Guidelines for releasing a variant effect predictor

Author(s): 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;
Details: Publication Year 2025-04-15,Volume 26,Issue #1,Page 97
Journal Title: Genome Biology
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.
Publisher: BMC
Keywords: Humans; *Genetic Variation; Algorithms; *Mutation; Guidelines as Topic; *Computational Biology/methods; Software
Research Division(s): Bioinformatics and Computational Biology
PubMed ID: 40234898
Publisher's Version: https://doi.org/10.1186/s13059-025-03572-z
Open Access at Publisher's Site: https://doi.org/10.1186/s13059-025-03572-z
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2025-12-05 09:11:09

Last Modified: 2025-12-05 09:29:23