The Data Science section of the Biomedical Data Science Wiki aims to be your go-to guide for all things data science at Fred Hutch. This section of the Wiki covers a wide range of data-related topics — from data stewardship and policy, to recommendations on how to work with big data, to advanced analysis and tools you can use to analyze your data.
Beyond the articles in this section, we have two other content types that are actively update and curate over time based on community needs shared with us via our Fred Hutch Data Slack #wiki-contributors channel
The Resource Library is a growing collection of step-by-step demonstrations, mini-tutorials, and how-to guides focused on real-world data tasks. Each resource is designed to help you learn by doing — whether you’re exploring cBioPortal, setting up an analysis environment, or troubleshooting a common workflow. These demos walk you through specific examples using real-world tools, platforms, and datasets, making it easier to apply concepts directly to your work.
While SciWiki content is organized by topic, many real-world tasks require following a sequence of steps across multiple topics. The Pathways section is designed to guide users through common workflows in biomedical data science by providing curated walkthroughs that connect the dots across the Wiki.These pathways are especially useful for new users or for anyone tackling a task they haven’t done before — from setting up a project to analyzing a dataset.
The Office of the Chief Data Officer (OCDO) leads Fred Hutch’s strategic vision for data. Its mission is to support all staff who use data — from clinicians to researchers to administrators — by advancing a coordinated, ethical, and effective data ecosystem. OCDO collaborates closely with teams across Fred Hutch, including the Office of Translational Research, Shared Resources, and Scientific Computing.
Areas of Expertise The OCDO provides support in these core areas:
If you are part of the Cancer Consortium (Fred Hutch, University of Washington, Seattle Children’s Hospital), you can also connect with us in the Fred Hutch Data Slack workspace (Note: this is limited to Consortium staff so please use your work email).
You can now schedule a consultation with OCDO staff on variety of data oriented questions. Schedule a Data House Call with our staff to get your questions answered on a variety of data related topics from AI and data policy, to clinical data access, to research analysis support and large scale computing.
The OCDO supports Fred Hutch investigators and teams in developing grant proposals that involve data, data infrastructure, or data science expertise. Whether you’re preparing a new submission or updating a renewal, we can help ensure that your data-related language reflects institutional resources, best practices, and future-ready capabilities.
We can provide you and your team with:
To request a current version of the OCDO/DaSL facilities and resources document, please email: data@fredhutch.org
The Data Science Lab (DaSL) is the outreach arm of the OCDO and provides direct-to-community support in the form of:
You can find more about what training and data science education and community learning events at hutchdatascience.org. Also our Fred Hutch-focused events can be found on our internal CenterNet page.
If you would like to see content on a specific topic you think is relevant to this space, please feel free to leave a request via GitHub Issue or by emailing data@fredhutch.org.
Read more here on how you can contribute to this collaborative Wiki.