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Related Concept Videos

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Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX.

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|September 1, 2022
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Summary
This summary is machine-generated.

Common Data Elements (CDEs) now link phenotypic data across studies in the database of Genotypes and Phenotypes (dbGaP). This facilitates data reuse and cross-study analysis by identifying comparable datasets.

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Area of Science:

  • Genomics and Bioinformatics
  • Data Science
  • Biomedical Informatics

Background:

  • Data reuse is hindered by challenges in identifying relevant studies and harmonizing datasets.
  • Common Data Elements (CDEs) can improve dataset comparability and reduce harmonization burdens but have not been historically mandated.
  • PhenX and dbGaP collaborated to address these data linkage and harmonization challenges.

Purpose of the Study:

  • To develop and implement an approach using PhenX variables as CDEs to link phenotypic data within dbGaP.
  • To enhance the identification of comparable studies and facilitate future data harmonization.
  • To improve discoverability of variable linkages for cross-study analysis.

Main Methods:

  • PhenX variables were mapped to dbGaP variables to serve as CDEs.
  • Variables were classified as comparable or related based on data collection modes for harmonization.
  • A CDE data field was integrated into dbGaP submission packets to denote PhenX usage and future linkage annotations.

Main Results:

  • 13,653 dbGaP variables across 521 studies were successfully linked using PhenX variable mapping.
  • Variable linkages are now searchable and browsable in dbGaP via a CDE-faceted search filter and the PhenX tool.
  • New dbGaP and PhenX features enable investigators to explore variable linkages and cross-study analysis opportunities.

Conclusions:

  • The PhenX-dbGaP collaboration successfully established a framework for using PhenX variables as CDEs.
  • This approach enhances the ability to identify comparable datasets and facilitates data reuse within dbGaP.
  • Improved data discoverability and linkage capabilities support advanced cross-study research.