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FAIR data retrieval for sensitive clinical research data in Galaxy.
Ouwerkerk, Jasper; Rasche, Helena; Spalding, John D; Hiltemann, Saskia; Stubbs, Andrew P.
Afiliación
  • Ouwerkerk J; Clinical Bioinformatics Group, Department of Pathology, Erasmus Medical Center, 3015 CN, Rotterdam, the Netherlands.
  • Rasche H; Clinical Bioinformatics Group, Department of Pathology, Erasmus Medical Center, 3015 CN, Rotterdam, the Netherlands.
  • Spalding JD; CSC-IT Center for Science, 02101 Espoo, Finland.
  • Hiltemann S; Clinical Bioinformatics Group, Department of Pathology, Erasmus Medical Center, 3015 CN, Rotterdam, the Netherlands.
  • Stubbs AP; Clinical Bioinformatics Group, Department of Pathology, Erasmus Medical Center, 3015 CN, Rotterdam, the Netherlands.
Gigascience ; 132024 01 02.
Article en En | MEDLINE | ID: mdl-38280189
ABSTRACT

BACKGROUND:

In clinical research, data have to be accessible and reproducible, but the generated data are becoming larger and analysis complex. Here we propose a platform for Findable, Accessible, Interoperable, and Reusable (FAIR) data access and creating reproducible findings. Standardized access to a major genomic repository, the European Genome-Phenome Archive (EGA), has been achieved with API services like PyEGA3. We aim to provide a FAIR data analysis service in Galaxy by retrieving genomic data from the EGA and provide a generalized "omics" platform for FAIR data analysis.

RESULTS:

To demonstrate this, we implemented an end-to-end Galaxy workflow to replicate the findings from an RD-Connect synthetic dataset Beyond the 1 Million Genomes (synB1MG) available from the EGA. We developed the PyEGA3 connector within Galaxy to easily download multiple datasets from the EGA. We added the gene.iobio tool, a diagnostic environment for precision genomics, to Galaxy and demonstrate that it provides a more dynamic and interpretable view for trio analysis results. We developed a Galaxy trio analysis workflow to determine the pathogenic variants from the synB1MG trios using the GEMINI and gene.iobio tool. The complete workflow is available at WorkflowHub, and an associated tutorial was created in the Galaxy Training Network, which helps researchers unfamiliar with Galaxy to run the workflow.

CONCLUSIONS:

We showed the feasibility of reusing data from the EGA in Galaxy via PyEGA3 and validated the workflow by rediscovering spiked-in variants in synthetic data. Finally, we improved existing tools in Galaxy and created a workflow for trio analysis to demonstrate the value of FAIR genomics analysis in Galaxy.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genómica Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Gigascience Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Genómica Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Gigascience Año: 2024 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos