Translational Data Science & Software
The Translational Data Science & Software group collaborate with and support both research and clinical staff with applying effective data science and analysis into research and clinical care. Our goal is to create a feedback loop to foster a learning healthcare system.
We develop data products, including web applications, data analysis tools, process automation, and scientific software, to enable effective data use and integration into research and clinical care. We also collaborate with our clinical and research partners to develop statistical/ML/NLP models, data analyses, and data-driven dashboards and visualizations using real-world healthcare and laboratory-generated data.
The Translational Data Science Integrated Research Center (TDS IRC) and Translational Data Science & Software teams have partnered together to provide financial support for data scientists to work with Fred Hutch research groups. Find out more about how to apply.
Clinical Data Science
Our team supports clinical data science at Fred Hutch by analyzing real-world data generated over the course of health care delivery, and by improving the interoperability, quality, and accessibility of these data. They collaborate with Hutch researchers and staff to understand critical questions about cancer patients, develop impactful and practical data analyses, and to develop tools that support democratized data access, exploration, and analysis.
Connect with us
- Fred Hutch patient data access and analysis support can be requested on Fred Hutch CenterNet.
- E-mail us about partnering on other clinical data science projects:
analytics@fredhutch.org. - Schedule a 20-minuteData House Call
- Clinical data access to discuss how we can support you in accessing and using Fred Hutch patient data for research
- Data wranging and visualization
Research Informatics
Our team supports the use of biomedical datasets in the research context that often include large scale public or private genomic data, licensed or regulated datasets (such as those under DUAs or legal protection like GDPR), or laboratory-generated data that require significant computational processing as part of their analysis. We focus on providing open-source tooling, best practices for computational workloads and data management, and other resources such as computational workflows and templates that staff can use as a jumping off point to customize for their own work. We work closely with Fred Hutch IT’s Scientific Computing group who provide support for our on-prem computing cluster, scientific data storage, and research applications.
Workflow Support in WILDS
We’re developing resources in collaboration with the Fred Hutch IT Scientific Computing group to support simplified interfaces to computing resources through our project PROOF. This will facilitate users running WDL workflows on our cluster and you can find our emerging resources in our WILDS GitHub organization, such as our WDL supports.
Research Data Applications
We support the private Fred Hutch instance of cBioPortal in collaboration with Fred Hutch IT’s Scientific Computing group. cBioPortal allows users to easily explore multidimensional cancer genomics data with an intuitive point-and-click interface. For more information, read the SciWiki documentation and visit cbioportal.fredhutch.org to try it out.
Connect with us
Our team provides support to the community through documentation on the Biomedical Data Science Wiki, through our Learning Communities, and through our Data House Calls program.
Research Data Management House Calls: to discuss questions about research data management, infrastructure, or tools.
Research Computing House Calls: to discuss questions about how to run your code or analysis more effectively and at scale
Note: Often we pull in folks from the Scientific Computing team to provide expert advice as well so please describe your needs well so we can try to have the right staff ready.
Human Computer Interaction
The Human Computer Interaction (HCI) team develops and enhances open-source scientific software for computational biology, bioinformatics, biostatistics, and biomedical data science, focusing on high standards of scientific rigor and providing training in software development. Their comprehensive approach combines qualitative research, human-centered design, and software development to empower research labs with adaptable tools that meet evolving research challenges.
Connect with us
Schedule a discussion on your code or software questions via a Code and Software, Data House Call type.