Clinical & Phenotypic Data CaptureClinical & Phenotypic Data Capture (Clin/Pheno) Work Stream

Helps clinicians and researchers store, describe, and send data about observable traits (phenotypes) and clinical care.
Advances like electronic health records, deep phenotyping methods, and genetic testing offer the opportunity to build genomics into our digital health infrastructure. Patient care would improve if clinicians could quickly share genomic test results or link patient symptoms to genetic variants. The Clinical & Phenotypic Data Capture (Clin/Pheno) Work Stream accelerates the use of genomics in medicine by standardising how we describe clinical data, with a particular focus on observable traits (phenotypes) and family health history information. Clin/Pheno produces information models and standards that help clinicians and researchers capture, describe, and exchange clinical and phenotypic data.

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The Clinical and Phenotypic Data Capture Work Stream supports clinical adoption of genomics through information models and standards for describing and exchanging clinical data.
Image summary: The Clinical and Phenotypic Data Capture Work Stream supports clinical adoption of genomics through information models and standards for describing and exchanging clinical data.
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Technical description
Accelerates the use of genomics in medicine by producing standard ontologies and information models to describe clinical and phenotypic data, including the capture and exchange of information between clinical, research, and patient-centred systems.
work stream leads
  • Mélanie Courtot
  • Monica Munoz-Torres
staff contact
TOOLS & PLATFORMS

Products

Community Resources

Dive deeper into our Work Stream! Clin/Pheno establishes information models and technical standards to describe clinical and phenotypic data for use in genomic medicine and research, including for the capture and exchange of information between clinical, research, and patient-centred systems. As part of these efforts, the Work Stream coordinates the integration of clinical and phenotypic data with other GA4GH and external products.


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5 Jun 2023
A new GA4GH Study Group explores the standardisation and storage of pharmacogenomic data
12 May 2023
Tell us what you think!
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Meeting of all Clin/Pheno Work Stream contributors to discus various topics including but not limited to subgroup updates, implementations, new project ideas, roadmapping, event planning, etc

A key goal of this meeting is to build community within Clin/Pheno.

Every Two Months
Wednesday
19:00 UTC
1 Hour

Working meeting to explore existing GA4GH tools and standards to address search across cohorts and assess the need for additional components.

ad hoc
ad hoc
UTC
1 Hour

Working meeting for the development of the GA4GH Pedigree product, including discussion of implementations and support tooling

Bi-Weekly
Thursday
20:00 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 for the development of the GA4GH Phenopackets product, including discussion of implementations and support tooling

ad hoc
ad hoc
UTC
1 Hour
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Don't see your name? Get in touch:

  • Jacqui Beckmann
    Université de Lausanne
  • Sergi Beltran
    CNAG CRG
  • Michael Brudno
    University Health Network
  • Orion Buske
    PhenoTips
  • Chritopher Chute
    Johns Hopkins University School of Medicine
  • Mélanie Courtot
    Ontario Institute for Cancer Research (OICR)
  • Megan Doerr
    Sage Bionetworks
  • Shahim Essaid
    University of Colorado Anschutz Medical Campus
  • Mallory Freeberg
    EMBL's European Bioinformatics Institute (EBI)
  • Robert Freimuth
    Mayo Clinic
  • Ian Green
    SNOMED International
  • Tudor Groza
    EMBL's European Bioinformatics Institute (EBI)
  • Melissa Haendel
    University of Colorado Anschutz Medical Campus
  • David Hansen
    CSIRO
  • Tim Jackson
    TrakGene
  • Jules Jacobsen
    Queen Mary University of London
  • Sebastian Koehler
    Ada Health
  • Guida Landoure
    University of Sciences, Techniques and Technologies of Bamako (USTTB)
  • Zane Lombard
    University of the Witwatersrand, National Health Laboratory Service
  • Mamana Mbiyavanga
    University of Cape Town
  • John McDermott
    Manchester University NHS Foundation Trust
  • Monica Munoz-Torres
    University of Colorado Anschutz Medical Campus
  • Sabine Oesterle
    SIB Swiss Institute of Bioinformatics
  • Soichi Ogishima
    Tohoku University Tohoku, Medical Megabank Organization
  • Helen Parkinson
    EMBL's European Bioinformatics Institute (EBI)
  • Peter Robinson
    The Jackson Laboratory
  • Videha Sharma
    Manchester University
  • Zornitza Stark
    Australian Genomics
  • Kathryn Van Diemen
    TrakGene
  • Susheel Varma
    Information Commissioner's Office
  • Grant Wood
    MyGenomeTrust
  • Christina Yung
    Ontario Institute for Cancer Research (OICR), Indoc Research
  • Ksenia Zaytseva
    Canadian Centre for Computational Genomics, McGill University / Université McGill