Overview of Clinical and Experimental Data

Updated: May 18, 2022

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For each study, the particular covariates associated with large scale data sets typically come from clinical or laboratory data. When these data are originating from human samples, certain protections need to be in place to ensure patient privacy. There are resources at the Fred Hutch which can help researchers effectively manage these data so that they can be associated with downstream molecular data sets more consistently and securely.

Clinical Data

This page includes an evolving discussion of data management systems are available to Fred Hutch researchers, to access and interpret clinical data for a select cohort. The ability to identify if there are suitable biospecimens associated with that cohort available via collaboration with other researchers or via a specimen repository is critical to being able to then generate large scale data sets associated with those patient phenotypes. There are multiple groups involved in the data access and management of clinically originating data, including the Hutch Data Core (HDC) and the Seattle Tumor Translational Research group (STTR). The current recommendations and descriptions of available resources for this work will be described here.

Specimen Data Management

This page contains guidance for using available software for prospective specimen banking and laboratory organization of retrospectively banked human specimens. The ability to identify if there are suitable biospecimens associated with that cohort available via collaboration with other researchers or via a specimen repository is critical to being able to then generate large scale data sets associated with those patient phenotypes.

Experimental Covariate Management Approaches

This page contains guidance for tools of particular utility to documenting, organizing and linking descriptions of laboratory based processes or experimental conditions in such a way as to provide accurate and easy linking of these data to the downstream large data sets.

Data Visualization

There are a wide range of tools and resources data intensive researchers have leveraged at the Hutch to perform data visualization. Some basics are described here.

Fred Hutch Shared Resources

The Fred Hutch hosts a wide range of Shared Resources that are available to both internal and external researchers. Some resources or researchers have provided additional information and context for some of the resources (such as Genomics and Proteomics, as well as Flow Cytometry and Specimen Processing), but links to all of the resources available are here.

Genomics

We have consolidated a variety of links to the Fred Hutch Genomics Shared Resource as well as provided quick reference notes on what technologies are currently supported, how to interact with them, where to go for help and what submission requirements might exist.

Proteomics

In addition to links to the Proteomics Shared Resource, researchers have curated additional information of use for those embarking on a project involving proteomics.

Updated: May 18, 2022

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