When a patient has their DNA sequenced, the clinical test shows specific changes in their genes. But when researchers collect knowledge and make statements about genomic evidence, they typically look at categories of variation.

For example, take the phrase “TP53 R248 mutations.” A study on breast cancer might use that phrase to refer to point mutations at location TP53.* The phrase is therefore categorical: it aggregates all variants leading to changes at amino acid position R248 of protein TP53.

The rise of categorical variants presents two problems. First, to interpret whether an assayed variant leads to disease, you need to manually search and collate knowledge spread across multiple categorical variants — a slow, error-prone process. Second, complex relationships between categorical variants frustrate efforts to curate and maintain the knowledge-bases that are crucial for connecting genes and disease.

The Categorical Variation (CatVar) Study Group tackles these problems by exploring a formal, computable specification for categorical variants.

*Berns et al. 1998.

Jump to...

Benefits

• Will make genomic knowledge associated with categorical variants computable and efficiently searchable
• Promotes more efficient and consistent sharing, curation, and availability of genomic knowledge across GA4GH Work Streams and partner organisations
• Ensures effective use of categorical variant knowledge — both now and as genomic knowledge grows in the future

Target users

Researchers, clinicians, clinical laboratories, data generators, data custodians, developers, and research institutes