Hands-on Biological Data Visualization with ggplot2 & R


About This Course

Get hands-on experience on the basic to advanced level analysis & visualization of biological datasets using the ggplot2 packages in R language. Also learn how to write scripts, preprocess, explore, visualize and analyze biological datasets for more meaningful biological research.

A Step-by-step Case-study of Human Mitochondrial Proteome
From Dataset Parsing to Beautiful Visualizations

Why is Biological Data Visualization Important for Your Research:

  • Validating the hypothesis based on visual inspection of the data analysis.
  • Quick visualization of large mathematical to better understand the dataset at hand.
  • Being able to compare the gene expression intensities among a large set of samples.
  • Plotting a bar chart to quickly understand the distribution of the dataset.
  • Construction of PCA plot to compare the PCA components among multiple and different samples.
  • Visualization of the distance matrix datasets among many biological replicates and samples through heatmaps.
  • Creating publishable figures for research papers, proposal and review papers.
  • Visualization of the commonly executed biological data analysis, such as principle component analysis, t-test, distributions and much more.

How will this workshop help you


In this pre-recorded, pre-scheduled Biological Data Visualization with ggplot2 in R Workshop, you will be learning skillsets that are required for beautiful, meaningful and interestingly publishable high quality biological data visualization and figures. Even if you don’t know programming or R language at all, in this workshop you’ll learn R language from the basics to the advanced levels and then apply your script writing skills on data visualizations.


Learning biological data visualization can not only help you in creating beautiful data visualization but also in making impactful decisions during your research based on data visualizations along with publishable figures for your research papers.


  • Complete Introduction to R language (view content below)
  • Biological Dataset Pre-processing
  • Introduction and Basics of ggplot2
  • Key Components of a Visualization, Scaling and Labels in ggplot2
  • Facet/Scattered Visualizations
  • Linear Regression & Smooth Visualizations
  • Box plots and Histograms for Pattern-Recognition in Biological Datasets
  • Frequency Plots for Information Mining Visualizations.
  • Volcano Plots for Gene Expression Datasets
  • Heatmaps for Gene Expression and Distance Matrix Datasets
  • PCA plot for Principle Component Analysis
  • Phylogenetic Tree Visualization Using ggtree

Important Note

You’ll be practicing on a case-study of human mitochondrial proteome and genome along with real-world gene expression dataset.

Therefore, you’ll not only learn data visualization with ggplot2 in R, but you’ll also do real-world biological data visualization in this biological data visualization with ggplot2 in R workshop.

Our Philosophy

Learning should be at your convenience

We believe that not everyone is a fast learner especially when it comes to Bioinformatics, so our courses and workshops are designed in such a way that you learn at your own pace, during any time of the day and any number of times.

Everything Online, For Everyone

Whether you’re a beginner in Bioinformatics, an experimental biologist or a Bioinformatics researcher, our workshop will help you greatly.

Learn effectively with well-curated materials

For an optimal learning experience we carefully prepare our learning materials and example data. So, you comprehend how your newly gained skills can help you do great research!

Learning Objectives

Introduction to R
Functions & Variables
Packages & Data Types
Control & Data Processing
Introduction to ggplot2
Biological Data Visualization with ggplot2


  • No prior experience in R or coding required

Target Audience

  • Biologists, beginner or intermediate Bioinformaticians or data analysts with no or little experience in applications of computational bioinformatics and bioinformatics pipelines for data visualization.
  • Students looking to create publication-ready figures for their research.


56 Lessons

Segment 1: Introduction to R Language & Installation

To get started with some exciting data analysis, you first need to learn how to install the RStudio. In this particular segment you’ll also learn for what purposes computational biologists and bioinformaticians are utilizing the RStudio.
Introduction to R in Bioinformatics & R Installation9:48
The R Studio Interface6:23

Segment 2: Introduction to Functions & Variables in R

Learn about built-functions provided by R language and their utilization. Also learn how to declare variables and how to create user-defined functions in R language.

Segment 3: Introduction to Packages & Data Types in R

Learn about various packages provided by R in order to enhance your programming experience with R language. Also how to install such packages in R and learn about different data types in R.

Segment 4: Control Flow & Biological Data Pre-processing in R

Learn the flow of the code execution and control it by understanding the modularity of R code. Learn the best tips and techniques to do large biological dataset pre-processing in R.

Segment 5: Biological Data Visualization via ggplot2 in R

Learn everything you need to know about the most famous R package, ggplot2 which has various functions to create different graphs, allows modification, annotation and much more.


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All Levels
56 lectures

Material Includes

  • Complete R for Bioinformatics Course
  • Step-by-step lectures to do data pre-processing and data visualizations in R.
  • Transcriptions
  • Notes
  • BioPresentations
  • Exercises
  • Automated Evaluations (MCQs)
  • 100% Authentic Certificate

Enrolment validity: 90 days

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