For many bench scientists, resources like GitHub often conjure images of computational researchers tapping away at lines of code—usually in the context of some experiment ending in “-omics.” But just because GitHub was developed with software and computational science in mind doesn’t mean it has no place at the bench. In fact, history is full of examples where technologies created for one field found transformative applications in another. Take microfluidics: originally developed for inkjet printing, it ultimately revolutionized single-cell sequencing and droplet-based assays in biology.
One of GitHub’s greatest strengths in software development is its ability to improve reproducibility, a challenge that also plagues modern wet lab research. The scale of this problem was spotlighted in a widely discussed 2012 Nature article by Drs. C. Glenn Begley and Lee M. Ellis, who described efforts at Amgen to replicate findings from fifty-three landmark cancer studies. Even with cooperation from the original labs and access to the same materials, only six studies could be successfully reproduced—a staggering failure rate of 88.7%. Better documentation and method sharing won’t eliminate irreproducibility overnight, but they could make a meaningful dent.
So what is GitHub, and what would it look like at the bench? At its core, Git is a version control system—think of it as a detailed logbook that tracks every change in a project. GitHub is the cloud-based platform where that version-controlled information can be stored, shared, and collaboratively edited. If Git is Microsoft Word, GitHub is Google Docs: a place to write, revise, and work together, with a complete history of who changed what and when.
A recent PLOS Biology article by Katharine Chen, Maria Toro-Moreno, and Rasi Subramaniam explored this very question, describing the benefits—and limitations—of using GitHub in an academic wet lab setting. Among the advantages: 1) collaboration, with multiple researchers able to contribute to the same project without overwriting each other’s work; 2) accessibility, since GitHub’s core features are free to use; and 3) ease of onboarding, thanks to abundant beginner-friendly documentation and tutorials. For those interested in digging deeper into the system, more detail is available in a follow-up publication from the group available as a preprint.
That said, there are caveats. For labs working with sensitive data—especially involving human subjects—GitHub is not the place to store protected health information. And while how-to resources are available, learning GitHub can still pose a hurdle for those with no computational background.
Maria Toro-Moreno, a postdoctoral fellow in the Subramaniam lab, sees GitHub as a practical tool for the future. “Every lab runs differently, and lab management knowledge typically comes only through direct experience,” she says. “Scientists rarely document these practical aspects of doing science, so this knowledge often gets lost. Finding GitHub useful in our work, we wanted to share our experience—especially for postdocs starting to think about how they'll run their future labs.”
GitHub may have started as a tool for coders, but its potential far exceeds the terminal window. For bench scientists facing challenges like poor reproducibility, disorganized data, and knowledge lost in transition, adopting version control systems like GitHub could be a quiet revolution in how we document, share, and collaborate. As science grows more interconnected, the tools we use should reflect that—and sometimes, the most powerful solutions come from thinking outside the pipette.
The spotlighted research was funded by the National Institutes of Health, the National Science Foundation, and the Hanna H. Gray Fellowship.
Fred Hutch/University of Washington/Seattle Children’s Cancer Consortium Member Dr. Arvind “Rasi” Subramaniam contributed to this research.
Chen KY, Toro-Moreno M, Subramaniam AR. 2025. GitHub enables collaborative and reproducible laboratory research. PLOS Biology. https://doi.org/10.1371/journal.pbio.3003029.