrangling:
- select, filter, rename
- the pipe operator
- from wide to long format
- More ggplots
- Exercises
- Interactive plots with {plotly}
- Heatmaps with {pheatmap}
- Demo volcano plots
