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Learn how GA4GH helps expand responsible genomic data use to benefit human health.
Sequence Annotation (SA)
Aims to develop a flexible, common model for describing genomic features
Researchers use a process called sequence annotation to document detailed information about a specific feature on a DNA sequence. To standardise how this information is captured, the GA4GH Genomic Knowledge Standards (GKS) Work Stream is developing the Sequence Annotation (SA) specification. The SA specification aims to define an extensible, common model for describing specific genomic regions of interest.
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Benefits
- Aims to develop a data model for core genomic entities such as gene, transcript, and regulatory region
- Will allow software developers to extend the model to explore specific needs
Target users
Developers
THEME
CATEGORY
TYPE
STATUS
Work Streams
LATEST VERSION
In progress
Product Leads
- Evan Christensen
- Karen EIlbeck
- Sean Upchurch
Staff Contact
Community resources
Dive deeper into this product! SA will provide a model for describing genomic features such as transcripts, genes, regulatory elements, and other related regions of interest. Developers can extend the SA model to cover their specific needs with the confidence that the core entities will remain compatible with others using the SA model.
Title
Info
Repeat
Day
Time
Duration
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
Date
Title
15 Dec 2023
14 Sep 2023
Don't see your name? Get in touch:
- Evan Christensen
University of Utah - Karen Eilbeck
University of Utah - Robert Freimuth
Mayo Clinic - Kais Ghedira
Institut Pasteur de Tunis - Roderic Guigo
Centre for Genomic Regulation - John Marshall
University of Glasgow - Jean Muller
Laboratoire de génétique médicale (UMR_S 1112) - Francis Ouellette
McGill University / Université McGill - Emilio Righi
Centre for Genomic Regulation - Dmitriy Sonkin
NIH National Cancer Institute (NCI) - David Steinberg
University of California, Santa Cruz - Sean Upchurch
California Institute of Technology - Andy Yates
EMBL's European Bioinformatics Institute (EBI)