Installing Ubuntu

Most bioinformatics tools are built for Linux. Genome aligners, variant callers, and pipeline managers all assume a Unix environment. Learning to work in Linux is not optional. It is a core skill.

Ubuntu is the most popular Linux distribution for bioinformatics. It has the largest community, the most tutorials, and the best package support. When something goes wrong, you will almost always find an answer online.

Why Linux for bioinformatics

Almost every bioinformatics tool runs on Linux natively. Tools like STAR, BWA, samtools, and Nextflow are developed and tested on Linux first. Some have macOS support. Very few support Windows directly.

HPC clusters and cloud servers run Linux. When you connect to your institution’s compute cluster or spin up an AWS instance, you will land in a Linux terminal. The commands you learn on your local Ubuntu machine will work the same way on those remote systems.

Reproducibility depends on it. Containers, conda environments, and workflow managers all work best on Linux. Building a reproducible pipeline on Windows or macOS often requires workarounds that break in unexpected ways.

Options for running Ubuntu

Dedicated machine or dual boot

The best experience. Install Ubuntu directly on your computer or set up a dual boot alongside Windows or macOS. This gives you full performance and no compatibility issues.

Windows Subsystem for Linux (WSL)

If you are on Windows 10 or 11, WSL lets you run a real Ubuntu environment inside Windows. It is fast and well integrated. Most bioinformatics workflows run fine under WSL.

Virtual machine

Use VirtualBox or VMware to run Ubuntu inside your current OS. This works but performance is lower than a native install. Good for trying things out before committing.

Cloud server

You do not need a local Linux machine at all. A cloud server gives you a full Ubuntu environment accessible from any computer with an internet connection. See the cloud options section below.

Installing Ubuntu

Canonical publishes detailed installation guides that stay up to date with each release. Rather than duplicating instructions that change every six months, here are the official resources.

Desktop install

For installing Ubuntu on your personal computer or as a dual boot:

• Ubuntu Desktop Installation Guide

WSL on Windows

For running Ubuntu inside Windows without dual booting:

• Install Ubuntu on WSL

Server install

For setting up a headless Ubuntu server without a graphical interface:

• Ubuntu Server Installation Guide

Cloud servers

A cloud server is often the easiest way to get started. You get a fresh Ubuntu machine in minutes without touching your personal computer. It is also how most real bioinformatics work gets done.

Amazon Web Services (EC2)

AWS is the most widely used cloud platform in bioinformatics. Many public datasets are hosted on AWS, and nf-core pipelines have built-in AWS support.

• Launch an EC2 instance
• Free tier includes 750 hours/month of a t2.micro instance for 12 months

This video walks through setting up an AWS account and launching your first instance:

DigitalOcean

Simpler interface and flat pricing. Good for learning and small projects. A basic droplet starts at $4/month.

• Create a Droplet

Google Cloud Platform

Similar to AWS with a generous free tier. Less common in bioinformatics but fully capable.

• Create a VM instance

Linode (Akamai)

Straightforward pricing and good documentation. Another solid option for a personal Linux server.

• Getting Started with Linode

Other Linux distributions

Ubuntu is our recommendation, but it is not the only option. Knowing the major distributions helps when you encounter them on servers or in documentation.

Debian

Ubuntu is based on Debian. Debian prioritizes stability over having the newest software. Server administrators often prefer it because packages are thoroughly tested before release. Debian uses the same apt package manager as Ubuntu. If you know Ubuntu, you can use Debian with minimal adjustment.

Fedora

Fedora is backed by Red Hat. It uses the dnf package manager instead of apt. Fedora tends to ship newer software versions than Ubuntu or Debian. Some bioinformatics researchers prefer it for access to the latest tools. Red Hat Enterprise Linux and Rocky Linux are related distributions common on HPC clusters.

Arch Linux

Arch is a rolling-release distribution. It always has the very latest software. It requires more manual setup and Linux knowledge. Arch is popular among experienced Linux users but is not recommended for bioinformatics beginners. Its wiki is excellent documentation even if you use a different distribution.

Which one to choose

For bioinformatics, stick with Ubuntu or Debian. Most tutorials, Docker images, and cloud server templates assume one of these two. When you connect to an HPC cluster, you may encounter CentOS, Rocky Linux, or Red Hat. The core commands are the same. Only the package manager differs.

Which Ubuntu version

Use the latest LTS (Long Term Support) release. LTS versions are supported for five years and receive security updates. As of mid 2026, Ubuntu 26.04 LTS is the current recommended version. The previous LTS, Ubuntu 24.04, is still supported and a fine fallback if you need a slightly older base for an existing pipeline.

Avoid non-LTS releases for bioinformatics work. They have shorter support windows and can cause compatibility issues with tools that expect a stable base.

After installation

Once you have a working Ubuntu environment, you are ready to start learning the command line. The next page covers navigating the filesystem.