Abstract
AbstractIdentifying relevant studies and harmonizing datasets are major hurdles for data reuse. Common Data Elements (CDEs) can help identify comparable study datasets and reduce the burden of retrospective data harmonization, but they have not been required, historically. The collaborative team at PhenX and dbGaP developed an approach to use PhenX variables as a set of CDEs to link phenotypic data and identify comparable studies in dbGaP. Variables were identified as either comparable or related, based on the data collection mode used to harmonize data across mapped datasets. We further added a CDE data field in the dbGaP data submission packet to indicate use of PhenX and annotate linkages in the future. Some 13,653 dbGaP variables from 521 studies were linked through PhenX variable mapping. These variable linkages have been made accessible for browsing and searching in the repository through dbGaP CDE-faceted search filter and the PhenX variable search tool. New features in dbGaP and PhenX enable investigators to identify variable linkages among dbGaP studies and reveal opportunities for cross-study analysis.
Funder
U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute
U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse
U.S. Department of Health & Human Services | NIH | National Institute of Mental Health
U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute
U.S. Department of Health & Human Services | NIH | NIH Office of the Director
U.S. Department of Health & Human Services | NIH | Office of Behavioral and Social Sciences Research
U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Cited by
1 articles.
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