Welcome to UP BMEC's student-made introductory guide to data science and bioinformatics using R! This is a free, open-source guide that can be used by anyone, and is used by UP BMEC members and applicants to learn the language and work on the organization's own projects.
R is a free and open-source programming language targeted towards statistical analysis, data visualization, and machine learning. Having been created for data analysis, the language has thousands of packages meant for specialized data science projects. It's often used for various sectors, implemented not just in industries but also within the academe for bioinformatics, environmental science, pharmaceuticals, and more.
RStudio is an integrated development environment (IDE) designed for R, with its layout designed to let you immediately display plots, view environment variables, and even push commits to GitHub. Other IDEs such as Positron (which has the same developer) and Visual Studio Code (which will need extensions downloaded to run R) can be used, but for the sake of this guide, RStudio will be used to showcase code snippets and data visualization.
Both languages are used for data analysis; however, Python was designed for general-purpose programming while R was designed specifically for statistical analysis. Python tends to lead in machine learning and is more commonly used due to being more well-known in tech sectors, while R tends to be more niche yet more powerful for statistical analysis and data visualization. For the most part, though, these differences do not matter, and it's often up to personal preference for the user!
Bioinformatics is an often overlooked aspect of biomedical engineering, despite being highly important and even necessary for medical and environmental research. Bioinformatics can be applied to genomics, drug discovery, environmental research, and more, with analyzed data giving insights to create machine learning models and simulations.
To follow along, the first step would be to download the latest version of R and RStudio.
- Download the latest version of R from the official CRAN website.
- Select the download link intended for your operating system.
- Run the installer and complete the setup.
- After having downloaded R, head to the Posit RStudio downloads page.
- Scroll down to find the latest download link for your operating system.
- Run the installer and complete the setup.
- Open RStudio.
- Click the Console pane (lower left panel) and type
1 + 1. - If
2shows up, your download was successful!
- To make code easier to read, you can wrap code through hitting
Ctrl + Shift + A(Windows/Linux) orCmd + Shift + A(Mac). This prevents your code from bleeding past the Source pane (where you view your code) and instead cuts into another line.- To permanently enable this, head to Tools > Global Options... > Code > Editing then check Soft-wrap R source files. Click Apply then OK.
- To change the theme, head to Tools > Global Options... > Appearance and select a theme of your liking!
- To allow for a clean state in RStudio every time you open your IDE, head to Tools > Global Options... > General, uncheck Restore .RData into workspace at startup, and set Save workspace to .RData on exit to Never.
While the guide is still a work in progress, below are the content you can expect over the next few months!
| Title | Description |
|---|---|
| Introductory Programming | Introduction to functions, data types, and packages |
| Loading and Manipulating Data | Loading various file types and manipulating data to filter, clean, aggregate, and join datasets |
| Data Visualization and Exploratory Data Analysis | Creating and modifying plots with R |
| Statistical Tests | Applying important statistical tests with common packages and functions |
| Special Topic: Bioinformatics | Using core bioinformatics-related packages in data analysis |
| Regression Models | Understanding the purpose and fundamentals of various regression models |
| Machine Learning | Developing machine learning models through various algorithms |
UP BMEC's social media pages will be updated when a new part of the guide is published, so follow us to stay updated!
Thank you for taking interest in this guide and we hope to see you around! 💚
Copyright (c) 2026 UP Biomedical Engineering Circle.
This project is licensed under the terms of the MIT license.