Choosing the Right Computer for Bioinformatics Analysis

If you're new to bioinformatics, one of the first questions you'll face is what kind of computer you need. This page provides an overview of your options for machines suitable for bioinformatics analysis.

The ideal specifications depend on the type of analysis you plan to run, so treat this as a general guide. If you're still unsure about requirements after reading this article, check the official documentation for the specific software you intend to use.

For laptop-based bioinformatics work, a MacBook Air or MacBook Pro is a solid choice. The base models ship with only 8GB of RAM, which is too little for many bioinformatics tools. Opt for a higher-tier configuration or upgrade the memory to at least 16GB—ideally 32GB. With 32GB, you'll have enough headroom for most standard next-generation sequencing (NGS) workflows, including variant calling and RNA-Seq analysis on organisms with reference genomes, as well as microbiome analysis with QIIME2. If you plan to write your own analysis scripts in Python or another language rather than relying on existing tools, you can design your code around your hardware, so memory is less of a concern. As for storage, NGS data accumulates fast—256GB will fill up quickly, so upgrading to 1TB or 2TB is strongly recommended.

While it is possible to do bioinformatics on a Windows machine, setting up the required environment tends to be more difficult. Most online tutorials and guides also assume a Mac, which is another reason to go with one. Since environment setup is one of the biggest hurdles for beginners, choosing a Mac helps avoid unnecessary frustration.

One thing to be aware of: since late 2020, Macs have shipped with Apple Silicon chips (M1 through M5) instead of Intel processors. This can occasionally cause compatibility issues with software originally built for Intel Macs. That said, enough time has passed that most tools now support Apple Silicon natively, and this is becoming less of a concern.

A well-configured MacBook can cost several thousand dollars, which may feel steep—especially if you only need to run a one-off analysis or want to try bioinformatics for the first time before committing to a dedicated machine.

In that case, cloud services such as AWS are a practical alternative. Unless you need a particularly powerful instance, 24 hours of computing time can cost just a few dollars.

You will still need a local computer to connect to the cloud, but it does not need high specs—your existing machine should work fine.

Some analyses exceed what a laptop can handle in terms of memory or CPU cores. Single-cell workflows are a common example: Cell Ranger requires a minimum of 8 CPU cores and 64GB of RAM, and Seurat can also demand substantial memory depending on the number of cells. For resource-intensive analyses like these, government-funded or institutional supercomputers are a good option. They are typically available to academic researchers at a relatively low cost.

Even when using a supercomputer, you still need a local machine to connect to it. The local machine itself does not need to be powerful for remote access, but having a MacBook Air or MacBook Pro is ideal since you may want to run simpler analyses locally as well.

In some situations, using an external supercomputer is not feasible —for example, when data cannot leave your institution due to privacy or security policies. In those cases, purchasing a custom-built workstation is a practical solution. You can tailor the specifications (CPU, RAM, storage) to match the exact requirements of your planned analyses.