New Hoorn DCS dataset available in the T2DKP via federation

A new dataset, "Hoorn DCS 2019," is now available in the Type 2 Diabetes Knowledge Portal via the T2DKP Federated node at the European Bioinformatics Institute (EBI). The Hoorn Diabetes Care System (DCS) cohort is a prospective cohort of type 2 diabetics in the West Friesland region of the Netherlands, for whom clinical measurements are collected annually. Association analysis was performed at EBI across 1,997 samples for 16 phenotypes, including glycemic, anthropometric, cardiovascular, and renal traits. The Hoorn DCS 2019 dataset is described in detail on the T2DKP Data page.

This new dataset is housed at the EBI Federated node of the T2DKP, which enables researchers to interact with results that may not be transferred to the AMP T2D Data Coordinating Center (DCC) at the Broad Institute because of institutional, regional, or national regulations. Data at the EBI node are stored in such a way that their specific privacy requirements are met, but they are available for secure remote queries via T2DKP tools and interfaces. Results from such queries are served up alongside results from all of the datasets housed at the AMP T2D DCC, such that researchers may browse and query data from any location without even needing to know where the data reside. This federation mechanism represents both an important technical advance in handling and protecting data, and a significant step forward in democratizing and improving access to genetic association results. Results at the EBI Federated node now comprise 9 datasets, nearly 40,000 samples, and associations for a wide variety of phenotypes.

Summary results from all of these datasets are integrated into Gene and Variant pages in the T2DKP, and may also be viewed in interactive Manhattan plots or queried using the Variant Finder tool. The individual-level data behind the datasets are accessible for custom association analysis in our Genetic Association Interactive Tool (GAIT) on Variant pages. Using this tool, researchers can filter samples to create a custom subset with defined characteristics such as age, gender, BMI, and other measures, and then run on-the-fly association analysis within that sample subset.

Please take a look at the new dataset and contact us with any questions or comments!