Overview of Clinical and Experimental Data

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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 Commonwealth (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 Banking

This page contains evolving guidance for using the 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.

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