Guidelines for releasing a variant effect predictor
Computational methods for assessing the likely impacts of mutations, known as variant effect predictors (VEPs), are widely used in the assessment and interpretation of human genetic variation, as well as in other applications like protein engineering. Many different VEPs have been released to date, and there is tremendous variability in their underlying algorithms and outputs, and in the ways in which the methodologies and predictions are shared. This leads to considerable challenges for end users in knowing which VEPs to use and how to use them. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs. Emphasising open-source availability, transparent methodologies, clear variant effect score interpretations, standardised scales, accessible predictions, and rigorous training data disclosure, we aim to improve the usability and interpretability of VEPs, and promote their integration into analysis and evaluation pipelines. We also provide a large, categorised list of currently available VEPs, aiming to facilitate the discovery and encourage the usage of novel methods within the scientific community.
Authors
- Alan F. Rubin (ORCID: https://orcid.org/0000-0003-1474-605X)
- David M. McCandlish (ORCID: https://orcid.org/0009-0006-1474-0407)
- Joseph A. Marsh (ORCID: https://orcid.org/0000-0003-4132-0628)
- Benjamin Livesey (ORCID: https://orcid.org/0000-0001-6866-1452)
- Mihaly Badonyi (ORCID: https://orcid.org/0000-0002-8305-5618)
- Kresten Lindorff‐Larsen (ORCID: https://orcid.org/0000-0002-4750-6039)
- Andrew M. Glazer (ORCID: https://orcid.org/0000-0002-3938-4713)
- Debora S. Marks (ORCID: https://orcid.org/0000-0001-9388-2281)
- Lara A. Muffley (ORCID: https://orcid.org/0000-0002-3035-3339)
- Rose Orenbuch (ORCID: https://orcid.org/0000-0002-4678-0837)
- Julia Foreman (ORCID: https://orcid.org/0000-0003-4567-2479)
- Jonathan Frazer (ORCID: https://orcid.org/0000-0001-6900-6484)
- Mafalda Dias (ORCID: https://orcid.org/0000-0002-1804-8542)
- Courtney A. Shearer (ORCID: https://orcid.org/0009-0006-8489-7434)
- Lea M. Starita (ORCID: https://orcid.org/0000-0003-2870-5099)
- Ben Lehner (ORCID: https://orcid.org/0000-0002-8817-1124)
- Sushant Kumar (ORCID: https://orcid.org/0000-0002-0317-8520)
- Frederick P. Roth (ORCID: https://orcid.org/0000-0002-6628-649X)
Institutions
- Broad Institute (US)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- University of Copenhagen (DK)
- European Bioinformatics Institute (GB)
- University Health Network (CA)
- Harvard University (US)
- The University of Melbourne (AU)
- University of Pittsburgh (US)
- Universitat Pompeu Fabra (ES)
- University of Toronto (CA)
- Cold Spring Harbor Laboratory (US)
- Wellcome Sanger Institute (GB)
- Princess Margaret Cancer Centre (CA)
- Centre for Genomic Regulation (ES)
- Center for Systems Biology (US)
- Institute of Genetics and Cancer (GB)
- Vanderbilt University Medical Center (US)
- University of Edinburgh (GB)
Publication Details
- Journal
- Genome biology
- Published
- 2025-04-15
- DOI
- https://doi.org/10.1186/s13059-025-03572-z
- Citations
- 20
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 25.44
Funders
- Johns Hopkins University
- Wellcome Trust
- Chan Zuckerberg Initiative
- Australian Government
- European Commission
- Novo Nordisk
- Ministerio de Ciencia e Innovación
- Novo Nordisk Fonden
- National Institutes of Health
- Medical Research Council
- European Research Council
- Center for Information Technology