GA4GH Work Streams evolve to match the scale of modern genomics

11 Jun 2026

From file formats to federated analysis to artificial intelligence, GA4GH’s Work Streams are evolving to meet the growing needs of the genomics and health fields.

The Global Alliance for Genomics and Health (GA4GH) is announcing two changes to its Work Stream portfolio, continuing a focused effort to ensure the organisation reflects the needs of the genomics community as it stands today, and where it is headed in the future.

Genomics has changed enormously over the past decade. Data volumes have grown by orders of magnitude. Cloud infrastructure has become standard practice across research and clinical settings. Federated analysis across distributed datasets has moved from an aspiration to an operational reality. And artificial intelligence has emerged as one of the most consequential forces reshaping how genomic data is understood and used. GA4GH has always evolved alongside the field it serves, and today’s announcements are the latest expression of that ethos.

The Cloud Work Stream, one of GA4GH’s six technical Work Streams established in 2017, will be renamed the Federated Analysis Work Stream (FAWS). The rename reflects how much the landscape has shifted since 2017. Where “cloud” once captured the frontier of how genomic data was being accessed and analysed, the community has moved toward a more precise and urgent challenge: enabling analysis across distributed data sources without requiring data to ever leave its home. Federated analysis highlights that challenge directly, and the Work Stream will serve as GA4GH’s centre for all development in this space going forward.

Alongside that rename, GA4GH is integrating the portfolio of its Large-Scale Genomics (LSG) Work Stream, also launched in 2017, into other technical Work Streams. LSG’s history predates GA4GH itself. The file formats work that became one of its defining contributions originated within the 1000 Genomes Project, moved into the GA4GH Data Working Group in 2014, and became part of LSG when the Data Working Group evolved into six separate technical Work Streams in 2017. Since then, LSG became the home of some of the most widely used tools and standards in genomics around the world, such as VCF/BCF and SAM/BAM/CRAM. 

The File Formats, Whole Genome Sequencing Quality Control Standards, and Future of VCF product teams will move into the Genomic Knowledge Standards (GKS) Work Stream, a natural home for work that defines how genomic data is represented and interpreted. All APIs currently housed in LSG, including htsget, RNAget, refget, and refget Sequence Collections, will move into the newly named Federated Analysis Work Stream. The Crypt4GH product team will move into the Data Security Work Stream, where its work on encrypted genomic data transfer joins the broader security standards that underpin the entire GA4GH ecosystem.

“Genomics is large-scale everywhere now, and that’s something worth celebrating,” said GA4GH Chief Product Officer Sasha Siegel, who is based at EMBL’s European Bioinformatics Institute (EMBL-EBI), a GA4GH Host Institution. “This is what progress looks like. Work that began in one place has become universal practice, and our Work Streams should reflect that.”

GA4GH extends its deep gratitude to Oliver Hofmann (University of Melbourne) and Thomas Keane (EMBL-EBI), who served as LSG Co-Leads since the group’s founding in 2017, and to Geraldine van der Auwera (Seqera), who joined as a Co-Lead in 2022. Their leadership stewarded some of the most widely used tools and standards in genomics over years of remarkable growth and change.

This announcement is part of a broader, ongoing effort to ensure GA4GH’s Work Streams reflect how the field operates today. The organisation recently launched a new Artificial Intelligence Work Stream (AIWS) and is actively reviewing how it communicates and presents its work to support clearer engagement and participation from researchers, clinicians, and institutions around the world. Additional changes may follow in the coming months, all oriented toward making GA4GH as accessible as possible for the global genomics community.