Guidelines for releasing a variant effect predictor

Benjamin J Livesey¹, Mihaly Badonyi¹, Mafalda Dias², Jonathan Frazer², Sushant Kumar^{3

4}, Kresten Lindorff-Larsen⁵, David M McCandlish⁶, Rose Orenbuch⁷, Courtney A Shearer⁷, Lara Muffley⁸, Julia Foreman⁹, Andrew M Glazer¹⁰, Ben Lehner^{11

12

13}, Debora S Marks^{7

14}, Frederick P Roth¹⁵, Alan F Rubin^{16

17}, Lea M Starita⁸, Joseph A Marsh¹⁸

Affiliations

¹ MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
² Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
³ Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
⁴ Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
⁵ Department of Biology, Linderstrøm-Lang Centre for Protein Science, University of Copenhagen, Copenhagen, Denmark.
⁶ Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, NY, USA.
⁷ Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
⁸ Department of Genome Sciences, University of Washingtonand the, Brotman Baty Institute for Precision Medicine , Seattle, WA, USA.
⁹ European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
¹⁰ Vanderbilt University Medical Center, Nashville, TN, USA.
¹¹ Wellcome Sanger Institute, Cambridge, UK.
¹² Universitat Pompeu Fabra (UPF), Barcelona, Spain.
¹³ Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain.
¹⁴ Broad Institute of MIT and Harvard, Boston, MA, USA.
¹⁵ Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
¹⁶ Bioinformatics Division, Walterand , Eliza Hall Institute of Medical Research, Parkville, Australia.
¹⁷ Department of Medical Biology, University of Melbourne, Parkville, Australia.
¹⁸ MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK. joseph.marsh@ed.ac.uk.

PMID: 40234898
PMCID: PMC11998465
DOI: 10.1186/s13059-025-03572-z

Guidelines for releasing a variant effect predictor

Benjamin J Livesey et al. Genome Biol. 2025.

. 2025 Apr 15;26(1):97.

doi: 10.1186/s13059-025-03572-z.

Authors

Affiliations

¹ MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
² Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
³ Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
⁴ Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
⁵ Department of Biology, Linderstrøm-Lang Centre for Protein Science, University of Copenhagen, Copenhagen, Denmark.
⁶ Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, NY, USA.
⁷ Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
⁸ Department of Genome Sciences, University of Washingtonand the, Brotman Baty Institute for Precision Medicine , Seattle, WA, USA.
⁹ European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
¹⁰ Vanderbilt University Medical Center, Nashville, TN, USA.
¹¹ Wellcome Sanger Institute, Cambridge, UK.
¹² Universitat Pompeu Fabra (UPF), Barcelona, Spain.
¹³ Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain.
¹⁴ Broad Institute of MIT and Harvard, Boston, MA, USA.
¹⁵ Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
¹⁶ Bioinformatics Division, Walterand , Eliza Hall Institute of Medical Research, Parkville, Australia.
¹⁷ Department of Medical Biology, University of Melbourne, Parkville, Australia.
¹⁸ MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK. joseph.marsh@ed.ac.uk.

PMID: 40234898
PMCID: PMC11998465
DOI: 10.1186/s13059-025-03572-z

Abstract

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, and there is tremendous variability in their underlying algorithms, outputs, and the ways in which the methodologies and predictions are shared. This leads to considerable difficulties for users trying to navigate the selection and application of VEPs. Here, to address these issues, we provide guidelines and recommendations for the release of novel VEPs.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Competing interests: F.P.R. is a shareholder and advisor for Constantiam Biosciences, Inc.

Figures

**Fig. 1**
Overview of variant effect predictors, including common inputs and outputs, and guidelines for development and release

See this image and copyright information in PMC

Update of

Guidelines for releasing a variant effect predictor.
Livesey BJ, Badonyi M, Dias M, Frazer J, Kumar S, Lindorff-Larsen K, McCandlish DM, Orenbuch R, Shearer CA, Muffley L, Foreman J, Glazer AM, Lehner B, Marks DS, Roth FP, Rubin AF, Starita LM, Marsh JA. Livesey BJ, et al. ArXiv [Preprint]. 2024 Apr 16:arXiv:2404.10807v1. ArXiv. 2024. Update in: Genome Biol. 2025 Apr 15;26(1):97. doi: 10.1186/s13059-025-03572-z. PMID: 38699161 Free PMC article. Updated. Preprint.

References

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Guidelines for releasing a variant effect predictor

Affiliations

Guidelines for releasing a variant effect predictor

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Update of

References

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources