Missing something? View this page on the old site We are thrilled to announce that ‘Ten Common Misconceptions About Galaxy (And Why They Are Wrong!)’ has just been published in PLOS Computational Biology! This paper is the result of passionate discussions, collaborative debates, and a shared commitment to clarifying what Galaxy truly is—and what it can do. Whether you are a longtime Galaxy user or new to the platform, this paper will challenge assumptions and highlight Galaxy’s versatility, scalability, and impact across disciplines.Every great idea starts with a spark. For this paper, that spark was a feeling, a nagging sense that Galaxy, despite its growing popularity and impact, was still misunderstood. That feeling grew into a thought, and that thought grew into a conversation. A lively conversation.It began with a group of nerds (affectionately referred to as such) gathering to vent their frustrations about the persistent myths surrounding Galaxy. Another group of nerds disagreed with their conclusions. Then, life got busy, and progress stalled. Later, a third group joined the fray, leading to a grand, collective whinge session in Australia. After countless hours in Google Docs, a write-a-thon, numerous online meetings, and moments of near-despair, something remarkable emerged: a paper that not only addresses misconceptions but does so with evidence, humor, and a touch of defiance.Galaxy is an open-source platform designed for accessible, reproducible, and scalable data analysis. It’s used by researchers, educators, clinicians, and industry professionals worldwide. Yet, despite its success, misconceptions persist. Some believe Galaxy is only for genomics, lacks scalability, or is just a teaching tool. Others question its security, software quality, or relevance outside academia.This paper tackles these myths head-on. It’s not just a defense of Galaxy: it’s a celebration of its versatility, maturity, and impact across disciplines.Let’s dive into the myths and the reality:Reality: Galaxy supports -omics and beyond. While it originated for genome analysis, its data-type agnostic architecture enables broad applicability, from proteomics and metabolomics to ecology, climate science, and even astronomy. Galaxy’s flexibility allows tool developers to contribute tools for any domain, and its extensive datatype system supports over 700 formats and 9,000+ tools.Reality: Coders can write their own tools and make their analysis reproducible with Galaxy. Galaxy brings decades of accumulated expertise, allowing developers to create versioned, documented, and reproducible analyses. Tools are easily shared, and Galaxy’s API enables programmatic interaction, making it a powerful platform for both developers and researchers.Reality: Galaxy scales to global analyses! UseGalaxy.* instances offer massive computing power, with thousands of CPU cores, TBs of RAM, and PBs of storage. Galaxy’s ability to handle large datasets is proven by its use in COVID-19 research, where it analyzed over 500,000 samples in near real-time.Reality: Galaxy is easier to use than the alternatives! Its standardized environments, simple user interface, and extensive training materials make it accessible to users of all skill levels. The Galaxy community actively improves usability, ensuring that trainees can focus on science rather than technical hurdles.Reality: Galaxy is used widely for high-impact studies and industry applications. It supports large-scale data analyses, from the Vertebrate Genomes Project to the Human Cell Atlas. Galaxy’s reproducibility and scalability make it a powerful tool for both education and cutting-edge research, as proved by the 20k+ citations.Reality: Galaxy is actively used in secure settings. It supports secure data analysis through features like Bring Your Own Compute (BYOC), encryption, and role-based access control. Galaxy is deployed in clinical and public health settings, ensuring compliance with data protection regulations.Reality: Galaxy is widely used in industry. Companies in biotech, pharma, and agritech leverage Galaxy for R&D and pipeline development. Its openness and reproducibility reduce vendor lock-in and accelerate innovation, making it a valuable tool for industry professionals.Reality: Galaxy is highly customizable and extensible. Advanced users can develop their own tools, integrate Galaxy with other platforms, and use its APIs for automation. Galaxy’s flexibility makes it suitable for both beginners and experts.Reality: Galaxy is a mature and sustainable platform. Its active global community, robust governance, and continuous development ensure long-term support and innovation. Galaxy’s open-source model fosters collaboration and shared responsibility.Reality: Galaxy prioritizes transparency. Every step of an analysis is documented, shareable, and reproducible. Users can inspect tools, workflows, and data provenance, ensuring full transparency and trust in the results.This paper isn’t just about correcting the record, it’s about empowering users. By addressing these misconceptions, we hope to:Galaxy is more than a platform; it’s a community-driven effort toward open, reproducible science. This paper is a testament to that spirit.This paper and its impact would not have been possible without the entire Galaxy community, a vibrant, global network of researchers, developers, educators, and advocates who continuously push the boundaries of open, reproducible science. We are deeply grateful for your contributions, feedback, and passion.We also acknowledge the founding vision and ongoing support of the Galaxy Project, which has grown from a small initiative into a cornerstone of accessible, scalable data analysis.Special thanks go to:To help share these insights, we’ve created a poster summarizing the 10 misconceptions. This poster was presented at the French Bioinformatics Conference (JOBIM 2025) and is now available for everyone to use. You can download, print, and share it as-is, or adapt it into a flyer to advocate for Galaxy in your own community. Let’s break those misconceptions together!Institut Français de Bioinformatiquefrance-bioinformatique.frGerman Network for Bioinformatics Infrastructure Service, Training, Cooperations & Cloud Computingdenbi.deMinistry of Science, Research and Artsmwk.baden-wuerttemberg.deELIXIR Europeelixir-europe.org Open source platform for accessible, reproducible, and transparent data analysis. © 2026 Galaxy Project. All rights reserved.