hCNV2Beacon -a Galaxy workflow for integrated CNV detection and federated data sharing

GA4GH Beacon v2 enables the discovery of genomic and phenotypic datasets while addressing clinical genomics and healthcare requirements through open standards and a reference implementation toolkit. The Beacon v2 Reference Implementation (B2RI) simplifies deployment for institutions and researchers with limited expertise in database and API development. To support wider adoption, Beacon v2 tools were integrated into the Galaxy platform, and the Beacon2 Import toolkit was developed to import data from Galaxy histories into a designated Beacon v2 database and to execute protocol-compliant queries.The hCNV2Beacon Galaxy workflow was developed. This workflow involves importing raw data from federated EGA to Galaxy using RDConnect, using the Galaxy CNVkit toolkit to detect CNVs from the imported data. The resulting output is converted into the Beacon v2 format using custom-developed tools and subsequently uploaded to the Beacon database.To support user adoption, Galaxy Training Network (GTN) tutorials were created to guide researchers through B2RI setup, Galaxy tool usage, and interaction with Beacon v2 services. These tutorials emphasise FAIR principles, interoperability, reproducibility, and accessibility, promoting transparent data sharing and secure federated discovery across diverse platforms.By embedding Beacon v2 capabilities within Galaxy, this work reduces technical barriers, empowers CNV researchers with streamlined, FAIR-compliant workflows for data analysis, discovery, and sharing, and fosters broader participation in federated genomics initiatives.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-07
DOI
https://doi.org/10.5281/zenodo.16761917
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
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article

hCNV2Beacon -a Galaxy workflow for integrated CNV detection and federated data sharing

Zenodo (CERN European Organization for Nuclear Research)
Genomics and Rare Diseases
article

hCNV2Beacon -a Galaxy workflow for integrated CNV detection and federated data sharing

article en

Abstract

GA4GH Beacon v2 enables the discovery of genomic and phenotypic datasets while addressing clinical genomics and healthcare requirements through open standards and a reference implementation toolkit. The Beacon v2 Reference Implementation (B2RI) simplifies deployment for institutions and researchers with limited expertise in database and API development. To support wider adoption, Beacon v2 tools were integrated into the Galaxy platform, and the Beacon2 Import toolkit was developed to import data from Galaxy histories into a designated Beacon v2 database and to execute protocol-compliant queries.The hCNV2Beacon Galaxy workflow was developed. This workflow involves importing raw data from federated EGA to Galaxy using RDConnect, using the Galaxy CNVkit toolkit to detect CNVs from the imported data. The resulting output is converted into the Beacon v2 format using custom-developed tools and subsequently uploaded to the Beacon database.To support user adoption, Galaxy Training Network (GTN) tutorials were created to guide researchers through B2RI setup, Galaxy tool usage, and interaction with Beacon v2 services. These tutorials emphasise FAIR principles, interoperability, reproducibility, and accessibility, promoting transparent data sharing and secure federated discovery across diverse platforms.By embedding Beacon v2 capabilities within Galaxy, this work reduces technical barriers, empowers CNV researchers with streamlined, FAIR-compliant workflows for data analysis, discovery, and sharing, and fosters broader participation in federated genomics initiatives.

Zenodo (CERN European Organization for Nuclear Research)
University of Bradford (GB), Erasmus MC (NL)
Partnerships for the goals
Openalex Percentile: Top 55%
Genomics and Rare Diseases
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hCNV2Beacon -a Galaxy workflow for integrated CNV detection and federated data sharing · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS