GDI D8.9 - Distributed analysis and federated learning PoC

This deliverable describes the design, implementation, and testing of a demonstrator for federated analysis within the European Genomic Data Infrastructure (GDI) project. It showcases a practical execution of a privacy-preserving Genome-Wide Association Study using a distributed architecture. Each participating national node (CZ, DE, PT, ES, SI, FI, EE) ran analyses locally, preserving data sovereignty and complying with legal constraints such as the GDPR. This demonstrator was built upon prior strategic and technical evaluations (previous deliverables and discussion from both WP7 and WP8) of federated technologies, validating the technical feasibility of GA4GH-compliant TES workflows. It leverages tools such as Snakemake, Docker, and MinIO, with Funnel serving as the TES endpoint. This prototype, using synthetic1 data previously distributed across the national nodes and generated for this demonstrator, paves the way for federated learning and cross-border analytics at scale.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-08
DOI
https://doi.org/10.5281/zenodo.16882880
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

GDI D8.9 - Distributed analysis and federated learning PoC

Zenodo (CERN European Organization for Nuclear Research)
Diverse Scientific and Economic Studies
article

GDI D8.9 - Distributed analysis and federated learning PoC

article en

Abstract

This deliverable describes the design, implementation, and testing of a demonstrator for federated analysis within the European Genomic Data Infrastructure (GDI) project. It showcases a practical execution of a privacy-preserving Genome-Wide Association Study using a distributed architecture. Each participating national node (CZ, DE, PT, ES, SI, FI, EE) ran analyses locally, preserving data sovereignty and complying with legal constraints such as the GDPR. This demonstrator was built upon prior strategic and technical evaluations (previous deliverables and discussion from both WP7 and WP8) of federated technologies, validating the technical feasibility of GA4GH-compliant TES workflows. It leverages tools such as Snakemake, Docker, and MinIO, with Funnel serving as the TES endpoint. This prototype, using synthetic1 data previously distributed across the national nodes and generated for this demonstrator, paves the way for federated learning and cross-border analytics at scale.

Zenodo (CERN European Organization for Nuclear Research)
Barcelona Supercomputing Center (ES), Universitat Politècnica de Catalunya (ES)
Industry, innovation and infrastructure
Openalex Percentile: Top 36%
Diverse Scientific and Economic Studies
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GDI D8.9 - Distributed analysis and federated learning PoC · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS