Comprehensive evaluation of ACMG/AMP-based variant classification tools
All data and source code required to reproduce the findings of this study are openly available in the Code Ocean repository at https://doi.org/10.24433/CO.6562438.v1.
Authors
- Mark Grosser (ORCID: https://orcid.org/0000-0002-4281-5369)
- Tohid Ghasemnejad (ORCID: https://orcid.org/0000-0002-4746-2320)
- Khadijeh Hoda Jahanian
- Milad Eidi (ORCID: https://orcid.org/0000-0001-5582-4435)
- Seyedeh Sedigheh Abedini (ORCID: https://orcid.org/0000-0003-2671-2295)
- Arash Salmaninejad (ORCID: https://orcid.org/0000-0001-6141-3915)
- Nigel Hamilton Lovell (ORCID: https://orcid.org/0000-0003-1637-1079)
- Thantrira Porntaveetus (ORCID: https://orcid.org/0000-0003-0145-9801)
- Yuheng Liang
- Mahmoud Aarabi (ORCID: https://orcid.org/0000-0002-9342-5205)
- Fabrizzio Horta
- Hamid Alinejad-Rokny
Institutions
- Centre National de la Recherche Scientifique (FR)
- The University of Sydney (AU)
- Mayo Clinic (US)
- Chulalongkorn University (TH)
- University of Pittsburgh (US)
- Royal Hospital for Women (AU)
- UNSW Sydney (AU)
- Houston Fertility Institute (US)
- Pyramid Technical Consultants (United States) (US)
- Mayo Clinic in Florida (US)
- Institut de Génétique Humaine (FR)
- Monash University (AU)
Publication Details
- Journal
- Bioinformatics
- Published
- 2026-02-01
- DOI
- https://doi.org/10.1093/bioinformatics/btaf623
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00