Genomic Knowledge StandardsGenomic Knowledge Standards (GKS) Work Stream

Designs technical standards that enable computer-to-computer exchange of information about genomes, improving the search and application of genomic knowledge.

When a doctor worries their patient might have a genetic disease, they can test a person’s genome to find differences (variants) which might cause the disease. The sheer number of variants a person has — around 5 million on average — presents a significant challenge in finding out which variants may impact their clinical care. Even computers struggle to run searches for clinically-important variants because there is no standard language for describing the evidence needed.

The Genomic Knowledge Standards (GKS) Work Stream works to define a common language for computers to describe variants — and the important biomedical knowledge associated with them — that may affect clinical care. As a result, GKS makes it easier for laboratories, researchers, and hospitals to find this information and improve patient health outcomes. 

Jump to...

The GKS Work Stream is defining a common language for computers to describe variants — and the important biomedical knowledge associated with them — that may affect clinical care.
Image summary: The GKS Work Stream is defining a common language for computers to describe variants — and the important biomedical knowledge associated with them — that may affect clinical care.
Contribute to this Work Stream

Subscribe to receive meeting invitations and real-time announcements.


Join the Work Stream
Technical description
Standardises the exchange of genomic knowledge through common APIs, schemas, and software. Enables interoperability between diagnostic laboratories, electronic health records, researchers, and knowledge bases — leading to better health outcomes.
work stream leads
staff contact
TOOLS & PLATFORMS

Products

Community Resources

Dive deeper into our Work Stream! GKS creates standards to exchange reference genomic information through schemas, APIs, and software. The Work Stream has developed products to unambiguously represent variation and reference genomic sequences. Knowledge linked to variants can be exchanged through GKS products, and wider efforts will expand the Work Stream’s efforts to other important genomic landmarks, such as genes. Clear genomic representation and annotation improve analyses and enable diagnostic laboratories, electronic health records, research institutions, and knowledge bases to compare results.


#

Title

Info

Repeat

Day

Time

Duration

CatVar meets biweekly, alternating between the first Wednesday of the month and the 3rd Tuesday of the Month.

Monthly
Wednesday
19:00 UTC
1 Hour

CatVar meets biweekly, alternating between the first Wednesday of the month and the 3rd Tuesday of the Month.

Monthly
Tuesday
12:00 UTC
1 Hour

This Study Group meets to discuss data standardisation and storage in the field of pharmacogenetics, and explores ways GA4GH might be able to help.

Every Two Months
Wednesday
15:00 UTC
1 Hour

Working meeting to describe genomic features including transcripts, genes, regulatory elements, and related regions of interest, Sequence Annotation is creating an expandable, shared model

 

 

Monthly
Thursday
15:00 UTC
1 Hour

This group meets to tackle the problem of representing structural variations in sequenced DNA.

Monthly
Thursday
12:00 UTC
1 Hour

This meeting will focus on the VA roadmap and will attempt to get feedback from interested Driver Projects and team members.

Monthly
Wednesday
15:00 UTC
1 Hour

This working meeting focused on implementation support aims to create cloud-based services and tools for generating, transforming, and validating content using the GKS specifications.

 

Bi-Weekly
Monday
15:00 UTC
1 Hour

This working meeting focused on implementation support aims to create cloud-based services and tools for generating, transforming, and validating content using the GKS specifications.

Meets on the third Monday of each month.

Monthly
Monday
21:00 UTC
1 Hour
#

Don't see your name? Get in touch:

  • Irina Armean
    EMBL's European Bioinformatics Institute (EBI)
  • Larry Babb
    Broad Institute of MIT and Harvard
  • Salem Bajjali
    Mayo Clinic
  • Michael Baudis
    University of Zurich
  • Jacqui Beckmann
    Université de Lausanne
  • Nicolas Bertin
    Genome Institute of Singapore
  • Steven Brenner
    University of California, Berkeley
  • Matt Brush
    Oregon Health & Science University
  • Daniel Cameron
    Walter and Eliza Hall Institute of Medical Research
  • Evan Christensen
    University of Utah
  • Melissa Cline
    University of California, Santa Cruz
  • Raymond Dalgleish
    University of Leicester
  • Karen Eilbeck
    University of Utah
  • Ramon Felciano
    Digital Alchemy
  • Kyle Ferriter
    Broad Institute of MIT and Harvard
  • Robert Freimuth
    Mayo Clinic
  • Kais Ghedira
    Institut Pasteur de Tunis
  • Wesley Goar
    Nationwide Children’s Hospital
  • Malachi Griffith
    The Genome Institute at Washington University, Variant Interpretation for Cancer Consortium (VICC)
  • Roderic Guigo
    Centre for Genomic Regulation
  • Melissa Haendel
    University of Colorado Anschutz Medical Campus
  • Reece Hart
    MyOme
  • Seik-Soon Khor
    National Center for Global Health and Medicine
  • Melissa Konopko
    ELIXIR
  • Kori Kuzma
    Nationwide Children’s Hospital
  • Jennifer Lee
    Sequencing.com
  • Christa Lese Martin
    Geisinger Health System
  • Xuelu (Jeff) Liu
    Dana-Farber Cancer Institute
  • Javier Lopez
    Genomics England
  • John Marshall
    University of Glasgow
  • John McDermott
    Manchester University NHS Foundation Trust
  • Eric Moyer
    NIH National Center for Biotechnology Information (NCBI)
  • Jean Muller
    Laboratoire de génétique médicale (UMR_S 1112)
  • Tristan Nelson
    Geisinger Health System
  • Vivek Nuthalapati
    Epic Systems
  • Francis Ouellette
    McGill University / Université McGill
  • Rahel Paloots
    University of Zurich
  • Andreas Prlić
    Invitae, Inc.
  • Daniel Puthawala
    Nationwide Children’s Hospital
  • Heidi Rehm
    Massachusetts General Hospital, Broad Institute of MIT and Harvard
  • Kevin Riehle
    Baylor College of Medicine
  • Emilio Righi
    Centre for Genomic Regulation
  • Videha Sharma
    Manchester University
  • Anastasia Smith
    Nationwide Children’s Hospital
  • Dmitriy Sonkin
    NIH National Cancer Institute (NCI)
  • Kathryn Stahl
    Nationwide Children’s Hospital
  • David Steinberg
    University of California, Santa Cruz
  • James Stevenson
    Nationwide Children’s Hospital
  • Jing Su
    Wellcome Sanger Institute (WSI)
  • David Tamborero
    Karolinska Institutet
  • Mrinal Thomas
    Epic Systems
  • Sean Upchurch
    California Institute of Technology
  • Alex Wagner
    Nationwide Children’s Hospital, Variant Interpretation for Cancer Consortium (VICC)
  • Ziying Yang
    University of Zurich
  • Zhenyu Zhang
    University of Chicago
  • Hangjia Zhao
    University of Zurich