Towards a standard benchmark for phenotype-driven variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework
PhEval and the standardised test corpora solve the issues of patient data availability and experimental tooling configuration when benchmarking and comparing rare disease VGPAs. By providing standardised data on patient cohorts from real-world case-reports and controlling the configuration of evaluated VGPAs, PhEval enables transparent, portable, comparable and reproducible benchmarking of VGPAs. As these tools are often a key component of many rare disease diagnostic pipelines, a thorough and standardised method of assessment is essential for improving patient diagnosis and care.
Authors
- Daniel Korn (ORCID: https://orcid.org/0000-0002-1780-9872)
- Chris Mungall (ORCID: https://orcid.org/0000-0002-6601-2165)
- Nikolaos M. Marinakis (ORCID: https://orcid.org/0000-0002-7078-3253)
- Damian Smedley (ORCID: https://orcid.org/0000-0002-5836-9850)
- Katherina G Cortes (ORCID: https://orcid.org/0000-0002-9489-3158)
- Nomi L. Harris (ORCID: https://orcid.org/0000-0001-6315-3707)
- Aaron Odell
- Nicolas Matentzoglu
- Vinícius de Souza (ORCID: https://orcid.org/0000-0003-3961-0247)
- David Osumi-Sutherland (ORCID: https://orcid.org/0000-0002-7073-9172)
- Melissa Haendel (ORCID: https://orcid.org/0000-0001-9114-8737)
- Julius O.B. Jacobsen (ORCID: https://orcid.org/0000-0002-3265-1591)
- James Alastair McLaughlin (ORCID: https://orcid.org/0000-0002-8361-2795)
- Yasemin Bridges (ORCID: https://orcid.org/0009-0002-1371-3782)
- Peter N. Robinson
Institutions
- University of North Carolina at Chapel Hill (US)
- European Bioinformatics Institute (GB)
- Lawrence Berkeley National Laboratory (US)
- Queen Mary University of London (GB)
- National and Kapodistrian University of Athens (GR)
- Wellcome Sanger Institute (GB)
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE)
- William Harvey Research Institute (GB)
- University of Colorado Anschutz Medical Campus (US)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-03-22
- DOI
- https://doi.org/10.1186/s12859-025-06105-4
- Citations
- 5
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 9.09