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.
This page includes an evolving discussion of data management systems, that 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 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.
This page contains evolving guidance for using the software for prospective specimen banking and laboratory organization of retrospectively banked human specimens. To generate large scale data sets associated with a particular patient phenotype, the ability to identify if there are any matching biospecimens avaiable becomes critical. This page will provide resources for the Fred Hutch researchers to determine if the associated cohort available via collaboration with other Fred Hutch researchers or via a specimen repository and different approaches to effectively access the specimens.
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.