Dataset Information

Systematically linking tranSMART, Galaxy and EGA for reusing human translational research data.

ABSTRACT: The availability of high-throughput molecular profiling techniques has provided more accurate and informative data for regular clinical studies. Nevertheless, complex computational workflows are required to interpret these data. Over the past years, the data volume has been growing explosively, requiring robust human data management to organise and integrate the data efficiently. For this reason, we set up an ELIXIR implementation study, together with the Translational research IT (TraIT) programme, to design a data ecosystem that is able to link raw and interpreted data. In this project, the data from the TraIT Cell Line Use Case (TraIT-CLUC) are used as a test case for this system. Within this ecosystem, we use the European Genome-phenome Archive (EGA) to store raw molecular profiling data; tranSMART to collect interpreted molecular profiling data and clinical data for corresponding samples; and Galaxy to store, run and manage the computational workflows. We can integrate these data by linking their repositories systematically. To showcase our design, we have structured the TraIT-CLUC data, which contain a variety of molecular profiling data types, for storage in both tranSMART and EGA. The metadata provided allows referencing between tranSMART and EGA, fulfilling the cycle of data submission and discovery; we have also designed a data flow from EGA to Galaxy, enabling reanalysis of the raw data in Galaxy. In this way, users can select patient cohorts in tranSMART, trace them back to the raw data and perform (re)analysis in Galaxy. Our conclusion is that the majority of metadata does not necessarily need to be stored (redundantly) in both databases, but that instead FAIR persistent identifiers should be available for well-defined data ontology levels: study, data access committee, physical sample, data sample and raw data file. This approach will pave the way for the stable linkage and reuse of data.

SUBMITTER: Zhang C

PROVIDER: S-EPMC5657030 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Systematically linking tranSMART, Galaxy and EGA for reusing human translational research data.

Zhang Chao C Bijlard Jochem J Staiger Christine C Scollen Serena S van Enckevort David D Hoogstrate Youri Y Senf Alexander A Hiltemann Saskia S Repo Susanna S Pipping Wibo W Bierkens Mariska M Payralbe Stefan S Stringer Bas B Heringa Jaap J Stubbs Andrew A Bonino Da Silva Santos Luiz Olavo LO Belien Jeroen J Weistra Ward W Azevedo Rita R van Bochove Kees K Meijer Gerrit G Boiten Jan-Willem JW Rambla Jordi J Fijneman Remond R Spalding J Dylan JD Abeln Sanne S

F1000Research 20170816

The availability of high-throughput molecular profiling techniques has provided more accurate and informative data for regular clinical studies. Nevertheless, complex computational workflows are required to interpret these data. Over the past years, the data volume has been growing explosively, requiring robust human data management to organise and integrate the data efficiently. For this reason, we set up an ELIXIR implementation study, together with the Translational research IT (TraIT) progra ...[more]

PMID: 29123641

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Project description:ObjectivesThe reuse of electronic patient data collected during clinical care has received increased attention as a way to increase our evidence base. The purpose of this paper was to review studies reusing electronic patient data for dental research.Data sources1527 citations obtained by searching MEDLINE and Embase databases, hand-searching seven dental and informatics journals, and snowball sampling.Study selectionWe included studies reusing electronic patient data for research on dental and craniofacial topics, alone or in combination with medical conditions, medications and outcomes. Studies using administrative or research databases and systematic reviews were excluded. Three reviewers extracted data independently and performed analysis jointlyResultsThe 60 studies reviewed covered epidemiological (32 studies), outcomes (16), health services research (10) and other (2) topics; were primarily retrospective (58 studies); varied significantly in sample size (9-153,619 patients) and follow-up period (1-12 years); often drew on other data sources in addition to electronic ones (25); but rarely tapped electronic dental record (EDR) data in private practices (3). Type of research was not associated with data sources used, but research topics/questions were. The most commonly reported advantages of reusing electronic data were being able to study large samples and saving time, while data quality and the inability to capture study-specific data were identified as major limitations.ConclusionsDental research reusing electronic patient data is nascent but accelerating. Future EDR design should focus on enhancing data quality, begin to integrate research data collection and implement interoperability with electronic medical records to facilitate oral-systemic investigations.Clinical significanceMeasuring and improving the quality of dental care requires that we begin to reuse electronic patient data collected in practice for clinical research. Practice data can potentially serve as a useful complement to data collected in traditional research studies.

Dataset Information

Systematically linking tranSMART, Galaxy and EGA for reusing human translational research data.

Publications

Systematically linking tranSMART, Galaxy and EGA for reusing human translational research data.

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