About us
Learn how GA4GH helps expand responsible genomic data use to benefit human health.
Clinical & 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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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.
Products
Family History Toolkit
Provides tools and best practices for documenting family health history information
Federated Cohort Building
Aims to explore methods for researchers to search across cohorts
Pedigree
Allows for computable exchange of family health history and representation of larger, more complex families
Pharmacogenomics Data Standardisation
Aims to develop a pharmacogenomics data standard to address translational gaps across disparate health systems and enable equitable clinical decision support
Phenopackets
Offers a human and machine-readable way to structure clinical and phenotypic data about a patient or individual
Publications
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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Date
Title
Info
5 Jun 2023
A new GA4GH Study Group explores the standardisation and storage of pharmacogenomic data
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Title
Info
Repeat
Day
Time
Duration
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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Date
Title
22 Feb 2024
15 Dec 2023
7 Nov 2023
19 Sep 2023
14 Sep 2023
14 Sep 2023
5 May 2023
28 Apr 2023
30 Mar 2023
11 Mar 2023
22 Feb 2022
29 Aug 2019
7 Feb 2016
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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